Ryan Malloy
c747abe813
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Build Ghidra Plugin / build (push) Has been cancelled
- Implement pagination system for large responses (10K+ items) - Add grep/regex filtering capability to results - Session isolation for multi-client MCP scenarios - Cursor management tools (next, list, delete, delete_all) - Upgrade to mcp>=1.22.0 for FastMCP Context support - Switch to date-based versioning (2025.12.1) - Add prominent _message field to guide LLMs on cursor usage 10 tools with pagination support: - functions_list - list all functions - functions_decompile - decompiled code (line pagination) - functions_disassemble - assembly (instruction pagination) - functions_get_variables - function variables - data_list - defined data items - data_list_strings - string data - xrefs_list - cross-references - structs_list - struct types - analysis_get_callgraph - call graph edges - analysis_get_dataflow - data flow steps
4183 lines
141 KiB
Python
4183 lines
141 KiB
Python
# /// script
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# requires-python = ">=3.11"
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# dependencies = [
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# "mcp>=1.22.0",
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# "requests>=2.32.3",
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# ]
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# ///
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# GhydraMCP Bridge for Ghidra HATEOAS API - Optimized for MCP integration
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# Provides namespaced tools for interacting with Ghidra's reverse engineering capabilities
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# Features: Cursor-based pagination, grep filtering, session isolation
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import os
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import signal
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import sys
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import threading
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import time
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from threading import Lock
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from typing import Dict, List, Optional, Union, Any
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from urllib.parse import quote, urlencode, urlparse
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import requests
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from mcp.server.fastmcp import FastMCP, Context
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# ================= Core Infrastructure =================
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ALLOWED_ORIGINS = os.environ.get(
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"GHIDRA_ALLOWED_ORIGINS", "http://localhost").split(",")
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active_instances: Dict[int, dict] = {}
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instances_lock = Lock()
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DEFAULT_GHIDRA_PORT = 8192
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DEFAULT_GHIDRA_HOST = "localhost"
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QUICK_DISCOVERY_RANGE = range(DEFAULT_GHIDRA_PORT, DEFAULT_GHIDRA_PORT+10)
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FULL_DISCOVERY_RANGE = range(DEFAULT_GHIDRA_PORT, DEFAULT_GHIDRA_PORT+20)
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BRIDGE_VERSION = "2025-12-01"
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REQUIRED_API_VERSION = 2010
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current_instance_port = DEFAULT_GHIDRA_PORT
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# ================= Cursor-Based Pagination System =================
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# Provides efficient pagination with grep filtering for large responses
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# Inspired by mcplaywright pagination system
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import re
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import hashlib
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import json
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from dataclasses import dataclass, field
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from typing import Callable, Iterator
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from collections import OrderedDict
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# Configuration
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CURSOR_TTL_SECONDS = 300 # 5 minutes
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CURSOR_MAX_CACHE_SIZE = 100 # Maximum number of cached cursors
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DEFAULT_PAGE_SIZE = 50
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MAX_PAGE_SIZE = 500
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TOKEN_ESTIMATION_RATIO = 4.0 # Roughly 4 chars per token
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# ReDoS Protection Configuration
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MAX_GREP_PATTERN_LENGTH = 500 # Maximum regex pattern length
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MAX_GREP_REPETITION_OPS = 15 # Maximum repetition operators (* + ? {})
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MAX_GREP_RECURSION_DEPTH = 10 # Maximum depth for nested data grep matching
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def compile_safe_pattern(pattern: str, flags: int = 0) -> re.Pattern:
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"""Compile regex pattern with ReDoS protection
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Validates pattern to prevent catastrophic backtracking attacks.
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Rejects patterns that are too long or have excessive repetition operators.
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Args:
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pattern: Regex pattern string
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flags: Regex compilation flags
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Returns:
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Compiled regex pattern
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Raises:
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ValueError: If pattern fails safety validation
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"""
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if not pattern:
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raise ValueError("Empty pattern")
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# Check pattern length
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if len(pattern) > MAX_GREP_PATTERN_LENGTH:
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raise ValueError(
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f"Pattern too long ({len(pattern)} chars, max {MAX_GREP_PATTERN_LENGTH}). "
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"Consider using a simpler pattern or substring match."
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)
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# Count repetition operators that could cause catastrophic backtracking
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# These are the main culprits: nested quantifiers like (a+)+, (a*)*
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repetition_ops = pattern.count('*') + pattern.count('+') + pattern.count('?')
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# Also count bounded repetitions {n,m}
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repetition_ops += len(re.findall(r'\{[0-9,]+\}', pattern))
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if repetition_ops > MAX_GREP_REPETITION_OPS:
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raise ValueError(
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f"Pattern has too many repetition operators ({repetition_ops}, max {MAX_GREP_REPETITION_OPS}). "
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"This could cause performance issues. Consider simplifying the pattern."
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)
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# Check for common dangerous patterns (nested quantifiers)
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dangerous_patterns = [
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r'\([^)]*[*+][^)]*\)[*+]', # (a+)+ or (a*)*
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r'\([^)]*[*+][^)]*\)\{', # (a+){n,m}
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]
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for dangerous in dangerous_patterns:
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if re.search(dangerous, pattern):
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raise ValueError(
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"Pattern contains nested quantifiers which could cause exponential backtracking. "
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"Example: (a+)+ is dangerous. Consider using atomic groups or simplifying."
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)
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# Try to compile the pattern
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try:
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return re.compile(pattern, flags)
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except re.error as e:
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raise ValueError(f"Invalid regex pattern: {e}")
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@dataclass
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class CursorState:
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"""Represents the state of a paginated query with session isolation"""
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cursor_id: str # Unique cursor identifier
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session_id: str # Session isolation key
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tool_name: str # Tool that created this cursor
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query_hash: str # Hash of original query parameters
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data: List[Any] # Full result set (or filtered)
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total_count: int # Total items before pagination
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filtered_count: int # Items after grep filtering
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current_offset: int = 0
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page_size: int = DEFAULT_PAGE_SIZE
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grep_pattern: str = None
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grep_flags: int = 0
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created_at: float = field(default_factory=time.time)
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last_accessed: float = field(default_factory=time.time)
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@property
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def is_expired(self) -> bool:
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return time.time() - self.last_accessed > CURSOR_TTL_SECONDS
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@property
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def has_more(self) -> bool:
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return self.current_offset + self.page_size < self.filtered_count
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@property
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def current_page(self) -> int:
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return (self.current_offset // self.page_size) + 1
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@property
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def total_pages(self) -> int:
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return max(1, (self.filtered_count + self.page_size - 1) // self.page_size)
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@property
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def ttl_remaining(self) -> int:
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return max(0, int(CURSOR_TTL_SECONDS - (time.time() - self.last_accessed)))
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def verify_session(self, session_id: str) -> bool:
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"""Verify cursor belongs to requesting session"""
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return self.session_id == session_id
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class CursorManager:
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"""Thread-safe cursor manager with TTL-based expiration and session isolation"""
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def __init__(self):
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self._cursors: OrderedDict[str, CursorState] = OrderedDict()
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self._session_cursors: Dict[str, set] = {} # session_id -> set of cursor_ids
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self._lock = Lock()
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def _generate_cursor_id(self, query_hash: str, session_id: str) -> str:
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"""Generate a unique cursor ID"""
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unique = f"{session_id}-{query_hash}-{time.time()}-{id(self)}"
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return hashlib.sha256(unique.encode()).hexdigest()[:16]
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def _cleanup_expired(self):
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"""Remove expired cursors (call while holding lock)"""
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expired = [cid for cid, state in self._cursors.items() if state.is_expired]
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for cid in expired:
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state = self._cursors[cid]
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# Remove from session tracking
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if state.session_id in self._session_cursors:
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self._session_cursors[state.session_id].discard(cid)
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del self._cursors[cid]
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# Also enforce max cache size (LRU eviction)
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while len(self._cursors) > CURSOR_MAX_CACHE_SIZE:
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oldest_id, oldest_state = self._cursors.popitem(last=False)
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if oldest_state.session_id in self._session_cursors:
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self._session_cursors[oldest_state.session_id].discard(oldest_id)
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def create_cursor(self, data: List[Any], query_params: dict,
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tool_name: str = "unknown",
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session_id: str = "default",
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grep_pattern: str = None, grep_flags: int = 0,
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page_size: int = DEFAULT_PAGE_SIZE) -> tuple[str, CursorState]:
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"""Create a new cursor for paginated results
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Args:
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data: The full result set to paginate
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query_params: Original query parameters (for hashing)
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tool_name: Name of tool creating cursor
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session_id: Session identifier for isolation
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grep_pattern: Optional regex pattern to filter results
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grep_flags: Regex flags (re.IGNORECASE, etc.)
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page_size: Items per page
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Returns:
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Tuple of (cursor_id, cursor_state)
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"""
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# Apply grep filtering if pattern provided (with ReDoS protection)
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filtered_data = data
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if grep_pattern:
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pattern = compile_safe_pattern(grep_pattern, grep_flags)
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filtered_data = [
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item for item in data
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if self._matches_grep(item, pattern)
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]
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# Create query hash for deduplication
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query_hash = hashlib.md5(
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json.dumps(query_params, sort_keys=True, default=str).encode()
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).hexdigest()[:12]
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with self._lock:
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self._cleanup_expired()
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cursor_id = self._generate_cursor_id(query_hash, session_id)
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state = CursorState(
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cursor_id=cursor_id,
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session_id=session_id,
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tool_name=tool_name,
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query_hash=query_hash,
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data=filtered_data,
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total_count=len(data),
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filtered_count=len(filtered_data),
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page_size=min(page_size, MAX_PAGE_SIZE),
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grep_pattern=grep_pattern,
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grep_flags=grep_flags
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)
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self._cursors[cursor_id] = state
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# Track by session
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if session_id not in self._session_cursors:
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self._session_cursors[session_id] = set()
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self._session_cursors[session_id].add(cursor_id)
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return cursor_id, state
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def get_cursor(self, cursor_id: str, session_id: str = None) -> Optional[CursorState]:
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"""Retrieve a cursor by ID, optionally validating session
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Args:
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cursor_id: The cursor identifier
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session_id: Optional session to validate against
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Returns:
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CursorState if found and valid, None otherwise
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"""
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with self._lock:
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self._cleanup_expired()
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if cursor_id not in self._cursors:
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return None
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state = self._cursors[cursor_id]
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if state.is_expired:
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del self._cursors[cursor_id]
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if state.session_id in self._session_cursors:
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self._session_cursors[state.session_id].discard(cursor_id)
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return None
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# Validate session if provided
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if session_id and not state.verify_session(session_id):
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return None
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state.last_accessed = time.time()
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# Move to end (most recently used)
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self._cursors.move_to_end(cursor_id)
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return state
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def advance_cursor(self, cursor_id: str, session_id: str = None) -> Optional[CursorState]:
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"""Advance cursor to next page
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Args:
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cursor_id: The cursor identifier
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session_id: Optional session to validate against
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Returns:
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Updated CursorState or None if invalid/expired
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"""
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with self._lock:
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state = self._cursors.get(cursor_id)
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if not state or state.is_expired:
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return None
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if session_id and not state.verify_session(session_id):
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return None
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state.current_offset += state.page_size
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state.last_accessed = time.time()
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self._cursors.move_to_end(cursor_id)
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return state
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def delete_cursor(self, cursor_id: str, session_id: str = None) -> bool:
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"""Explicitly delete a cursor
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Args:
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cursor_id: The cursor identifier
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session_id: Optional session to validate against
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Returns:
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True if deleted, False if not found or session mismatch
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"""
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with self._lock:
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if cursor_id not in self._cursors:
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return False
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state = self._cursors[cursor_id]
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if session_id and not state.verify_session(session_id):
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return False
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if state.session_id in self._session_cursors:
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self._session_cursors[state.session_id].discard(cursor_id)
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del self._cursors[cursor_id]
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return True
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def delete_session_cursors(self, session_id: str) -> int:
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"""Delete all cursors for a session
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Args:
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session_id: The session identifier
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Returns:
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Number of cursors deleted
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"""
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with self._lock:
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if session_id not in self._session_cursors:
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return 0
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cursor_ids = list(self._session_cursors[session_id])
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count = 0
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for cid in cursor_ids:
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if cid in self._cursors:
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del self._cursors[cid]
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count += 1
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del self._session_cursors[session_id]
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return count
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def get_page(self, state: CursorState) -> List[Any]:
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"""Get current page of data from cursor state"""
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start = state.current_offset
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end = start + state.page_size
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return state.data[start:end]
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def _matches_grep(self, item: Any, pattern: re.Pattern, depth: int = 0) -> bool:
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"""Check if an item matches the grep pattern
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Searches through string representations of dict values,
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list items, or the item itself.
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Args:
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item: The item to search
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pattern: Compiled regex pattern
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depth: Current recursion depth (for stack overflow protection)
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Returns:
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True if pattern matches anywhere in the item
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"""
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# Prevent stack overflow from deeply nested structures
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if depth > MAX_GREP_RECURSION_DEPTH:
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return False
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if isinstance(item, dict):
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# Search all string values in the dict (recursively)
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for key, value in item.items():
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if isinstance(value, str) and pattern.search(value):
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return True
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elif isinstance(value, (int, float)):
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if pattern.search(str(value)):
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return True
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elif isinstance(value, dict):
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if self._matches_grep(value, pattern, depth + 1):
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return True
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elif isinstance(value, (list, tuple)):
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if self._matches_grep(value, pattern, depth + 1):
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return True
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return False
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elif isinstance(item, (list, tuple)):
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return any(self._matches_grep(i, pattern, depth + 1) for i in item)
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elif isinstance(item, str):
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return bool(pattern.search(item))
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else:
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return bool(pattern.search(str(item)))
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def list_cursors(self, session_id: str = None) -> List[dict]:
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"""List active cursors, optionally filtered by session
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Args:
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session_id: Optional session filter
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Returns:
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List of cursor info dicts
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"""
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with self._lock:
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self._cleanup_expired()
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return [
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{
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"cursor_id": cid,
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"session_id": state.session_id,
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"tool_name": state.tool_name,
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"total_count": state.total_count,
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"filtered_count": state.filtered_count,
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"current_page": state.current_page,
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"total_pages": state.total_pages,
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"current_offset": state.current_offset,
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"page_size": state.page_size,
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"has_more": state.has_more,
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"grep_pattern": state.grep_pattern,
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"age_seconds": int(time.time() - state.created_at),
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"ttl_remaining": state.ttl_remaining
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}
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for cid, state in self._cursors.items()
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if session_id is None or state.session_id == session_id
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]
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def get_stats(self) -> dict:
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"""Get cursor manager statistics"""
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with self._lock:
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self._cleanup_expired()
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return {
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"total_cursors": len(self._cursors),
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"total_sessions": len(self._session_cursors),
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"max_cache_size": CURSOR_MAX_CACHE_SIZE,
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"ttl_seconds": CURSOR_TTL_SECONDS,
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"cursors_per_session": {
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sid: len(cids) for sid, cids in self._session_cursors.items()
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}
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}
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# Global cursor manager instance
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cursor_manager = CursorManager()
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def estimate_tokens(data: List[Any]) -> int:
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"""Estimate token count for a list of items"""
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text = json.dumps(data, default=str)
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return int(len(text) / TOKEN_ESTIMATION_RATIO)
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def paginate_response(data: List[Any], query_params: dict,
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tool_name: str = "unknown",
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session_id: str = "default",
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page_size: int = DEFAULT_PAGE_SIZE,
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grep: str = None, grep_ignorecase: bool = True,
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return_all: bool = False) -> dict:
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"""Create a paginated response with optional grep filtering
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Args:
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data: Full result list to paginate
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query_params: Original query parameters (for cursor creation)
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tool_name: Name of the tool creating this response
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session_id: Session identifier for cursor isolation
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page_size: Items per page (default: 50, max: 500)
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grep: Optional regex pattern to filter results
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grep_ignorecase: Case-insensitive grep (default: True)
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return_all: Bypass pagination and return all results (with warning)
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Returns:
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dict with pagination metadata and results
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"""
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grep_flags = re.IGNORECASE if grep_ignorecase else 0
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# Handle return_all bypass
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if return_all:
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# Apply grep filtering even for return_all
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filtered_data = data
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if grep:
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try:
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pattern = compile_safe_pattern(grep, grep_flags)
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filtered_data = [
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item for item in data
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if cursor_manager._matches_grep(item, pattern)
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]
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except ValueError as e:
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return {
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"success": False,
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"error": {
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"code": "INVALID_GREP_PATTERN",
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"message": str(e)
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},
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"timestamp": int(time.time() * 1000)
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}
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estimated_tokens = estimate_tokens(filtered_data)
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warning = None
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|
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if estimated_tokens > 50000:
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warning = f"🚨 EXTREMELY LARGE response (~{estimated_tokens:,} tokens) - may cause issues"
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elif estimated_tokens > 20000:
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warning = f"⚠️ VERY LARGE response (~{estimated_tokens:,} tokens) - consider using pagination"
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elif estimated_tokens > 8000:
|
|
warning = f"⚠️ Large response (~{estimated_tokens:,} tokens)"
|
|
|
|
return {
|
|
"success": True,
|
|
"result": filtered_data,
|
|
"pagination": {
|
|
"bypassed": True,
|
|
"total_count": len(data),
|
|
"filtered_count": len(filtered_data),
|
|
"grep_pattern": grep,
|
|
"estimated_tokens": estimated_tokens,
|
|
"warning": warning
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
# Normal pagination flow
|
|
try:
|
|
cursor_id, state = cursor_manager.create_cursor(
|
|
data=data,
|
|
query_params=query_params,
|
|
tool_name=tool_name,
|
|
session_id=session_id,
|
|
grep_pattern=grep,
|
|
grep_flags=grep_flags,
|
|
page_size=page_size
|
|
)
|
|
except ValueError as e:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "INVALID_GREP_PATTERN",
|
|
"message": str(e)
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
current_page = cursor_manager.get_page(state)
|
|
|
|
# Only include cursor_id if there are more pages
|
|
response_cursor = cursor_id if state.has_more else None
|
|
|
|
# Build response with prominent continuation message for LLMs
|
|
response = {
|
|
"success": True,
|
|
"result": current_page,
|
|
"pagination": {
|
|
"cursor_id": response_cursor,
|
|
"session_id": session_id,
|
|
"total_count": state.total_count,
|
|
"filtered_count": state.filtered_count,
|
|
"page_size": state.page_size,
|
|
"current_page": state.current_page,
|
|
"total_pages": state.total_pages,
|
|
"has_more": state.has_more,
|
|
"grep_pattern": grep,
|
|
"items_returned": len(current_page),
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
# Add prominent message for LLMs when more data is available
|
|
if state.has_more:
|
|
remaining = state.filtered_count - (state.current_page * state.page_size)
|
|
response["_message"] = (
|
|
f"📄 Showing {len(current_page)} of {state.filtered_count} items "
|
|
f"(page {state.current_page}/{state.total_pages}). "
|
|
f"To get the next {min(state.page_size, remaining)} items, call: "
|
|
f"cursor_next(cursor_id='{cursor_id}')"
|
|
)
|
|
else:
|
|
response["_message"] = f"✅ Complete: {len(current_page)} items returned (all results)"
|
|
|
|
return response
|
|
|
|
|
|
# ================= End Cursor System =================
|
|
|
|
instructions = """
|
|
GhydraMCP allows interacting with multiple Ghidra SRE instances. Ghidra SRE is a tool for reverse engineering and analyzing binaries, e.g. malware.
|
|
|
|
First, run `instances_list()` to see all available Ghidra instances (automatically discovers instances on the default host).
|
|
Then use `instances_use(port)` to set your working instance.
|
|
|
|
Note: Use `instances_discover(host)` only if you need to scan a different host.
|
|
|
|
The API is organized into namespaces for different types of operations:
|
|
- instances_* : For managing Ghidra instances
|
|
- functions_* : For working with functions
|
|
- data_* : For working with data items
|
|
- structs_* : For creating and managing struct data types
|
|
- memory_* : For memory access
|
|
- xrefs_* : For cross-references
|
|
- analysis_* : For program analysis
|
|
- cursor_* : For pagination cursor management
|
|
|
|
## Pagination System
|
|
The following tools support cursor-based pagination with grep filtering:
|
|
- `functions_list` - List functions (can be 10K+)
|
|
- `functions_decompile` - Decompiled code lines (grep for patterns like "if.*NULL")
|
|
- `functions_disassemble` - Assembly instructions (grep for "CALL", "JMP", etc.)
|
|
- `functions_get_variables` - Function variables (grep for "local_", "param", etc.)
|
|
- `data_list` - List data items
|
|
- `data_list_strings` - List string data
|
|
- `xrefs_list` - List cross-references (can be very large for common functions)
|
|
- `structs_list` - List struct types
|
|
- `structs_get` - Struct fields (grep for field names/types in large structs)
|
|
- `analysis_get_callgraph` - Call graph edges (grep for function names)
|
|
- `analysis_get_dataflow` - Data flow steps (grep for opcodes/registers)
|
|
|
|
Pagination parameters:
|
|
- `page_size`: Items per page (default: 50, max: 500)
|
|
- `grep`: Regex pattern to filter results (e.g., "main|init", "FUN_00.*")
|
|
- `grep_ignorecase`: Case-insensitive grep (default: True)
|
|
- `return_all`: Bypass pagination and return all results (use with caution)
|
|
|
|
When results are paginated, the response includes a `_message` field with instructions.
|
|
Use `cursor_next(cursor_id)` to fetch the next page of results.
|
|
Use `cursor_list()` to see active cursors.
|
|
Use `cursor_delete(cursor_id)` to clean up cursors.
|
|
"""
|
|
|
|
mcp = FastMCP("GhydraMCP", instructions=instructions)
|
|
|
|
ghidra_host = os.environ.get("GHIDRA_HYDRA_HOST", DEFAULT_GHIDRA_HOST)
|
|
|
|
# Helper function to get the current instance or validate a specific port
|
|
def _get_instance_port(port=None):
|
|
"""Internal helper to get the current instance port or validate a specific port"""
|
|
port = port or current_instance_port
|
|
# Validate that the instance exists and is active
|
|
if port not in active_instances:
|
|
# Try to register it if not found
|
|
register_instance(port)
|
|
if port not in active_instances:
|
|
raise ValueError(f"No active Ghidra instance on port {port}")
|
|
return port
|
|
|
|
# The rest of the utility functions (HTTP helpers, etc.) remain the same...
|
|
def get_instance_url(port: int) -> str:
|
|
"""Get URL for a Ghidra instance by port"""
|
|
with instances_lock:
|
|
if port in active_instances:
|
|
return active_instances[port]["url"]
|
|
|
|
if 8192 <= port <= 65535:
|
|
register_instance(port)
|
|
if port in active_instances:
|
|
return active_instances[port]["url"]
|
|
|
|
return f"http://{ghidra_host}:{port}"
|
|
|
|
def validate_origin(headers: dict) -> bool:
|
|
"""Validate request origin against allowed origins"""
|
|
origin = headers.get("Origin")
|
|
if not origin:
|
|
# No origin header - allow (browser same-origin policy applies)
|
|
return True
|
|
|
|
# Parse origin to get scheme+hostname
|
|
try:
|
|
parsed = urlparse(origin)
|
|
origin_base = f"{parsed.scheme}://{parsed.hostname}"
|
|
if parsed.port:
|
|
origin_base += f":{parsed.port}"
|
|
except:
|
|
return False
|
|
|
|
return origin_base in ALLOWED_ORIGINS
|
|
|
|
def _make_request(method: str, port: int, endpoint: str, params: dict = None,
|
|
json_data: dict = None, data: str = None,
|
|
headers: dict = None) -> dict:
|
|
"""Internal helper to make HTTP requests and handle common errors."""
|
|
url = f"{get_instance_url(port)}/{endpoint}"
|
|
|
|
# Set up headers according to HATEOAS API expected format
|
|
request_headers = {
|
|
'Accept': 'application/json',
|
|
'X-Request-ID': f"mcp-bridge-{int(time.time() * 1000)}"
|
|
}
|
|
|
|
if headers:
|
|
request_headers.update(headers)
|
|
|
|
is_state_changing = method.upper() in ["POST", "PUT", "PATCH", "DELETE"]
|
|
if is_state_changing:
|
|
check_headers = json_data.get("headers", {}) if isinstance(
|
|
json_data, dict) else (headers or {})
|
|
if not validate_origin(check_headers):
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "ORIGIN_NOT_ALLOWED",
|
|
"message": "Origin not allowed for state-changing request"
|
|
},
|
|
"status_code": 403,
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
if json_data is not None:
|
|
request_headers['Content-Type'] = 'application/json'
|
|
elif data is not None:
|
|
request_headers['Content-Type'] = 'text/plain'
|
|
|
|
try:
|
|
response = requests.request(
|
|
method,
|
|
url,
|
|
params=params,
|
|
json=json_data,
|
|
data=data,
|
|
headers=request_headers,
|
|
timeout=10
|
|
)
|
|
|
|
try:
|
|
parsed_json = response.json()
|
|
|
|
# Add timestamp if not present
|
|
if isinstance(parsed_json, dict) and "timestamp" not in parsed_json:
|
|
parsed_json["timestamp"] = int(time.time() * 1000)
|
|
|
|
# Check for HATEOAS compliant error response format and reformat if needed
|
|
if not response.ok and isinstance(parsed_json, dict) and "success" in parsed_json and not parsed_json["success"]:
|
|
# Check if error is in the expected HATEOAS format
|
|
if "error" in parsed_json and not isinstance(parsed_json["error"], dict):
|
|
# Convert string error to the proper format
|
|
error_message = parsed_json["error"]
|
|
parsed_json["error"] = {
|
|
"code": f"HTTP_{response.status_code}",
|
|
"message": error_message
|
|
}
|
|
|
|
return parsed_json
|
|
|
|
except ValueError:
|
|
if response.ok:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "NON_JSON_RESPONSE",
|
|
"message": "Received non-JSON success response from Ghidra plugin"
|
|
},
|
|
"status_code": response.status_code,
|
|
"response_text": response.text[:500],
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
else:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": f"HTTP_{response.status_code}",
|
|
"message": f"Non-JSON error response: {response.text[:100]}..."
|
|
},
|
|
"status_code": response.status_code,
|
|
"response_text": response.text[:500],
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
except requests.exceptions.Timeout:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "REQUEST_TIMEOUT",
|
|
"message": "Request timed out"
|
|
},
|
|
"status_code": 408,
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
except requests.exceptions.ConnectionError:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "CONNECTION_ERROR",
|
|
"message": f"Failed to connect to Ghidra instance at {url}"
|
|
},
|
|
"status_code": 503,
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
except Exception as e:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "UNEXPECTED_ERROR",
|
|
"message": f"An unexpected error occurred: {str(e)}"
|
|
},
|
|
"exception": e.__class__.__name__,
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
def safe_get(port: int, endpoint: str, params: dict = None) -> dict:
|
|
"""Make GET request to Ghidra instance"""
|
|
return _make_request("GET", port, endpoint, params=params)
|
|
|
|
def safe_put(port: int, endpoint: str, data: dict) -> dict:
|
|
"""Make PUT request to Ghidra instance with JSON payload"""
|
|
headers = data.pop("headers", None) if isinstance(data, dict) else None
|
|
return _make_request("PUT", port, endpoint, json_data=data, headers=headers)
|
|
|
|
def safe_post(port: int, endpoint: str, data: Union[dict, str]) -> dict:
|
|
"""Perform a POST request to a specific Ghidra instance with JSON or text payload"""
|
|
headers = None
|
|
json_payload = None
|
|
text_payload = None
|
|
|
|
if isinstance(data, dict):
|
|
headers = data.pop("headers", None)
|
|
json_payload = data
|
|
else:
|
|
text_payload = data
|
|
|
|
return _make_request("POST", port, endpoint, json_data=json_payload, data=text_payload, headers=headers)
|
|
|
|
def safe_patch(port: int, endpoint: str, data: dict) -> dict:
|
|
"""Perform a PATCH request to a specific Ghidra instance with JSON payload"""
|
|
headers = data.pop("headers", None) if isinstance(data, dict) else None
|
|
return _make_request("PATCH", port, endpoint, json_data=data, headers=headers)
|
|
|
|
def safe_delete(port: int, endpoint: str) -> dict:
|
|
"""Perform a DELETE request to a specific Ghidra instance"""
|
|
return _make_request("DELETE", port, endpoint)
|
|
|
|
def simplify_response(response: dict) -> dict:
|
|
"""
|
|
Simplify HATEOAS response data for easier AI agent consumption
|
|
- Removes _links from result entries
|
|
- Flattens nested structures when appropriate
|
|
- Preserves important metadata
|
|
- Converts structured data like disassembly to text for easier consumption
|
|
"""
|
|
if not isinstance(response, dict):
|
|
return response
|
|
|
|
# Make a copy to avoid modifying the original
|
|
result = response.copy()
|
|
|
|
# Store API response metadata
|
|
api_metadata = {}
|
|
for key in ["id", "instance", "timestamp", "size", "offset", "limit"]:
|
|
if key in result:
|
|
api_metadata[key] = result.get(key)
|
|
|
|
# Simplify the main result data if present
|
|
if "result" in result:
|
|
# Handle array results
|
|
if isinstance(result["result"], list):
|
|
simplified_items = []
|
|
for item in result["result"]:
|
|
if isinstance(item, dict):
|
|
# Store but remove HATEOAS links from individual items
|
|
item_copy = item.copy()
|
|
links = item_copy.pop("_links", None)
|
|
|
|
# Optionally store direct href links as more accessible properties
|
|
# This helps AI agents navigate the API without understanding HATEOAS
|
|
if isinstance(links, dict):
|
|
for link_name, link_data in links.items():
|
|
if isinstance(link_data, dict) and "href" in link_data:
|
|
item_copy[f"{link_name}_url"] = link_data["href"]
|
|
|
|
simplified_items.append(item_copy)
|
|
else:
|
|
simplified_items.append(item)
|
|
result["result"] = simplified_items
|
|
|
|
# Handle object results
|
|
elif isinstance(result["result"], dict):
|
|
result_copy = result["result"].copy()
|
|
|
|
# Store but remove links from result object
|
|
links = result_copy.pop("_links", None)
|
|
|
|
# Add direct href links for easier navigation
|
|
if isinstance(links, dict):
|
|
for link_name, link_data in links.items():
|
|
if isinstance(link_data, dict) and "href" in link_data:
|
|
result_copy[f"{link_name}_url"] = link_data["href"]
|
|
|
|
# Special case for disassembly - convert to text for easier consumption
|
|
if "instructions" in result_copy and isinstance(result_copy["instructions"], list):
|
|
disasm_text = ""
|
|
for instr in result_copy["instructions"]:
|
|
if isinstance(instr, dict):
|
|
addr = instr.get("address", "")
|
|
mnemonic = instr.get("mnemonic", "")
|
|
operands = instr.get("operands", "")
|
|
bytes_str = instr.get("bytes", "")
|
|
|
|
# Format: address: bytes mnemonic operands
|
|
disasm_text += f"{addr}: {bytes_str.ljust(10)} {mnemonic} {operands}\n"
|
|
|
|
# Add the text representation
|
|
result_copy["disassembly_text"] = disasm_text
|
|
# Remove the original structured instructions to simplify the response
|
|
result_copy.pop("instructions", None)
|
|
|
|
# Special case for decompiled code - make sure it's directly accessible
|
|
if "ccode" in result_copy:
|
|
result_copy["decompiled_text"] = result_copy["ccode"]
|
|
elif "decompiled" in result_copy:
|
|
result_copy["decompiled_text"] = result_copy["decompiled"]
|
|
|
|
result["result"] = result_copy
|
|
|
|
# Store but remove HATEOAS links from the top level
|
|
links = result.pop("_links", None)
|
|
|
|
# Add direct href links in a more accessible format
|
|
if isinstance(links, dict):
|
|
api_links = {}
|
|
for link_name, link_data in links.items():
|
|
if isinstance(link_data, dict) and "href" in link_data:
|
|
api_links[link_name] = link_data["href"]
|
|
|
|
# Add simplified links
|
|
if api_links:
|
|
result["api_links"] = api_links
|
|
|
|
# Restore API metadata
|
|
for key, value in api_metadata.items():
|
|
if key not in result:
|
|
result[key] = value
|
|
|
|
return result
|
|
|
|
def register_instance(port: int, url: str = None) -> str:
|
|
"""Register a new Ghidra instance
|
|
|
|
Args:
|
|
port: Port number of the Ghidra instance
|
|
url: Optional URL if different from default http://host:port
|
|
|
|
Returns:
|
|
str: Confirmation message or error
|
|
"""
|
|
if url is None:
|
|
url = f"http://{ghidra_host}:{port}"
|
|
|
|
try:
|
|
# Check for HATEOAS API by checking plugin-version endpoint
|
|
test_url = f"{url}/plugin-version"
|
|
response = requests.get(test_url, timeout=2)
|
|
|
|
if not response.ok:
|
|
return f"Error: Instance at {url} is not responding properly to HATEOAS API"
|
|
|
|
project_info = {"url": url}
|
|
|
|
try:
|
|
# Check plugin version to ensure compatibility
|
|
try:
|
|
version_data = response.json()
|
|
if "result" in version_data:
|
|
result = version_data["result"]
|
|
if isinstance(result, dict):
|
|
plugin_version = result.get("plugin_version", "")
|
|
api_version = result.get("api_version", 0)
|
|
|
|
project_info["plugin_version"] = plugin_version
|
|
project_info["api_version"] = api_version
|
|
|
|
# Verify API version compatibility
|
|
if api_version != REQUIRED_API_VERSION:
|
|
error_msg = f"API version mismatch: Plugin reports version {api_version}, but bridge requires version {REQUIRED_API_VERSION}"
|
|
print(error_msg, file=sys.stderr)
|
|
return error_msg
|
|
|
|
print(f"Connected to Ghidra plugin version {plugin_version} with API version {api_version}")
|
|
except Exception as e:
|
|
print(f"Error parsing plugin version: {e}", file=sys.stderr)
|
|
|
|
# Get program info from HATEOAS API
|
|
info_url = f"{url}/program"
|
|
|
|
try:
|
|
info_response = requests.get(info_url, timeout=2)
|
|
if info_response.ok:
|
|
try:
|
|
info_data = info_response.json()
|
|
if "result" in info_data:
|
|
result = info_data["result"]
|
|
if isinstance(result, dict):
|
|
# Extract project and file from programId (format: "project:/file")
|
|
program_id = result.get("programId", "")
|
|
if ":" in program_id:
|
|
project_name, file_path = program_id.split(":", 1)
|
|
project_info["project"] = project_name
|
|
# Remove leading slash from file path if present
|
|
if file_path.startswith("/"):
|
|
file_path = file_path[1:]
|
|
project_info["path"] = file_path
|
|
|
|
# Get file name directly from the result
|
|
project_info["file"] = result.get("name", "")
|
|
|
|
# Get other metadata
|
|
project_info["language_id"] = result.get("languageId", "")
|
|
project_info["compiler_spec_id"] = result.get("compilerSpecId", "")
|
|
project_info["image_base"] = result.get("image_base", "")
|
|
|
|
# Store _links from result for HATEOAS navigation
|
|
if "_links" in result:
|
|
project_info["_links"] = result.get("_links", {})
|
|
except Exception as e:
|
|
print(f"Error parsing info endpoint: {e}", file=sys.stderr)
|
|
except Exception as e:
|
|
print(f"Error connecting to info endpoint: {e}", file=sys.stderr)
|
|
except Exception:
|
|
# Non-critical, continue with registration even if project info fails
|
|
pass
|
|
|
|
with instances_lock:
|
|
active_instances[port] = project_info
|
|
|
|
return f"Registered instance on port {port} at {url}"
|
|
except Exception as e:
|
|
return f"Error: Could not connect to instance at {url}: {str(e)}"
|
|
|
|
def _discover_instances(port_range, host=None, timeout=0.5) -> dict:
|
|
"""Internal function to discover NEW Ghidra instances by scanning ports
|
|
|
|
This function only returns newly discovered instances that weren't already
|
|
in the active_instances registry. Use instances_discover() for a complete
|
|
list including already known instances.
|
|
"""
|
|
found_instances = []
|
|
scan_host = host if host is not None else ghidra_host
|
|
|
|
for port in port_range:
|
|
if port in active_instances:
|
|
continue # Skip already known instances
|
|
|
|
url = f"http://{scan_host}:{port}"
|
|
try:
|
|
# Try HATEOAS API via plugin-version endpoint
|
|
test_url = f"{url}/plugin-version"
|
|
response = requests.get(test_url,
|
|
headers={'Accept': 'application/json',
|
|
'X-Request-ID': f"discovery-{int(time.time() * 1000)}"},
|
|
timeout=timeout)
|
|
|
|
if response.ok:
|
|
# Further validate it's a GhydraMCP instance by checking response format
|
|
try:
|
|
json_data = response.json()
|
|
if "success" in json_data and json_data["success"] and "result" in json_data:
|
|
# Looks like a valid HATEOAS API response
|
|
# Instead of relying only on register_instance, which already checks program info,
|
|
# extract additional information here for more detailed discovery results
|
|
result = register_instance(port, url)
|
|
|
|
# Initialize report info
|
|
instance_info = {
|
|
"port": port,
|
|
"url": url
|
|
}
|
|
|
|
# Extract version info for reporting
|
|
if isinstance(json_data["result"], dict):
|
|
instance_info["plugin_version"] = json_data["result"].get("plugin_version", "unknown")
|
|
instance_info["api_version"] = json_data["result"].get("api_version", "unknown")
|
|
else:
|
|
instance_info["plugin_version"] = "unknown"
|
|
instance_info["api_version"] = "unknown"
|
|
|
|
# Include project details from registered instance in the report
|
|
if port in active_instances:
|
|
instance_info["project"] = active_instances[port].get("project", "")
|
|
instance_info["file"] = active_instances[port].get("file", "")
|
|
|
|
instance_info["result"] = result
|
|
found_instances.append(instance_info)
|
|
except (ValueError, KeyError):
|
|
# Not a valid JSON response or missing expected keys
|
|
print(f"Port {port} returned non-HATEOAS response", file=sys.stderr)
|
|
continue
|
|
|
|
except requests.exceptions.RequestException:
|
|
# Instance not available, just continue
|
|
continue
|
|
|
|
return {
|
|
"found": len(found_instances),
|
|
"instances": found_instances
|
|
}
|
|
|
|
def periodic_discovery():
|
|
"""Periodically discover new instances"""
|
|
while True:
|
|
try:
|
|
_discover_instances(FULL_DISCOVERY_RANGE, timeout=0.5)
|
|
|
|
with instances_lock:
|
|
ports_to_remove = []
|
|
for port, info in active_instances.items():
|
|
url = info["url"]
|
|
try:
|
|
# Check HATEOAS API via plugin-version endpoint
|
|
response = requests.get(f"{url}/plugin-version", timeout=1)
|
|
if not response.ok:
|
|
ports_to_remove.append(port)
|
|
continue
|
|
|
|
# Update program info if available (especially to get project name)
|
|
try:
|
|
info_url = f"{url}/program"
|
|
info_response = requests.get(info_url, timeout=1)
|
|
if info_response.ok:
|
|
try:
|
|
info_data = info_response.json()
|
|
if "result" in info_data:
|
|
result = info_data["result"]
|
|
if isinstance(result, dict):
|
|
# Extract project and file from programId (format: "project:/file")
|
|
program_id = result.get("programId", "")
|
|
if ":" in program_id:
|
|
project_name, file_path = program_id.split(":", 1)
|
|
info["project"] = project_name
|
|
# Remove leading slash from file path if present
|
|
if file_path.startswith("/"):
|
|
file_path = file_path[1:]
|
|
info["path"] = file_path
|
|
|
|
# Get file name directly from the result
|
|
info["file"] = result.get("name", "")
|
|
|
|
# Get other metadata
|
|
info["language_id"] = result.get("languageId", "")
|
|
info["compiler_spec_id"] = result.get("compilerSpecId", "")
|
|
info["image_base"] = result.get("image_base", "")
|
|
except Exception as e:
|
|
print(f"Error parsing info endpoint during discovery: {e}", file=sys.stderr)
|
|
except Exception:
|
|
# Non-critical, continue even if update fails
|
|
pass
|
|
|
|
except requests.exceptions.RequestException:
|
|
ports_to_remove.append(port)
|
|
|
|
for port in ports_to_remove:
|
|
del active_instances[port]
|
|
print(f"Removed unreachable instance on port {port}")
|
|
except Exception as e:
|
|
print(f"Error in periodic discovery: {e}")
|
|
|
|
time.sleep(30)
|
|
|
|
def handle_sigint(signum, frame):
|
|
os._exit(0)
|
|
|
|
# ================= MCP Resources =================
|
|
# Resources provide information that can be loaded directly into context
|
|
# They focus on data and minimize metadata
|
|
|
|
@mcp.resource(uri="/instance/{port}")
|
|
def ghidra_instance(port: int = None) -> dict:
|
|
"""Get detailed information about a Ghidra instance and the loaded program
|
|
|
|
Args:
|
|
port: Specific Ghidra instance port (optional, uses current if omitted)
|
|
|
|
Returns:
|
|
dict: Detailed information about the Ghidra instance and loaded program
|
|
"""
|
|
port = _get_instance_port(port)
|
|
response = safe_get(port, "program")
|
|
|
|
if not isinstance(response, dict) or not response.get("success", False):
|
|
return {"error": f"Unable to access Ghidra instance on port {port}"}
|
|
|
|
# Extract only the most relevant information for the resource
|
|
result = response.get("result", {})
|
|
|
|
if not isinstance(result, dict):
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "INVALID_RESPONSE",
|
|
"message": "Invalid response format from Ghidra instance"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
instance_info = {
|
|
"port": port,
|
|
"url": get_instance_url(port),
|
|
"program_name": result.get("name", "unknown"),
|
|
"program_id": result.get("programId", "unknown"),
|
|
"language": result.get("languageId", "unknown"),
|
|
"compiler": result.get("compilerSpecId", "unknown"),
|
|
"base_address": result.get("imageBase", "0x0"),
|
|
"memory_size": result.get("memorySize", 0),
|
|
"analysis_complete": result.get("analysisComplete", False)
|
|
}
|
|
|
|
# Add project information if available
|
|
if "project" in active_instances[port]:
|
|
instance_info["project"] = active_instances[port]["project"]
|
|
|
|
return instance_info
|
|
|
|
@mcp.resource(uri="/instance/{port}/function/decompile/address/{address}")
|
|
def decompiled_function_by_address(port: int = None, address: str = None) -> str:
|
|
"""Get decompiled C code for a function by address
|
|
|
|
Args:
|
|
port: Specific Ghidra instance port
|
|
address: Function address in hex format
|
|
|
|
Returns:
|
|
str: The decompiled C code as a string, or error message
|
|
"""
|
|
if not address:
|
|
return "Error: Address parameter is required"
|
|
|
|
port = _get_instance_port(port)
|
|
|
|
params = {
|
|
"syntax_tree": "false",
|
|
"style": "normalize"
|
|
}
|
|
|
|
endpoint = f"functions/{address}/decompile"
|
|
|
|
response = safe_get(port, endpoint, params)
|
|
simplified = simplify_response(response)
|
|
|
|
# For a resource, we want to directly return just the decompiled code
|
|
if (not isinstance(simplified, dict) or
|
|
not simplified.get("success", False) or
|
|
"result" not in simplified):
|
|
error_message = "Error: Could not decompile function"
|
|
if isinstance(simplified, dict) and "error" in simplified:
|
|
if isinstance(simplified["error"], dict):
|
|
error_message = simplified["error"].get("message", error_message)
|
|
else:
|
|
error_message = str(simplified["error"])
|
|
return error_message
|
|
|
|
# Extract just the decompiled code text
|
|
result = simplified["result"]
|
|
|
|
# Different endpoints may return the code in different fields, try all of them
|
|
if isinstance(result, dict):
|
|
for key in ["decompiled_text", "ccode", "decompiled"]:
|
|
if key in result:
|
|
return result[key]
|
|
|
|
return "Error: Could not extract decompiled code from response"
|
|
|
|
@mcp.resource(uri="/instance/{port}/function/decompile/name/{name}")
|
|
def decompiled_function_by_name(port: int = None, name: str = None) -> str:
|
|
"""Get decompiled C code for a function by name
|
|
|
|
Args:
|
|
port: Specific Ghidra instance port
|
|
name: Function name
|
|
|
|
Returns:
|
|
str: The decompiled C code as a string, or error message
|
|
"""
|
|
if not name:
|
|
return "Error: Name parameter is required"
|
|
|
|
port = _get_instance_port(port)
|
|
|
|
params = {
|
|
"syntax_tree": "false",
|
|
"style": "normalize"
|
|
}
|
|
|
|
endpoint = f"functions/by-name/{quote(name)}/decompile"
|
|
|
|
response = safe_get(port, endpoint, params)
|
|
simplified = simplify_response(response)
|
|
|
|
# For a resource, we want to directly return just the decompiled code
|
|
if (not isinstance(simplified, dict) or
|
|
not simplified.get("success", False) or
|
|
"result" not in simplified):
|
|
error_message = "Error: Could not decompile function"
|
|
if isinstance(simplified, dict) and "error" in simplified:
|
|
if isinstance(simplified["error"], dict):
|
|
error_message = simplified["error"].get("message", error_message)
|
|
else:
|
|
error_message = str(simplified["error"])
|
|
return error_message
|
|
|
|
# Extract just the decompiled code text
|
|
result = simplified["result"]
|
|
|
|
# Different endpoints may return the code in different fields, try all of them
|
|
if isinstance(result, dict):
|
|
for key in ["decompiled_text", "ccode", "decompiled"]:
|
|
if key in result:
|
|
return result[key]
|
|
|
|
return "Error: Could not extract decompiled code from response"
|
|
|
|
@mcp.resource(uri="/instance/{port}/function/info/address/{address}")
|
|
def function_info_by_address(port: int = None, address: str = None) -> dict:
|
|
"""Get detailed information about a function by address
|
|
|
|
Args:
|
|
port: Specific Ghidra instance port
|
|
address: Function address in hex format
|
|
|
|
Returns:
|
|
dict: Complete function information including signature, parameters, etc.
|
|
"""
|
|
if not address:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "MISSING_PARAMETER",
|
|
"message": "Address parameter is required"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
port = _get_instance_port(port)
|
|
|
|
endpoint = f"functions/{address}"
|
|
|
|
response = safe_get(port, endpoint)
|
|
simplified = simplify_response(response)
|
|
|
|
if (not isinstance(simplified, dict) or
|
|
not simplified.get("success", False) or
|
|
"result" not in simplified):
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "FUNCTION_NOT_FOUND",
|
|
"message": "Could not get function information",
|
|
"details": simplified.get("error") if isinstance(simplified, dict) else None
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
# Return just the function data without API metadata
|
|
return simplified["result"]
|
|
|
|
@mcp.resource(uri="/instance/{port}/function/info/name/{name}")
|
|
def function_info_by_name(port: int = None, name: str = None) -> dict:
|
|
"""Get detailed information about a function by name
|
|
|
|
Args:
|
|
port: Specific Ghidra instance port
|
|
name: Function name
|
|
|
|
Returns:
|
|
dict: Complete function information including signature, parameters, etc.
|
|
"""
|
|
if not name:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "MISSING_PARAMETER",
|
|
"message": "Name parameter is required"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
port = _get_instance_port(port)
|
|
|
|
endpoint = f"functions/by-name/{quote(name)}"
|
|
|
|
response = safe_get(port, endpoint)
|
|
simplified = simplify_response(response)
|
|
|
|
if (not isinstance(simplified, dict) or
|
|
not simplified.get("success", False) or
|
|
"result" not in simplified):
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "FUNCTION_NOT_FOUND",
|
|
"message": "Could not get function information",
|
|
"details": simplified.get("error") if isinstance(simplified, dict) else None
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
# Return just the function data without API metadata
|
|
return simplified["result"]
|
|
|
|
@mcp.resource(uri="/instance/{port}/function/disassembly/address/{address}")
|
|
def disassembly_by_address(port: int = None, address: str = None) -> str:
|
|
"""Get disassembled instructions for a function by address
|
|
|
|
Args:
|
|
port: Specific Ghidra instance port
|
|
address: Function address in hex format
|
|
|
|
Returns:
|
|
str: Formatted disassembly listing as a string
|
|
"""
|
|
if not address:
|
|
return "Error: Address parameter is required"
|
|
|
|
port = _get_instance_port(port)
|
|
|
|
endpoint = f"functions/{address}/disassembly"
|
|
|
|
response = safe_get(port, endpoint)
|
|
simplified = simplify_response(response)
|
|
|
|
if (not isinstance(simplified, dict) or
|
|
not simplified.get("success", False) or
|
|
"result" not in simplified):
|
|
error_message = "Error: Could not get disassembly"
|
|
if isinstance(simplified, dict) and "error" in simplified:
|
|
if isinstance(simplified["error"], dict):
|
|
error_message = simplified["error"].get("message", error_message)
|
|
else:
|
|
error_message = str(simplified["error"])
|
|
return error_message
|
|
|
|
# For a resource, we want to directly return just the disassembly text
|
|
result = simplified["result"]
|
|
|
|
# Check if we have a disassembly_text field already
|
|
if isinstance(result, dict) and "disassembly_text" in result:
|
|
return result["disassembly_text"]
|
|
|
|
# Otherwise if we have raw instructions, format them ourselves
|
|
if isinstance(result, dict) and "instructions" in result and isinstance(result["instructions"], list):
|
|
disasm_text = ""
|
|
for instr in result["instructions"]:
|
|
if isinstance(instr, dict):
|
|
addr = instr.get("address", "")
|
|
mnemonic = instr.get("mnemonic", "")
|
|
operands = instr.get("operands", "")
|
|
bytes_str = instr.get("bytes", "")
|
|
|
|
# Format: address: bytes mnemonic operands
|
|
disasm_text += f"{addr}: {bytes_str.ljust(10)} {mnemonic} {operands}\n"
|
|
|
|
return disasm_text
|
|
|
|
# If we have a direct disassembly field, try that as well
|
|
if isinstance(result, dict) and "disassembly" in result:
|
|
return result["disassembly"]
|
|
|
|
return "Error: Could not extract disassembly from response"
|
|
|
|
@mcp.resource(uri="/instance/{port}/function/disassembly/name/{name}")
|
|
def disassembly_by_name(port: int = None, name: str = None) -> str:
|
|
"""Get disassembled instructions for a function by name
|
|
|
|
Args:
|
|
port: Specific Ghidra instance port
|
|
name: Function name
|
|
|
|
Returns:
|
|
str: Formatted disassembly listing as a string
|
|
"""
|
|
if not name:
|
|
return "Error: Name parameter is required"
|
|
|
|
port = _get_instance_port(port)
|
|
|
|
endpoint = f"functions/by-name/{quote(name)}/disassembly"
|
|
|
|
response = safe_get(port, endpoint)
|
|
simplified = simplify_response(response)
|
|
|
|
if (not isinstance(simplified, dict) or
|
|
not simplified.get("success", False) or
|
|
"result" not in simplified):
|
|
error_message = "Error: Could not get disassembly"
|
|
if isinstance(simplified, dict) and "error" in simplified:
|
|
if isinstance(simplified["error"], dict):
|
|
error_message = simplified["error"].get("message", error_message)
|
|
else:
|
|
error_message = str(simplified["error"])
|
|
return error_message
|
|
|
|
# For a resource, we want to directly return just the disassembly text
|
|
result = simplified["result"]
|
|
|
|
# Check if we have a disassembly_text field already
|
|
if isinstance(result, dict) and "disassembly_text" in result:
|
|
return result["disassembly_text"]
|
|
|
|
# Otherwise if we have raw instructions, format them ourselves
|
|
if isinstance(result, dict) and "instructions" in result and isinstance(result["instructions"], list):
|
|
disasm_text = ""
|
|
for instr in result["instructions"]:
|
|
if isinstance(instr, dict):
|
|
addr = instr.get("address", "")
|
|
mnemonic = instr.get("mnemonic", "")
|
|
operands = instr.get("operands", "")
|
|
bytes_str = instr.get("bytes", "")
|
|
|
|
# Format: address: bytes mnemonic operands
|
|
disasm_text += f"{addr}: {bytes_str.ljust(10)} {mnemonic} {operands}\n"
|
|
|
|
return disasm_text
|
|
|
|
# If we have a direct disassembly field, try that as well
|
|
if isinstance(result, dict) and "disassembly" in result:
|
|
return result["disassembly"]
|
|
|
|
return "Error: Could not extract disassembly from response"
|
|
|
|
|
|
# ================= Enumeration Resources =================
|
|
# Lightweight read-only resources for listing/enumerating Ghidra data
|
|
# More efficient than tool calls for simple data access
|
|
|
|
@mcp.resource(uri="/instances")
|
|
def resource_instances_list() -> dict:
|
|
"""List all active Ghidra instances
|
|
|
|
Returns a lightweight summary of available instances for quick enumeration.
|
|
Use the /instance/{port} resource for detailed program info.
|
|
|
|
Returns:
|
|
dict: List of instances with port, project, and file info
|
|
"""
|
|
# Auto-discover instances before listing
|
|
_discover_instances(QUICK_DISCOVERY_RANGE, host=None, timeout=0.5)
|
|
|
|
with instances_lock:
|
|
instances = [
|
|
{
|
|
"port": port,
|
|
"project": info.get("project", ""),
|
|
"file": info.get("file", ""),
|
|
"url": info.get("url", f"http://{ghidra_host}:{port}")
|
|
}
|
|
for port, info in active_instances.items()
|
|
]
|
|
|
|
return {
|
|
"instances": instances,
|
|
"count": len(instances),
|
|
"current_port": current_instance_port,
|
|
"_hint": "Use /instance/{port} for detailed program info"
|
|
}
|
|
|
|
|
|
@mcp.resource(uri="/instance/{port}/functions")
|
|
def resource_functions_list(port: int = None) -> dict:
|
|
"""List all functions in the program (lightweight enumeration)
|
|
|
|
Returns function names and addresses for quick reference.
|
|
This is a read-only resource - use functions_list tool for filtering/pagination.
|
|
|
|
Args:
|
|
port: Ghidra instance port
|
|
|
|
Returns:
|
|
dict: List of functions with name, address, and size
|
|
"""
|
|
port = _get_instance_port(port)
|
|
|
|
# Fetch functions from Ghidra (limited for resource efficiency)
|
|
params = {"limit": 1000} # Cap at 1000 for resource response
|
|
response = safe_get(port, "functions", params)
|
|
simplified = simplify_response(response)
|
|
|
|
if not simplified.get("success", True):
|
|
return simplified
|
|
|
|
functions = simplified.get("result", simplified.get("functions", []))
|
|
if isinstance(functions, dict):
|
|
functions = functions.get("functions", [])
|
|
|
|
# Extract just the essential fields
|
|
func_list = []
|
|
for f in functions[:1000]: # Hard cap
|
|
if isinstance(f, dict):
|
|
func_list.append({
|
|
"name": f.get("name", "unknown"),
|
|
"address": f.get("entryPoint", f.get("address", "")),
|
|
"size": f.get("size", 0)
|
|
})
|
|
|
|
return {
|
|
"functions": func_list,
|
|
"count": len(func_list),
|
|
"truncated": len(functions) > 1000,
|
|
"_hint": "Use functions_list tool for filtering and pagination of large lists"
|
|
}
|
|
|
|
|
|
@mcp.resource(uri="/instance/{port}/strings")
|
|
def resource_strings_list(port: int = None) -> dict:
|
|
"""List defined strings in the program (lightweight enumeration)
|
|
|
|
Returns string values and addresses for quick reference.
|
|
Use data_list_strings tool for filtering/pagination.
|
|
|
|
Args:
|
|
port: Ghidra instance port
|
|
|
|
Returns:
|
|
dict: List of strings with address and value
|
|
"""
|
|
port = _get_instance_port(port)
|
|
|
|
params = {"limit": 500} # Strings can be verbose, cap lower
|
|
response = safe_get(port, "strings", params)
|
|
simplified = simplify_response(response)
|
|
|
|
if not simplified.get("success", True):
|
|
return simplified
|
|
|
|
strings = simplified.get("result", simplified.get("strings", []))
|
|
if isinstance(strings, dict):
|
|
strings = strings.get("strings", [])
|
|
|
|
# Extract essential fields
|
|
string_list = []
|
|
for s in strings[:500]:
|
|
if isinstance(s, dict):
|
|
string_list.append({
|
|
"address": s.get("address", ""),
|
|
"value": s.get("value", s.get("string", ""))[:200], # Truncate long strings
|
|
"length": s.get("length", len(s.get("value", "")))
|
|
})
|
|
|
|
return {
|
|
"strings": string_list,
|
|
"count": len(string_list),
|
|
"truncated": len(strings) > 500,
|
|
"_hint": "Use data_list_strings tool for full strings and pagination"
|
|
}
|
|
|
|
|
|
@mcp.resource(uri="/instance/{port}/data")
|
|
def resource_data_list(port: int = None) -> dict:
|
|
"""List defined data items in the program (lightweight enumeration)
|
|
|
|
Returns data labels, addresses, and types for quick reference.
|
|
Use data_list tool for filtering/pagination.
|
|
|
|
Args:
|
|
port: Ghidra instance port
|
|
|
|
Returns:
|
|
dict: List of data items with address, name, and type
|
|
"""
|
|
port = _get_instance_port(port)
|
|
|
|
params = {"limit": 1000}
|
|
response = safe_get(port, "data", params)
|
|
simplified = simplify_response(response)
|
|
|
|
if not simplified.get("success", True):
|
|
return simplified
|
|
|
|
data_items = simplified.get("result", simplified.get("data", []))
|
|
if isinstance(data_items, dict):
|
|
data_items = data_items.get("data", [])
|
|
|
|
# Extract essential fields
|
|
data_list = []
|
|
for d in data_items[:1000]:
|
|
if isinstance(d, dict):
|
|
data_list.append({
|
|
"address": d.get("address", ""),
|
|
"name": d.get("name", d.get("label", "")),
|
|
"type": d.get("type", d.get("dataType", ""))
|
|
})
|
|
|
|
return {
|
|
"data": data_list,
|
|
"count": len(data_list),
|
|
"truncated": len(data_items) > 1000,
|
|
"_hint": "Use data_list tool for filtering and pagination"
|
|
}
|
|
|
|
|
|
@mcp.resource(uri="/instance/{port}/structs")
|
|
def resource_structs_list(port: int = None) -> dict:
|
|
"""List defined struct types in the program (lightweight enumeration)
|
|
|
|
Returns struct names, sizes, and categories for quick reference.
|
|
Use structs_list tool for filtering/pagination, structs_get for fields.
|
|
|
|
Args:
|
|
port: Ghidra instance port
|
|
|
|
Returns:
|
|
dict: List of structs with name, size, and category
|
|
"""
|
|
port = _get_instance_port(port)
|
|
|
|
params = {"limit": 500}
|
|
response = safe_get(port, "structs", params)
|
|
simplified = simplify_response(response)
|
|
|
|
if not simplified.get("success", True):
|
|
return simplified
|
|
|
|
structs = simplified.get("result", simplified.get("structs", []))
|
|
if isinstance(structs, dict):
|
|
structs = structs.get("structs", [])
|
|
|
|
# Extract essential fields
|
|
struct_list = []
|
|
for s in structs[:500]:
|
|
if isinstance(s, dict):
|
|
struct_list.append({
|
|
"name": s.get("name", ""),
|
|
"size": s.get("size", s.get("length", 0)),
|
|
"category": s.get("category", s.get("categoryPath", ""))
|
|
})
|
|
|
|
return {
|
|
"structs": struct_list,
|
|
"count": len(struct_list),
|
|
"truncated": len(structs) > 500,
|
|
"_hint": "Use structs_list tool for pagination, structs_get for field details"
|
|
}
|
|
|
|
|
|
@mcp.resource(uri="/instance/{port}/xrefs/to/{address}")
|
|
def resource_xrefs_to(port: int = None, address: str = None) -> dict:
|
|
"""List cross-references TO an address (lightweight enumeration)
|
|
|
|
Returns references pointing to the specified address.
|
|
Use xrefs_list tool for full filtering/pagination.
|
|
|
|
Args:
|
|
port: Ghidra instance port
|
|
address: Target address in hex format
|
|
|
|
Returns:
|
|
dict: List of references to this address
|
|
"""
|
|
if not address:
|
|
return {"error": "Address parameter required"}
|
|
|
|
port = _get_instance_port(port)
|
|
|
|
params = {"toAddress": address, "limit": 200}
|
|
response = safe_get(port, "xrefs", params)
|
|
simplified = simplify_response(response)
|
|
|
|
if not simplified.get("success", True):
|
|
return simplified
|
|
|
|
xrefs = simplified.get("result", simplified.get("xrefs", []))
|
|
if isinstance(xrefs, dict):
|
|
xrefs = xrefs.get("xrefs", [])
|
|
|
|
# Extract essential fields
|
|
xref_list = []
|
|
for x in xrefs[:200]:
|
|
if isinstance(x, dict):
|
|
xref_list.append({
|
|
"from": x.get("fromAddress", x.get("from", "")),
|
|
"type": x.get("refType", x.get("type", "")),
|
|
"context": x.get("context", "")[:100] if x.get("context") else ""
|
|
})
|
|
|
|
return {
|
|
"to_address": address,
|
|
"references": xref_list,
|
|
"count": len(xref_list),
|
|
"truncated": len(xrefs) > 200,
|
|
"_hint": "Use xrefs_list tool for full filtering and pagination"
|
|
}
|
|
|
|
|
|
@mcp.resource(uri="/instance/{port}/xrefs/from/{address}")
|
|
def resource_xrefs_from(port: int = None, address: str = None) -> dict:
|
|
"""List cross-references FROM an address (lightweight enumeration)
|
|
|
|
Returns references originating from the specified address.
|
|
Use xrefs_list tool for full filtering/pagination.
|
|
|
|
Args:
|
|
port: Ghidra instance port
|
|
address: Source address in hex format
|
|
|
|
Returns:
|
|
dict: List of references from this address
|
|
"""
|
|
if not address:
|
|
return {"error": "Address parameter required"}
|
|
|
|
port = _get_instance_port(port)
|
|
|
|
params = {"fromAddress": address, "limit": 200}
|
|
response = safe_get(port, "xrefs", params)
|
|
simplified = simplify_response(response)
|
|
|
|
if not simplified.get("success", True):
|
|
return simplified
|
|
|
|
xrefs = simplified.get("result", simplified.get("xrefs", []))
|
|
if isinstance(xrefs, dict):
|
|
xrefs = xrefs.get("xrefs", [])
|
|
|
|
# Extract essential fields
|
|
xref_list = []
|
|
for x in xrefs[:200]:
|
|
if isinstance(x, dict):
|
|
xref_list.append({
|
|
"to": x.get("toAddress", x.get("to", "")),
|
|
"type": x.get("refType", x.get("type", "")),
|
|
"context": x.get("context", "")[:100] if x.get("context") else ""
|
|
})
|
|
|
|
return {
|
|
"from_address": address,
|
|
"references": xref_list,
|
|
"count": len(xref_list),
|
|
"truncated": len(xrefs) > 200,
|
|
"_hint": "Use xrefs_list tool for full filtering and pagination"
|
|
}
|
|
|
|
|
|
@mcp.resource(uri="/instance/{port}/summary")
|
|
def resource_program_summary(port: int = None) -> dict:
|
|
"""Get a comprehensive summary of the loaded program
|
|
|
|
Combines instance info with counts of functions, strings, data, etc.
|
|
Useful for getting a quick overview before detailed analysis.
|
|
|
|
Args:
|
|
port: Ghidra instance port
|
|
|
|
Returns:
|
|
dict: Program summary with statistics
|
|
"""
|
|
port = _get_instance_port(port)
|
|
|
|
# Get basic program info
|
|
program_info = ghidra_instance(port=port)
|
|
if "error" in program_info:
|
|
return program_info
|
|
|
|
# Get counts (lightweight queries)
|
|
summary = {
|
|
"program": program_info,
|
|
"statistics": {}
|
|
}
|
|
|
|
# Function count
|
|
try:
|
|
fn_response = safe_get(port, "functions", {"limit": 1})
|
|
if isinstance(fn_response, dict):
|
|
total = fn_response.get("result", {}).get("total", 0)
|
|
if not total:
|
|
total = fn_response.get("total", 0)
|
|
summary["statistics"]["functions"] = total
|
|
except Exception:
|
|
summary["statistics"]["functions"] = "unknown"
|
|
|
|
# String count
|
|
try:
|
|
str_response = safe_get(port, "strings", {"limit": 1})
|
|
if isinstance(str_response, dict):
|
|
total = str_response.get("result", {}).get("total", 0)
|
|
if not total:
|
|
total = str_response.get("total", 0)
|
|
summary["statistics"]["strings"] = total
|
|
except Exception:
|
|
summary["statistics"]["strings"] = "unknown"
|
|
|
|
# Data count
|
|
try:
|
|
data_response = safe_get(port, "data", {"limit": 1})
|
|
if isinstance(data_response, dict):
|
|
total = data_response.get("result", {}).get("total", 0)
|
|
if not total:
|
|
total = data_response.get("total", 0)
|
|
summary["statistics"]["data_items"] = total
|
|
except Exception:
|
|
summary["statistics"]["data_items"] = "unknown"
|
|
|
|
summary["_hint"] = "Use /instance/{port}/functions, /strings, /data for listings"
|
|
|
|
return summary
|
|
|
|
|
|
# ================= MCP Prompts =================
|
|
# Prompts define reusable templates for LLM interactions
|
|
|
|
@mcp.prompt("analyze_function")
|
|
def analyze_function_prompt(name: str = None, address: str = None, port: int = None):
|
|
"""A prompt to guide the LLM through analyzing a function
|
|
|
|
Args:
|
|
name: Function name (mutually exclusive with address)
|
|
address: Function address in hex format (mutually exclusive with address)
|
|
port: Specific Ghidra instance port (optional)
|
|
"""
|
|
port = _get_instance_port(port)
|
|
|
|
# Get function name if only address is provided
|
|
if address and not name:
|
|
fn_info = function_info_by_address(address=address, port=port)
|
|
if isinstance(fn_info, dict) and "name" in fn_info:
|
|
name = fn_info["name"]
|
|
|
|
# Create the template that guides analysis
|
|
decompiled = ""
|
|
disasm = ""
|
|
fn_info = None
|
|
|
|
if address:
|
|
decompiled = decompiled_function_by_address(address=address, port=port)
|
|
disasm = disassembly_by_address(address=address, port=port)
|
|
fn_info = function_info_by_address(address=address, port=port)
|
|
elif name:
|
|
decompiled = decompiled_function_by_name(name=name, port=port)
|
|
disasm = disassembly_by_name(name=name, port=port)
|
|
fn_info = function_info_by_name(name=name, port=port)
|
|
|
|
return {
|
|
"prompt": f"""
|
|
Analyze the following function: {name or address}
|
|
|
|
Decompiled code:
|
|
```c
|
|
{decompiled}
|
|
```
|
|
|
|
Disassembly:
|
|
```
|
|
{disasm}
|
|
```
|
|
|
|
1. What is the purpose of this function?
|
|
2. What are the key parameters and their uses?
|
|
3. What are the return values and their meanings?
|
|
4. Are there any security concerns in this implementation?
|
|
5. Describe the algorithm or process being implemented.
|
|
""",
|
|
"context": {
|
|
"function_info": fn_info
|
|
}
|
|
}
|
|
|
|
@mcp.prompt("identify_vulnerabilities")
|
|
def identify_vulnerabilities_prompt(name: str = None, address: str = None, port: int = None):
|
|
"""A prompt to help identify potential vulnerabilities in a function
|
|
|
|
Args:
|
|
name: Function name (mutually exclusive with address)
|
|
address: Function address in hex format (mutually exclusive with address)
|
|
port: Specific Ghidra instance port (optional)
|
|
"""
|
|
port = _get_instance_port(port)
|
|
|
|
# Get function name if only address is provided
|
|
if address and not name:
|
|
fn_info = function_info_by_address(address=address, port=port)
|
|
if isinstance(fn_info, dict) and "name" in fn_info:
|
|
name = fn_info["name"]
|
|
|
|
# Create the template focused on security analysis
|
|
decompiled = ""
|
|
disasm = ""
|
|
fn_info = None
|
|
|
|
if address:
|
|
decompiled = decompiled_function_by_address(address=address, port=port)
|
|
disasm = disassembly_by_address(address=address, port=port)
|
|
fn_info = function_info_by_address(address=address, port=port)
|
|
elif name:
|
|
decompiled = decompiled_function_by_name(name=name, port=port)
|
|
disasm = disassembly_by_name(name=name, port=port)
|
|
fn_info = function_info_by_name(name=name, port=port)
|
|
|
|
return {
|
|
"prompt": f"""
|
|
Analyze the following function for security vulnerabilities: {name or address}
|
|
|
|
Decompiled code:
|
|
```c
|
|
{decompiled}
|
|
```
|
|
|
|
Look for these vulnerability types:
|
|
1. Buffer overflows or underflows
|
|
2. Integer overflow/underflow
|
|
3. Use-after-free or double-free bugs
|
|
4. Format string vulnerabilities
|
|
5. Missing bounds checks
|
|
6. Insecure memory operations
|
|
7. Race conditions or timing issues
|
|
8. Input validation problems
|
|
|
|
For each potential vulnerability:
|
|
- Describe the vulnerability and where it occurs
|
|
- Explain the security impact
|
|
- Suggest how it could be exploited
|
|
- Recommend a fix
|
|
""",
|
|
"context": {
|
|
"function_info": fn_info,
|
|
"disassembly": disasm
|
|
}
|
|
}
|
|
|
|
@mcp.prompt("reverse_engineer_binary")
|
|
def reverse_engineer_binary_prompt(port: int = None):
|
|
"""A comprehensive prompt to guide the process of reverse engineering an entire binary
|
|
|
|
Args:
|
|
port: Specific Ghidra instance port (optional)
|
|
"""
|
|
port = _get_instance_port(port)
|
|
|
|
# Get program info for context
|
|
program_info = ghidra_instance(port=port)
|
|
|
|
# Create a comprehensive reverse engineering guide
|
|
return {
|
|
"prompt": f"""
|
|
# Comprehensive Binary Reverse Engineering Plan
|
|
|
|
Begin reverse engineering the binary {program_info.get('program_name', 'unknown')} using a methodical approach.
|
|
|
|
## Phase 1: Initial Reconnaissance
|
|
1. Analyze entry points and the main function
|
|
2. Identify and catalog key functions and libraries
|
|
3. Map the overall program structure
|
|
4. Identify important data structures
|
|
|
|
## Phase 2: Functional Analysis
|
|
1. Start with main() or entry point functions and trace the control flow
|
|
2. Find and rename all unnamed functions (FUN_*) called from main
|
|
3. For each function:
|
|
- Decompile and analyze its purpose
|
|
- Rename with descriptive names following consistent patterns
|
|
- Add comments for complex logic
|
|
- Identify parameters and return values
|
|
4. Follow cross-references (xrefs) to understand context of function usage
|
|
5. Pay special attention to:
|
|
- File I/O operations
|
|
- Network communication
|
|
- Memory allocation/deallocation
|
|
- Authentication/encryption routines
|
|
- Data processing algorithms
|
|
|
|
## Phase 3: Data Flow Mapping
|
|
1. Identify key data structures and rename them meaningfully
|
|
2. Track global variables and their usage across functions
|
|
3. Map data transformations through the program
|
|
4. Identify sensitive data handling (keys, credentials, etc.)
|
|
|
|
## Phase 4: Deep Analysis
|
|
1. For complex functions, perform deeper analysis using:
|
|
- Data flow analysis
|
|
- Call graph analysis
|
|
- Security vulnerability scanning
|
|
2. Look for interesting patterns:
|
|
- Command processing routines
|
|
- State machines
|
|
- Protocol implementations
|
|
- Cryptographic operations
|
|
|
|
## Implementation Strategy
|
|
1. Start with functions called from main
|
|
2. Search for unnamed functions with pattern "FUN_*"
|
|
3. Decompile each function and analyze its purpose
|
|
4. Look at its call graph and cross-references to understand context
|
|
5. Rename the function based on its behavior
|
|
6. Document key insights
|
|
7. Continue iteratively until the entire program flow is mapped
|
|
|
|
## Function Prioritization
|
|
1. Start with entry points and initialization functions
|
|
2. Focus on functions with high centrality in the call graph
|
|
3. Pay special attention to functions with:
|
|
- Command processing logic
|
|
- Error handling
|
|
- Security checks
|
|
- Data transformation
|
|
|
|
Remember to use the available GhydraMCP tools:
|
|
- Use functions_list to find functions matching patterns
|
|
- Use xrefs_list to find cross-references
|
|
- Use functions_decompile for C-like representations
|
|
- Use functions_disassemble for lower-level analysis
|
|
- Use functions_rename to apply meaningful names
|
|
- Use data_* tools to work with program data
|
|
""",
|
|
"context": {
|
|
"program_info": program_info
|
|
}
|
|
}
|
|
|
|
# ================= MCP Tools =================
|
|
# Since we can't use tool groups, we'll use namespaces in the function names
|
|
|
|
# Instance management tools
|
|
@mcp.tool()
|
|
def instances_list() -> dict:
|
|
"""List all active Ghidra instances
|
|
|
|
This is the primary tool for working with instances. It automatically discovers
|
|
new instances on the default host before listing.
|
|
|
|
Use instances_discover(host) only if you need to scan a different host.
|
|
|
|
Returns:
|
|
dict: Contains 'instances' list with all available Ghidra instances
|
|
"""
|
|
# Auto-discover new instances before listing
|
|
_discover_instances(QUICK_DISCOVERY_RANGE, host=None, timeout=0.5)
|
|
|
|
with instances_lock:
|
|
return {
|
|
"instances": [
|
|
{
|
|
"port": port,
|
|
"url": info["url"],
|
|
"project": info.get("project", ""),
|
|
"file": info.get("file", "")
|
|
}
|
|
for port, info in active_instances.items()
|
|
]
|
|
}
|
|
|
|
@mcp.tool()
|
|
def instances_discover(host: str = None) -> dict:
|
|
"""Discover Ghidra instances on a specific host
|
|
|
|
Use this ONLY when you need to discover instances on a different host.
|
|
For normal usage, just use instances_list() which auto-discovers on the default host.
|
|
|
|
Args:
|
|
host: Host to scan for Ghidra instances (default: configured ghidra_host)
|
|
|
|
Returns:
|
|
dict: Contains 'instances' list with all available instances after discovery
|
|
"""
|
|
# Discover instances on the specified host
|
|
_discover_instances(QUICK_DISCOVERY_RANGE, host=host, timeout=0.5)
|
|
|
|
# Return all instances (same format as instances_list for consistency)
|
|
with instances_lock:
|
|
return {
|
|
"instances": [
|
|
{
|
|
"port": port,
|
|
"url": info["url"],
|
|
"project": info.get("project", ""),
|
|
"file": info.get("file", "")
|
|
}
|
|
for port, info in active_instances.items()
|
|
]
|
|
}
|
|
|
|
@mcp.tool()
|
|
def instances_register(port: int, url: str = None) -> str:
|
|
"""Register a new Ghidra instance
|
|
|
|
Args:
|
|
port: Port number of the Ghidra instance
|
|
url: Optional URL if different from default http://host:port
|
|
|
|
Returns:
|
|
str: Confirmation message or error
|
|
"""
|
|
return register_instance(port, url)
|
|
|
|
@mcp.tool()
|
|
def instances_unregister(port: int) -> str:
|
|
"""Unregister a Ghidra instance
|
|
|
|
Args:
|
|
port: Port number of the instance to unregister
|
|
|
|
Returns:
|
|
str: Confirmation message or error
|
|
"""
|
|
with instances_lock:
|
|
if port in active_instances:
|
|
del active_instances[port]
|
|
return f"Unregistered instance on port {port}"
|
|
return f"No instance found on port {port}"
|
|
|
|
@mcp.tool()
|
|
def instances_use(port: int) -> str:
|
|
"""Set the current working Ghidra instance
|
|
|
|
Args:
|
|
port: Port number of the instance to use
|
|
|
|
Returns:
|
|
str: Confirmation message or error
|
|
"""
|
|
global current_instance_port
|
|
|
|
# First validate that the instance exists and is active
|
|
if port not in active_instances:
|
|
# Try to register it if not found
|
|
register_instance(port)
|
|
if port not in active_instances:
|
|
return f"Error: No active Ghidra instance found on port {port}"
|
|
|
|
# Set as current instance
|
|
current_instance_port = port
|
|
|
|
# Return information about the selected instance
|
|
with instances_lock:
|
|
info = active_instances[port]
|
|
program = info.get("file", "unknown program")
|
|
project = info.get("project", "unknown project")
|
|
return f"Now using Ghidra instance on port {port} with {program} in project {project}"
|
|
|
|
@mcp.tool()
|
|
def instances_current() -> dict:
|
|
"""Get information about the current working Ghidra instance
|
|
|
|
Returns:
|
|
dict: Details about the current instance and program
|
|
"""
|
|
return ghidra_instance(port=current_instance_port)
|
|
|
|
|
|
# ================= Cursor Management Tools =================
|
|
# Tools for managing pagination cursors with session isolation
|
|
|
|
def _get_session_id(ctx: Context = None) -> str:
|
|
"""Get session ID from FastMCP context
|
|
|
|
Uses the session object's id() for reliable session tracking.
|
|
The session object persists across tool calls within the same MCP connection.
|
|
|
|
Security: This function does NOT accept manual session_id overrides
|
|
to prevent session spoofing attacks.
|
|
"""
|
|
if ctx:
|
|
# Try to get client_id first (explicitly provided by client)
|
|
if hasattr(ctx, 'client_id') and ctx.client_id:
|
|
return f"client-{ctx.client_id}"
|
|
|
|
# Use session object's memory id as unique session identifier
|
|
# This persists across tool calls within the same MCP connection
|
|
if hasattr(ctx, 'session') and ctx.session:
|
|
return f"session-{id(ctx.session)}"
|
|
|
|
# Fallback to request_id prefix for stdio transport
|
|
if hasattr(ctx, 'request_id') and ctx.request_id:
|
|
return f"req-{ctx.request_id[:8]}" if len(ctx.request_id) > 8 else f"req-{ctx.request_id}"
|
|
|
|
return "default"
|
|
|
|
|
|
@mcp.tool()
|
|
def cursor_next(cursor_id: str, ctx: Context = None) -> dict:
|
|
"""Get the next page of results for a pagination cursor
|
|
|
|
Args:
|
|
cursor_id: The cursor ID from a previous paginated response
|
|
ctx: FastMCP context (auto-injected)
|
|
|
|
Returns:
|
|
dict: Next page of results with updated pagination info
|
|
"""
|
|
if not cursor_id:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "MISSING_PARAMETER",
|
|
"message": "cursor_id parameter is required"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
sid = _get_session_id(ctx)
|
|
state = cursor_manager.advance_cursor(cursor_id, sid)
|
|
|
|
if not state:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "CURSOR_NOT_FOUND",
|
|
"message": f"Cursor '{cursor_id}' not found, expired, or belongs to another session"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
current_page = cursor_manager.get_page(state)
|
|
response_cursor = cursor_id if state.has_more else None
|
|
|
|
response = {
|
|
"success": True,
|
|
"result": current_page,
|
|
"pagination": {
|
|
"cursor_id": response_cursor,
|
|
"session_id": state.session_id,
|
|
"tool_name": state.tool_name,
|
|
"total_count": state.total_count,
|
|
"filtered_count": state.filtered_count,
|
|
"page_size": state.page_size,
|
|
"current_page": state.current_page,
|
|
"total_pages": state.total_pages,
|
|
"has_more": state.has_more,
|
|
"grep_pattern": state.grep_pattern,
|
|
"items_returned": len(current_page),
|
|
"ttl_remaining": state.ttl_remaining,
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
# Add prominent message for LLMs
|
|
if state.has_more:
|
|
remaining = state.filtered_count - (state.current_page * state.page_size)
|
|
response["_message"] = (
|
|
f"📄 Page {state.current_page}/{state.total_pages}: "
|
|
f"{len(current_page)} items. {remaining} more available. "
|
|
f"Continue with: cursor_next(cursor_id='{cursor_id}')"
|
|
)
|
|
else:
|
|
total_fetched = state.current_page * state.page_size
|
|
response["_message"] = (
|
|
f"✅ Final page {state.current_page}/{state.total_pages}: "
|
|
f"{len(current_page)} items. All {state.filtered_count} items retrieved."
|
|
)
|
|
|
|
return response
|
|
|
|
|
|
@mcp.tool()
|
|
def cursor_list(ctx: Context = None, all_sessions: bool = False) -> dict:
|
|
"""List active pagination cursors
|
|
|
|
Args:
|
|
ctx: FastMCP context (auto-injected)
|
|
all_sessions: If True, list cursors from all sessions (admin use)
|
|
|
|
Returns:
|
|
dict: List of active cursors with their metadata
|
|
"""
|
|
sid = None if all_sessions else _get_session_id(ctx)
|
|
cursors = cursor_manager.list_cursors(session_id=sid)
|
|
|
|
return {
|
|
"success": True,
|
|
"result": cursors,
|
|
"stats": cursor_manager.get_stats(),
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
|
|
@mcp.tool()
|
|
def cursor_delete(cursor_id: str, ctx: Context = None) -> dict:
|
|
"""Delete a pagination cursor to free resources
|
|
|
|
Args:
|
|
cursor_id: The cursor ID to delete
|
|
ctx: FastMCP context (auto-injected)
|
|
|
|
Returns:
|
|
dict: Operation result
|
|
"""
|
|
if not cursor_id:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "MISSING_PARAMETER",
|
|
"message": "cursor_id parameter is required"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
sid = _get_session_id(ctx)
|
|
deleted = cursor_manager.delete_cursor(cursor_id, sid)
|
|
|
|
if deleted:
|
|
return {
|
|
"success": True,
|
|
"result": {
|
|
"deleted": True,
|
|
"cursor_id": cursor_id,
|
|
"message": "Cursor deleted successfully"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
else:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "CURSOR_NOT_FOUND",
|
|
"message": f"Cursor '{cursor_id}' not found or belongs to another session"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
|
|
@mcp.tool()
|
|
def cursor_delete_all(ctx: Context = None) -> dict:
|
|
"""Delete all pagination cursors for the current session
|
|
|
|
Args:
|
|
ctx: FastMCP context (auto-injected)
|
|
|
|
Returns:
|
|
dict: Number of cursors deleted
|
|
"""
|
|
sid = _get_session_id(ctx)
|
|
count = cursor_manager.delete_session_cursors(sid)
|
|
|
|
return {
|
|
"success": True,
|
|
"result": {
|
|
"deleted_count": count,
|
|
"session_id": sid,
|
|
"message": f"Deleted {count} cursor(s) for session '{sid}'"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
|
|
# ================= End Cursor Management Tools =================
|
|
|
|
# Function tools
|
|
@mcp.tool()
|
|
def functions_list(
|
|
name_contains: str = None,
|
|
name_matches_regex: str = None,
|
|
port: int = None,
|
|
# Pagination parameters
|
|
page_size: int = DEFAULT_PAGE_SIZE,
|
|
grep: str = None,
|
|
grep_ignorecase: bool = True,
|
|
return_all: bool = False,
|
|
ctx: Context = None
|
|
) -> dict:
|
|
"""List functions with cursor-based pagination and grep filtering
|
|
|
|
Args:
|
|
name_contains: Substring name filter (case-insensitive, server-side)
|
|
name_matches_regex: Regex name filter (server-side)
|
|
port: Specific Ghidra instance port (optional)
|
|
page_size: Items per page (default: 50, max: 500)
|
|
grep: Regex pattern to filter results client-side (e.g., "main|init", "FUN_.*")
|
|
grep_ignorecase: Case-insensitive grep (default: True)
|
|
return_all: Bypass pagination and return all results (use with caution)
|
|
ctx: FastMCP context (auto-injected)
|
|
|
|
|
|
Returns:
|
|
dict: List of functions with pagination info. Use cursor_next(cursor_id) for more.
|
|
|
|
Examples:
|
|
# Get first page of all functions
|
|
functions_list()
|
|
|
|
# Filter to functions containing "main"
|
|
functions_list(name_contains="main")
|
|
|
|
# Client-side grep for FUN_* named functions
|
|
functions_list(grep="^FUN_")
|
|
|
|
# Get all functions (bypasses pagination - use carefully!)
|
|
functions_list(return_all=True)
|
|
"""
|
|
port_to_use = _get_instance_port(port)
|
|
sid = _get_session_id(ctx)
|
|
|
|
# Fetch a larger batch from Ghidra to enable client-side pagination
|
|
# We request more than page_size to allow grep filtering
|
|
fetch_limit = 5000 if return_all else max(page_size * 10, 500)
|
|
|
|
params = {
|
|
"offset": 0,
|
|
"limit": fetch_limit
|
|
}
|
|
if name_contains:
|
|
params["name_contains"] = name_contains
|
|
if name_matches_regex:
|
|
params["name_matches_regex"] = name_matches_regex
|
|
|
|
response = safe_get(port_to_use, "functions", params)
|
|
simplified = simplify_response(response)
|
|
|
|
# Handle error responses
|
|
if not isinstance(simplified, dict) or not simplified.get("success", False):
|
|
return simplified
|
|
|
|
# Extract the result list
|
|
result_data = simplified.get("result", [])
|
|
if not isinstance(result_data, list):
|
|
return simplified
|
|
|
|
# Build query params for cursor hashing
|
|
query_params = {
|
|
"tool": "functions_list",
|
|
"port": port_to_use,
|
|
"name_contains": name_contains,
|
|
"name_matches_regex": name_matches_regex,
|
|
"grep": grep
|
|
}
|
|
|
|
# Use the paginate_response helper
|
|
return paginate_response(
|
|
data=result_data,
|
|
query_params=query_params,
|
|
tool_name="functions_list",
|
|
session_id=sid,
|
|
page_size=page_size,
|
|
grep=grep,
|
|
grep_ignorecase=grep_ignorecase,
|
|
return_all=return_all
|
|
)
|
|
|
|
@mcp.tool()
|
|
def functions_get(name: str = None, address: str = None, port: int = None) -> dict:
|
|
"""Get detailed information about a function
|
|
|
|
Args:
|
|
name: Function name (mutually exclusive with address)
|
|
address: Function address in hex format (mutually exclusive with name)
|
|
port: Specific Ghidra instance port (optional)
|
|
|
|
Returns:
|
|
dict: Detailed function information
|
|
"""
|
|
if not name and not address:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "MISSING_PARAMETER",
|
|
"message": "Either name or address parameter is required"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
port = _get_instance_port(port)
|
|
|
|
if address:
|
|
endpoint = f"functions/{address}"
|
|
else:
|
|
endpoint = f"functions/by-name/{quote(name)}"
|
|
|
|
response = safe_get(port, endpoint)
|
|
return simplify_response(response)
|
|
|
|
@mcp.tool()
|
|
def functions_decompile(
|
|
name: str = None,
|
|
address: str = None,
|
|
syntax_tree: bool = False,
|
|
style: str = "normalize",
|
|
port: int = None,
|
|
# Pagination parameters (line-based)
|
|
page_size: int = 50,
|
|
grep: str = None,
|
|
grep_ignorecase: bool = True,
|
|
return_all: bool = False,
|
|
ctx: Context = None
|
|
) -> dict:
|
|
"""Get decompiled code for a function with cursor-based line pagination
|
|
|
|
Args:
|
|
name: Function name (mutually exclusive with address)
|
|
address: Function address in hex format (mutually exclusive with name)
|
|
syntax_tree: Include syntax tree (default: False)
|
|
style: Decompiler style (default: "normalize")
|
|
port: Specific Ghidra instance port (optional)
|
|
page_size: Lines per page (default: 50, max: 500)
|
|
grep: Regex pattern to filter lines (e.g., "if.*==", "malloc|free")
|
|
grep_ignorecase: Case-insensitive grep (default: True)
|
|
return_all: Return all lines without pagination (use with caution for large functions)
|
|
ctx: FastMCP context (auto-injected)
|
|
|
|
|
|
Returns:
|
|
dict: Decompiled code with pagination. Use cursor_next(cursor_id) for more lines.
|
|
|
|
Examples:
|
|
# Get first 50 lines (default)
|
|
functions_decompile(name="main")
|
|
|
|
# Search for specific patterns
|
|
functions_decompile(name="main", grep="if.*NULL")
|
|
|
|
# Get all lines (for small functions)
|
|
functions_decompile(name="small_func", return_all=True)
|
|
"""
|
|
if not name and not address:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "MISSING_PARAMETER",
|
|
"message": "Either name or address parameter is required"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
port_to_use = _get_instance_port(port)
|
|
|
|
params = {
|
|
"syntax_tree": str(syntax_tree).lower(),
|
|
"style": style
|
|
}
|
|
|
|
if address:
|
|
endpoint = f"functions/{address}/decompile"
|
|
func_id = address
|
|
else:
|
|
endpoint = f"functions/by-name/{quote(name)}/decompile"
|
|
func_id = name
|
|
|
|
response = safe_get(port_to_use, endpoint, params)
|
|
simplified = simplify_response(response)
|
|
|
|
if not simplified.get("success", False):
|
|
return simplified
|
|
|
|
# Extract the decompiled code and split into lines
|
|
result = simplified.get("result", {})
|
|
code = result.get("code", "") if isinstance(result, dict) else ""
|
|
|
|
if not code:
|
|
return simplified # Return as-is if no code
|
|
|
|
# Split code into lines, preserving line numbers
|
|
lines = code.split('\n')
|
|
# Create line objects with line numbers for better grep matching
|
|
line_objects = [{"line_num": i + 1, "code": line} for i, line in enumerate(lines)]
|
|
|
|
# Build query params for cursor hashing
|
|
query_params = {
|
|
"tool": "functions_decompile",
|
|
"port": port_to_use,
|
|
"name": name,
|
|
"address": address,
|
|
"style": style,
|
|
"grep": grep
|
|
}
|
|
|
|
sid = _get_session_id(ctx)
|
|
|
|
# Use pagination system
|
|
paginated = paginate_response(
|
|
data=line_objects,
|
|
query_params=query_params,
|
|
tool_name="functions_decompile",
|
|
session_id=sid,
|
|
page_size=min(page_size, MAX_PAGE_SIZE),
|
|
grep=grep,
|
|
grep_ignorecase=grep_ignorecase,
|
|
return_all=return_all
|
|
)
|
|
|
|
# Transform result back to code format with line numbers
|
|
if paginated.get("success"):
|
|
page_lines = paginated.get("result", [])
|
|
# Format as "line_num: code" for clarity
|
|
formatted_lines = [f"{item['line_num']:4d}: {item['code']}" for item in page_lines]
|
|
paginated["result"] = {
|
|
"function": func_id,
|
|
"code_lines": formatted_lines,
|
|
"raw_lines": [item['code'] for item in page_lines]
|
|
}
|
|
# Add function metadata if available
|
|
if isinstance(result, dict):
|
|
for key in ["name", "address", "signature", "return_type"]:
|
|
if key in result:
|
|
paginated["result"][key] = result[key]
|
|
|
|
return paginated
|
|
|
|
@mcp.tool()
|
|
def functions_disassemble(
|
|
name: str = None,
|
|
address: str = None,
|
|
port: int = None,
|
|
# Pagination parameters (instruction-based)
|
|
page_size: int = 50,
|
|
grep: str = None,
|
|
grep_ignorecase: bool = True,
|
|
return_all: bool = False,
|
|
ctx: Context = None
|
|
) -> dict:
|
|
"""Get disassembly for a function with cursor-based instruction pagination
|
|
|
|
Args:
|
|
name: Function name (mutually exclusive with address)
|
|
address: Function address in hex format (mutually exclusive with name)
|
|
port: Specific Ghidra instance port (optional)
|
|
page_size: Instructions per page (default: 50, max: 500)
|
|
grep: Regex pattern to filter instructions (e.g., "CALL", "JMP|JNZ", "MOV.*EAX")
|
|
grep_ignorecase: Case-insensitive grep (default: True)
|
|
return_all: Return all instructions without pagination
|
|
ctx: FastMCP context (auto-injected)
|
|
|
|
|
|
Returns:
|
|
dict: Disassembly with pagination. Use cursor_next(cursor_id) for more instructions.
|
|
|
|
Examples:
|
|
# Get first 50 instructions
|
|
functions_disassemble(name="main")
|
|
|
|
# Find all CALL instructions
|
|
functions_disassemble(name="main", grep="CALL")
|
|
|
|
# Find jumps and conditional jumps
|
|
functions_disassemble(name="main", grep="^J")
|
|
"""
|
|
if not name and not address:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "MISSING_PARAMETER",
|
|
"message": "Either name or address parameter is required"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
port_to_use = _get_instance_port(port)
|
|
|
|
if address:
|
|
endpoint = f"functions/{address}/disassembly"
|
|
func_id = address
|
|
else:
|
|
endpoint = f"functions/by-name/{quote(name)}/disassembly"
|
|
func_id = name
|
|
|
|
response = safe_get(port_to_use, endpoint)
|
|
simplified = simplify_response(response)
|
|
|
|
if not simplified.get("success", False):
|
|
return simplified
|
|
|
|
# Extract the disassembly - could be text or structured
|
|
result = simplified.get("result", {})
|
|
|
|
# Handle different response formats
|
|
if isinstance(result, dict):
|
|
disasm_text = result.get("disassembly", "") or result.get("text", "")
|
|
instructions = result.get("instructions", [])
|
|
elif isinstance(result, str):
|
|
disasm_text = result
|
|
instructions = []
|
|
else:
|
|
disasm_text = ""
|
|
instructions = []
|
|
|
|
# If we have structured instructions, use them; otherwise parse text
|
|
if instructions:
|
|
# Already have instruction objects
|
|
line_objects = instructions
|
|
elif disasm_text:
|
|
# Split text into lines
|
|
lines = disasm_text.strip().split('\n')
|
|
line_objects = [{"addr": f"line_{i+1}", "instruction": line} for i, line in enumerate(lines) if line.strip()]
|
|
else:
|
|
return simplified # Return as-is if no disassembly
|
|
|
|
# Build query params for cursor hashing
|
|
query_params = {
|
|
"tool": "functions_disassemble",
|
|
"port": port_to_use,
|
|
"name": name,
|
|
"address": address,
|
|
"grep": grep
|
|
}
|
|
|
|
sid = _get_session_id(ctx)
|
|
|
|
# Use pagination system
|
|
paginated = paginate_response(
|
|
data=line_objects,
|
|
query_params=query_params,
|
|
tool_name="functions_disassemble",
|
|
session_id=sid,
|
|
page_size=min(page_size, MAX_PAGE_SIZE),
|
|
grep=grep,
|
|
grep_ignorecase=grep_ignorecase,
|
|
return_all=return_all
|
|
)
|
|
|
|
# Add function context to result
|
|
if paginated.get("success"):
|
|
page_instructions = paginated.get("result", [])
|
|
paginated["result"] = {
|
|
"function": func_id,
|
|
"instructions": page_instructions
|
|
}
|
|
# Add function metadata if available
|
|
if isinstance(result, dict):
|
|
for key in ["name", "address", "entry_point", "size"]:
|
|
if key in result:
|
|
paginated["result"][key] = result[key]
|
|
|
|
return paginated
|
|
|
|
@mcp.tool()
|
|
def functions_create(address: str, port: int = None) -> dict:
|
|
"""Create a new function at the specified address
|
|
|
|
Args:
|
|
address: Memory address in hex format where function starts
|
|
port: Specific Ghidra instance port (optional)
|
|
|
|
Returns:
|
|
dict: Operation result with the created function information
|
|
"""
|
|
if not address:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "MISSING_PARAMETER",
|
|
"message": "Address parameter is required"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
port = _get_instance_port(port)
|
|
|
|
payload = {
|
|
"address": address
|
|
}
|
|
|
|
response = safe_post(port, "functions", payload)
|
|
return simplify_response(response)
|
|
|
|
@mcp.tool()
|
|
def functions_rename(old_name: str = None, address: str = None, new_name: str = "", port: int = None) -> dict:
|
|
"""Rename a function
|
|
|
|
Args:
|
|
old_name: Current function name (mutually exclusive with address)
|
|
address: Function address in hex format (mutually exclusive with name)
|
|
new_name: New function name
|
|
port: Specific Ghidra instance port (optional)
|
|
|
|
Returns:
|
|
dict: Operation result with the updated function information
|
|
"""
|
|
if not (old_name or address) or not new_name:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "MISSING_PARAMETER",
|
|
"message": "Either old_name or address, and new_name parameters are required"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
port = _get_instance_port(port)
|
|
|
|
payload = {
|
|
"name": new_name
|
|
}
|
|
|
|
if address:
|
|
endpoint = f"functions/{address}"
|
|
else:
|
|
endpoint = f"functions/by-name/{quote(old_name)}"
|
|
|
|
response = safe_patch(port, endpoint, payload)
|
|
return simplify_response(response)
|
|
|
|
@mcp.tool()
|
|
def functions_set_signature(name: str = None, address: str = None, signature: str = "", port: int = None) -> dict:
|
|
"""Set function signature/prototype
|
|
|
|
Args:
|
|
name: Function name (mutually exclusive with address)
|
|
address: Function address in hex format (mutually exclusive with name)
|
|
signature: New function signature (e.g., "int func(char *data, int size)")
|
|
port: Specific Ghidra instance port (optional)
|
|
|
|
Returns:
|
|
dict: Operation result with the updated function information
|
|
"""
|
|
if not (name or address) or not signature:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "MISSING_PARAMETER",
|
|
"message": "Either name or address, and signature parameters are required"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
port = _get_instance_port(port)
|
|
|
|
payload = {
|
|
"signature": signature
|
|
}
|
|
|
|
if address:
|
|
endpoint = f"functions/{address}"
|
|
else:
|
|
endpoint = f"functions/by-name/{quote(name)}"
|
|
|
|
response = safe_patch(port, endpoint, payload)
|
|
return simplify_response(response)
|
|
|
|
@mcp.tool()
|
|
def functions_get_variables(
|
|
name: str = None,
|
|
address: str = None,
|
|
port: int = None,
|
|
# Pagination parameters
|
|
page_size: int = DEFAULT_PAGE_SIZE,
|
|
grep: str = None,
|
|
grep_ignorecase: bool = True,
|
|
return_all: bool = False,
|
|
ctx: Context = None
|
|
) -> dict:
|
|
"""Get variables for a function with cursor-based pagination
|
|
|
|
Args:
|
|
name: Function name (mutually exclusive with address)
|
|
address: Function address in hex format (mutually exclusive with name)
|
|
port: Specific Ghidra instance port (optional)
|
|
page_size: Variables per page (default: 50, max: 500)
|
|
grep: Regex pattern to filter variables (e.g., "local_", "param", "ptr.*int")
|
|
grep_ignorecase: Case-insensitive grep (default: True)
|
|
return_all: Return all variables without pagination
|
|
ctx: FastMCP context (auto-injected)
|
|
|
|
|
|
Returns:
|
|
dict: Variables with pagination. Use cursor_next(cursor_id) for more.
|
|
|
|
Examples:
|
|
# Get all local variables
|
|
functions_get_variables(name="main", grep="local_")
|
|
|
|
# Find pointer variables
|
|
functions_get_variables(name="main", grep="ptr|\\*")
|
|
"""
|
|
if not name and not address:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "MISSING_PARAMETER",
|
|
"message": "Either name or address parameter is required"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
port_to_use = _get_instance_port(port)
|
|
|
|
if address:
|
|
endpoint = f"functions/{address}/variables"
|
|
func_id = address
|
|
else:
|
|
endpoint = f"functions/by-name/{quote(name)}/variables"
|
|
func_id = name
|
|
|
|
response = safe_get(port_to_use, endpoint)
|
|
simplified = simplify_response(response)
|
|
|
|
if not simplified.get("success", False):
|
|
return simplified
|
|
|
|
# Extract variables list
|
|
result = simplified.get("result", {})
|
|
variables = result.get("variables", []) if isinstance(result, dict) else []
|
|
|
|
if not variables:
|
|
return simplified # Return as-is if no variables
|
|
|
|
# Build query params for cursor hashing
|
|
query_params = {
|
|
"tool": "functions_get_variables",
|
|
"port": port_to_use,
|
|
"name": name,
|
|
"address": address,
|
|
"grep": grep
|
|
}
|
|
|
|
sid = _get_session_id(ctx)
|
|
|
|
# Use pagination system
|
|
paginated = paginate_response(
|
|
data=variables,
|
|
query_params=query_params,
|
|
tool_name="functions_get_variables",
|
|
session_id=sid,
|
|
page_size=min(page_size, MAX_PAGE_SIZE),
|
|
grep=grep,
|
|
grep_ignorecase=grep_ignorecase,
|
|
return_all=return_all
|
|
)
|
|
|
|
# Add function context
|
|
if paginated.get("success"):
|
|
paginated["result"] = {
|
|
"function": func_id,
|
|
"variables": paginated.get("result", [])
|
|
}
|
|
# Preserve other metadata
|
|
if isinstance(result, dict):
|
|
for key in ["name", "address", "parameter_count", "local_count"]:
|
|
if key in result:
|
|
paginated["result"][key] = result[key]
|
|
|
|
return paginated
|
|
|
|
# Memory tools
|
|
@mcp.tool()
|
|
def memory_read(address: str, length: int = 16, format: str = "hex", port: int = None) -> dict:
|
|
"""Read bytes from memory
|
|
|
|
Args:
|
|
address: Memory address in hex format
|
|
length: Number of bytes to read (default: 16)
|
|
format: Output format - "hex", "base64", or "string" (default: "hex")
|
|
port: Specific Ghidra instance port (optional)
|
|
|
|
Returns:
|
|
dict: {
|
|
"address": original address,
|
|
"length": bytes read,
|
|
"format": output format,
|
|
"hexBytes": the memory contents as hex string,
|
|
"rawBytes": the memory contents as base64 string,
|
|
"timestamp": response timestamp
|
|
}
|
|
"""
|
|
if not address:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "MISSING_PARAMETER",
|
|
"message": "Address parameter is required"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
port = _get_instance_port(port)
|
|
|
|
# Use query parameters instead of path parameters for more reliable handling
|
|
params = {
|
|
"address": address,
|
|
"length": length,
|
|
"format": format
|
|
}
|
|
|
|
response = safe_get(port, "memory", params)
|
|
simplified = simplify_response(response)
|
|
|
|
# Ensure the result is simple and directly usable
|
|
if "result" in simplified and isinstance(simplified["result"], dict):
|
|
result = simplified["result"]
|
|
|
|
# Pass through all representations of the bytes
|
|
memory_info = {
|
|
"success": True,
|
|
"address": result.get("address", address),
|
|
"length": result.get("bytesRead", length),
|
|
"format": format,
|
|
"timestamp": simplified.get("timestamp", int(time.time() * 1000))
|
|
}
|
|
|
|
# Include all the different byte representations
|
|
if "hexBytes" in result:
|
|
memory_info["hexBytes"] = result["hexBytes"]
|
|
if "rawBytes" in result:
|
|
memory_info["rawBytes"] = result["rawBytes"]
|
|
|
|
return memory_info
|
|
|
|
return simplified
|
|
|
|
@mcp.tool()
|
|
def memory_write(address: str, bytes_data: str, format: str = "hex", port: int = None) -> dict:
|
|
"""Write bytes to memory (use with caution)
|
|
|
|
Args:
|
|
address: Memory address in hex format
|
|
bytes_data: Data to write (format depends on 'format' parameter)
|
|
format: Input format - "hex", "base64", or "string" (default: "hex")
|
|
port: Specific Ghidra instance port (optional)
|
|
|
|
Returns:
|
|
dict: Operation result with success status
|
|
"""
|
|
if not address:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "MISSING_PARAMETER",
|
|
"message": "Address parameter is required"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
if not bytes_data:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "MISSING_PARAMETER",
|
|
"message": "Bytes parameter is required"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
port = _get_instance_port(port)
|
|
|
|
payload = {
|
|
"bytes": bytes_data,
|
|
"format": format
|
|
}
|
|
|
|
# Memory write is handled by ProgramEndpoints, not MemoryEndpoints
|
|
response = safe_patch(port, f"programs/current/memory/{address}", payload)
|
|
return simplify_response(response)
|
|
|
|
# Xrefs tools
|
|
@mcp.tool()
|
|
def xrefs_list(
|
|
to_addr: str = None,
|
|
from_addr: str = None,
|
|
type: str = None,
|
|
port: int = None,
|
|
# Pagination parameters
|
|
page_size: int = DEFAULT_PAGE_SIZE,
|
|
grep: str = None,
|
|
grep_ignorecase: bool = True,
|
|
return_all: bool = False,
|
|
ctx: Context = None
|
|
) -> dict:
|
|
"""List cross-references with filtering and cursor-based pagination
|
|
|
|
Args:
|
|
to_addr: Filter references to this address (hexadecimal)
|
|
from_addr: Filter references from this address (hexadecimal)
|
|
type: Filter by reference type (e.g. "CALL", "READ", "WRITE")
|
|
port: Specific Ghidra instance port (optional)
|
|
page_size: Items per page (default: 50, max: 500)
|
|
grep: Regex pattern to filter results
|
|
grep_ignorecase: Case-insensitive grep (default: True)
|
|
return_all: Return all results without pagination (use with caution)
|
|
ctx: FastMCP context (auto-injected)
|
|
|
|
|
|
Returns:
|
|
dict: Cross-references with pagination metadata and cursor for more results
|
|
"""
|
|
# At least one of the address parameters must be provided
|
|
if not to_addr and not from_addr:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "MISSING_PARAMETER",
|
|
"message": "Either to_addr or from_addr parameter is required"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
port_to_use = _get_instance_port(port)
|
|
|
|
# Fetch large batch for client-side pagination
|
|
params = {
|
|
"offset": 0,
|
|
"limit": 10000 # Fetch up to 10K for cursor pagination
|
|
}
|
|
if to_addr:
|
|
params["to_addr"] = to_addr
|
|
if from_addr:
|
|
params["from_addr"] = from_addr
|
|
if type:
|
|
params["type"] = type
|
|
|
|
response = safe_get(port_to_use, "xrefs", params)
|
|
simplified = simplify_response(response)
|
|
|
|
if not simplified.get("success", False):
|
|
return simplified
|
|
|
|
all_xrefs = simplified.get("result", [])
|
|
|
|
# Build query params for cursor hashing
|
|
query_params = {
|
|
"tool": "xrefs_list",
|
|
"port": port_to_use,
|
|
"to_addr": to_addr,
|
|
"from_addr": from_addr,
|
|
"type": type,
|
|
"grep": grep
|
|
}
|
|
|
|
sid = _get_session_id(ctx)
|
|
|
|
return paginate_response(
|
|
data=all_xrefs,
|
|
query_params=query_params,
|
|
tool_name="xrefs_list",
|
|
session_id=sid,
|
|
page_size=page_size,
|
|
grep=grep,
|
|
grep_ignorecase=grep_ignorecase,
|
|
return_all=return_all
|
|
)
|
|
|
|
# Data tools
|
|
@mcp.tool()
|
|
def data_list(
|
|
addr: str = None,
|
|
name: str = None,
|
|
name_contains: str = None,
|
|
type: str = None,
|
|
port: int = None,
|
|
# Pagination parameters
|
|
page_size: int = DEFAULT_PAGE_SIZE,
|
|
grep: str = None,
|
|
grep_ignorecase: bool = True,
|
|
return_all: bool = False,
|
|
ctx: Context = None
|
|
) -> dict:
|
|
"""List defined data items with filtering and cursor-based pagination
|
|
|
|
Args:
|
|
addr: Filter by address (hexadecimal)
|
|
name: Exact name match filter (case-sensitive)
|
|
name_contains: Substring name filter (case-insensitive)
|
|
type: Filter by data type (e.g. "string", "dword")
|
|
port: Specific Ghidra instance port (optional)
|
|
page_size: Items per page (default: 50, max: 500)
|
|
grep: Regex pattern to filter results
|
|
grep_ignorecase: Case-insensitive grep (default: True)
|
|
return_all: Return all results without pagination (use with caution)
|
|
ctx: FastMCP context (auto-injected)
|
|
|
|
|
|
Returns:
|
|
dict: Data items with pagination metadata and cursor for more results
|
|
"""
|
|
port_to_use = _get_instance_port(port)
|
|
|
|
# Fetch large batch for client-side pagination
|
|
params = {
|
|
"offset": 0,
|
|
"limit": 10000 # Fetch up to 10K for cursor pagination
|
|
}
|
|
if addr:
|
|
params["addr"] = addr
|
|
if name:
|
|
params["name"] = name
|
|
if name_contains:
|
|
params["name_contains"] = name_contains
|
|
if type:
|
|
params["type"] = type
|
|
|
|
response = safe_get(port_to_use, "data", params)
|
|
simplified = simplify_response(response)
|
|
|
|
if not simplified.get("success", False):
|
|
return simplified
|
|
|
|
all_data = simplified.get("result", [])
|
|
|
|
# Build query params for cursor hashing
|
|
query_params = {
|
|
"tool": "data_list",
|
|
"port": port_to_use,
|
|
"addr": addr,
|
|
"name": name,
|
|
"name_contains": name_contains,
|
|
"type": type,
|
|
"grep": grep
|
|
}
|
|
|
|
sid = _get_session_id(ctx)
|
|
|
|
return paginate_response(
|
|
data=all_data,
|
|
query_params=query_params,
|
|
tool_name="data_list",
|
|
session_id=sid,
|
|
page_size=page_size,
|
|
grep=grep,
|
|
grep_ignorecase=grep_ignorecase,
|
|
return_all=return_all
|
|
)
|
|
|
|
@mcp.tool()
|
|
def data_create(address: str, data_type: str, size: int = None, port: int = None) -> dict:
|
|
"""Define a new data item at the specified address
|
|
|
|
Args:
|
|
address: Memory address in hex format
|
|
data_type: Data type (e.g. "string", "dword", "byte")
|
|
size: Optional size in bytes for the data item
|
|
port: Specific Ghidra instance port (optional)
|
|
|
|
Returns:
|
|
dict: Operation result with the created data information
|
|
"""
|
|
if not address or not data_type:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "MISSING_PARAMETER",
|
|
"message": "Address and data_type parameters are required"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
port = _get_instance_port(port)
|
|
|
|
payload = {
|
|
"address": address,
|
|
"type": data_type
|
|
}
|
|
|
|
if size is not None:
|
|
payload["size"] = size
|
|
|
|
response = safe_post(port, "data", payload)
|
|
return simplify_response(response)
|
|
|
|
@mcp.tool()
|
|
def data_list_strings(
|
|
filter: str = None,
|
|
port: int = None,
|
|
# Pagination parameters
|
|
page_size: int = DEFAULT_PAGE_SIZE,
|
|
grep: str = None,
|
|
grep_ignorecase: bool = True,
|
|
return_all: bool = False,
|
|
ctx: Context = None
|
|
) -> dict:
|
|
"""List all defined strings in the binary with cursor-based pagination and grep filtering
|
|
|
|
Args:
|
|
filter: Server-side string content filter
|
|
port: Specific Ghidra instance port (optional)
|
|
page_size: Items per page (default: 50, max: 500)
|
|
grep: Regex pattern to filter results client-side (e.g., "password|key", "http://")
|
|
grep_ignorecase: Case-insensitive grep (default: True)
|
|
return_all: Bypass pagination and return all strings (use with caution)
|
|
ctx: FastMCP context (auto-injected)
|
|
|
|
|
|
Returns:
|
|
dict: List of string data with pagination info. Use cursor_next(cursor_id) for more.
|
|
|
|
Examples:
|
|
# Get first page of strings
|
|
data_list_strings()
|
|
|
|
# Filter to strings containing "error"
|
|
data_list_strings(filter="error")
|
|
|
|
# Client-side grep for URLs
|
|
data_list_strings(grep="https?://")
|
|
|
|
# Get all strings (bypasses pagination)
|
|
data_list_strings(return_all=True)
|
|
"""
|
|
port_to_use = _get_instance_port(port)
|
|
sid = _get_session_id(ctx)
|
|
|
|
# Fetch larger batch for client-side pagination
|
|
fetch_limit = 10000 if return_all else max(page_size * 10, 2000)
|
|
|
|
params = {
|
|
"offset": 0,
|
|
"limit": fetch_limit
|
|
}
|
|
|
|
if filter:
|
|
params["filter"] = filter
|
|
|
|
response = safe_get(port_to_use, "strings", params)
|
|
simplified = simplify_response(response)
|
|
|
|
# Handle error responses
|
|
if not isinstance(simplified, dict) or not simplified.get("success", False):
|
|
return simplified
|
|
|
|
# Extract the result list
|
|
result_data = simplified.get("result", [])
|
|
if not isinstance(result_data, list):
|
|
return simplified
|
|
|
|
# Build query params for cursor hashing
|
|
query_params = {
|
|
"tool": "data_list_strings",
|
|
"port": port_to_use,
|
|
"filter": filter,
|
|
"grep": grep
|
|
}
|
|
|
|
# Use the paginate_response helper
|
|
return paginate_response(
|
|
data=result_data,
|
|
query_params=query_params,
|
|
tool_name="data_list_strings",
|
|
session_id=sid,
|
|
page_size=page_size,
|
|
grep=grep,
|
|
grep_ignorecase=grep_ignorecase,
|
|
return_all=return_all
|
|
)
|
|
|
|
@mcp.tool()
|
|
def data_rename(address: str, name: str, port: int = None) -> dict:
|
|
"""Rename a data item
|
|
|
|
Args:
|
|
address: Memory address in hex format
|
|
name: New name for the data item
|
|
port: Specific Ghidra instance port (optional)
|
|
|
|
Returns:
|
|
dict: Operation result with the updated data information
|
|
"""
|
|
if not address or not name:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "MISSING_PARAMETER",
|
|
"message": "Address and name parameters are required"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
port = _get_instance_port(port)
|
|
|
|
payload = {
|
|
"address": address,
|
|
"newName": name
|
|
}
|
|
|
|
response = safe_post(port, "data", payload)
|
|
return simplify_response(response)
|
|
|
|
@mcp.tool()
|
|
def data_delete(address: str, port: int = None) -> dict:
|
|
"""Delete data at the specified address
|
|
|
|
Args:
|
|
address: Memory address in hex format
|
|
port: Specific Ghidra instance port (optional)
|
|
|
|
Returns:
|
|
dict: Operation result
|
|
"""
|
|
if not address:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "MISSING_PARAMETER",
|
|
"message": "Address parameter is required"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
port = _get_instance_port(port)
|
|
|
|
payload = {
|
|
"address": address,
|
|
"action": "delete"
|
|
}
|
|
|
|
response = safe_post(port, "data/delete", payload)
|
|
return simplify_response(response)
|
|
|
|
@mcp.tool()
|
|
def data_set_type(address: str, data_type: str, port: int = None) -> dict:
|
|
"""Set the data type of a data item
|
|
|
|
Args:
|
|
address: Memory address in hex format
|
|
data_type: Data type name (e.g. "uint32_t", "char[10]")
|
|
port: Specific Ghidra instance port (optional)
|
|
|
|
Returns:
|
|
dict: Operation result with the updated data information
|
|
"""
|
|
if not address or not data_type:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "MISSING_PARAMETER",
|
|
"message": "Address and data_type parameters are required"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
port = _get_instance_port(port)
|
|
|
|
payload = {
|
|
"address": address,
|
|
"type": data_type
|
|
}
|
|
|
|
response = safe_post(port, "data/type", payload)
|
|
return simplify_response(response)
|
|
|
|
# Struct tools
|
|
@mcp.tool()
|
|
def structs_list(
|
|
category: str = None,
|
|
port: int = None,
|
|
# Pagination parameters
|
|
page_size: int = DEFAULT_PAGE_SIZE,
|
|
grep: str = None,
|
|
grep_ignorecase: bool = True,
|
|
return_all: bool = False,
|
|
ctx: Context = None
|
|
) -> dict:
|
|
"""List all struct data types in the program with cursor-based pagination
|
|
|
|
Args:
|
|
category: Filter by category path (e.g. "/winapi")
|
|
port: Specific Ghidra instance port (optional)
|
|
page_size: Items per page (default: 50, max: 500)
|
|
grep: Regex pattern to filter results (searches struct names)
|
|
grep_ignorecase: Case-insensitive grep (default: True)
|
|
return_all: Return all results without pagination (use with caution)
|
|
ctx: FastMCP context (auto-injected)
|
|
|
|
|
|
Returns:
|
|
dict: Structs with pagination metadata and cursor for more results
|
|
"""
|
|
port_to_use = _get_instance_port(port)
|
|
|
|
# Fetch large batch for client-side pagination
|
|
params = {
|
|
"offset": 0,
|
|
"limit": 10000 # Fetch up to 10K for cursor pagination
|
|
}
|
|
if category:
|
|
params["category"] = category
|
|
|
|
response = safe_get(port_to_use, "structs", params)
|
|
simplified = simplify_response(response)
|
|
|
|
if not simplified.get("success", False):
|
|
return simplified
|
|
|
|
all_structs = simplified.get("result", [])
|
|
|
|
# Build query params for cursor hashing
|
|
query_params = {
|
|
"tool": "structs_list",
|
|
"port": port_to_use,
|
|
"category": category,
|
|
"grep": grep
|
|
}
|
|
|
|
sid = _get_session_id(ctx)
|
|
|
|
return paginate_response(
|
|
data=all_structs,
|
|
query_params=query_params,
|
|
tool_name="structs_list",
|
|
session_id=sid,
|
|
page_size=page_size,
|
|
grep=grep,
|
|
grep_ignorecase=grep_ignorecase,
|
|
return_all=return_all
|
|
)
|
|
|
|
@mcp.tool()
|
|
def structs_get(
|
|
name: str,
|
|
port: int = None,
|
|
# Pagination parameters (field-based)
|
|
page_size: int = DEFAULT_PAGE_SIZE,
|
|
grep: str = None,
|
|
grep_ignorecase: bool = True,
|
|
return_all: bool = False,
|
|
ctx: Context = None
|
|
) -> dict:
|
|
"""Get detailed information about a specific struct including all fields
|
|
|
|
Supports pagination for structs with many fields (e.g., large C++ classes).
|
|
|
|
Args:
|
|
name: Struct name
|
|
port: Specific Ghidra instance port (optional)
|
|
page_size: Number of fields per page (default: 50, max: 500)
|
|
grep: Regex pattern to filter fields (matches field name, type, or comment)
|
|
grep_ignorecase: Case-insensitive grep matching (default: True)
|
|
return_all: Return all fields without pagination (WARNING: large structs may have 100+ fields)
|
|
ctx: FastMCP context (auto-injected)
|
|
|
|
|
|
Returns:
|
|
dict: Struct details with paginated fields list
|
|
"""
|
|
if not name:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "MISSING_PARAMETER",
|
|
"message": "Struct name parameter is required"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
port = _get_instance_port(port)
|
|
sid = _get_session_id(ctx)
|
|
|
|
params = {"name": name}
|
|
response = safe_get(port, "structs", params)
|
|
simplified = simplify_response(response)
|
|
|
|
# Extract struct info and fields for pagination
|
|
if not simplified.get("success", True):
|
|
return simplified
|
|
|
|
result = simplified.get("result", simplified)
|
|
|
|
# Get struct metadata (preserve everything except fields for pagination)
|
|
struct_info = {}
|
|
fields = []
|
|
|
|
if isinstance(result, dict):
|
|
for key, value in result.items():
|
|
if key == "fields" and isinstance(value, list):
|
|
fields = value
|
|
else:
|
|
struct_info[key] = value
|
|
|
|
# If no fields or very few, return as-is
|
|
if len(fields) <= 10 and not grep:
|
|
return simplified
|
|
|
|
# Build query params for cursor hashing
|
|
query_params = {
|
|
"tool": "structs_get",
|
|
"port": port,
|
|
"name": name
|
|
}
|
|
|
|
# Paginate fields
|
|
paginated = paginate_response(
|
|
data=fields,
|
|
query_params=query_params,
|
|
tool_name="structs_get",
|
|
session_id=sid,
|
|
page_size=page_size,
|
|
grep=grep,
|
|
grep_ignorecase=grep_ignorecase,
|
|
return_all=return_all
|
|
)
|
|
|
|
# Merge struct metadata with paginated fields
|
|
if paginated.get("success"):
|
|
paginated["struct_name"] = struct_info.get("name", name)
|
|
paginated["struct_size"] = struct_info.get("size", struct_info.get("length"))
|
|
paginated["struct_category"] = struct_info.get("category", struct_info.get("categoryPath"))
|
|
paginated["struct_description"] = struct_info.get("description")
|
|
# The paginated "result" contains the fields
|
|
paginated["fields"] = paginated.pop("result", [])
|
|
|
|
# Update message to be struct-specific
|
|
if "_message" in paginated:
|
|
paginated["_message"] = paginated["_message"].replace("items", "fields")
|
|
|
|
return paginated
|
|
|
|
@mcp.tool()
|
|
def structs_create(name: str, category: str = None, description: str = None, port: int = None) -> dict:
|
|
"""Create a new struct data type
|
|
|
|
Args:
|
|
name: Name for the new struct
|
|
category: Category path for the struct (e.g. "/custom")
|
|
description: Optional description for the struct
|
|
port: Specific Ghidra instance port (optional)
|
|
|
|
Returns:
|
|
dict: Created struct information
|
|
"""
|
|
if not name:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "MISSING_PARAMETER",
|
|
"message": "Struct name parameter is required"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
port = _get_instance_port(port)
|
|
|
|
payload = {"name": name}
|
|
if category:
|
|
payload["category"] = category
|
|
if description:
|
|
payload["description"] = description
|
|
|
|
response = safe_post(port, "structs/create", payload)
|
|
return simplify_response(response)
|
|
|
|
@mcp.tool()
|
|
def structs_add_field(struct_name: str, field_name: str, field_type: str,
|
|
offset: int = None, comment: str = None, port: int = None) -> dict:
|
|
"""Add a field to an existing struct
|
|
|
|
Args:
|
|
struct_name: Name of the struct to modify
|
|
field_name: Name for the new field
|
|
field_type: Data type for the field (e.g. "int", "char", "pointer")
|
|
offset: Specific offset to insert field (optional, appends to end if not specified)
|
|
comment: Optional comment for the field
|
|
port: Specific Ghidra instance port (optional)
|
|
|
|
Returns:
|
|
dict: Operation result with updated struct size and field information
|
|
"""
|
|
if not struct_name or not field_name or not field_type:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "MISSING_PARAMETER",
|
|
"message": "struct_name, field_name, and field_type parameters are required"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
port = _get_instance_port(port)
|
|
|
|
payload = {
|
|
"struct": struct_name,
|
|
"fieldName": field_name,
|
|
"fieldType": field_type
|
|
}
|
|
if offset is not None:
|
|
payload["offset"] = offset
|
|
if comment:
|
|
payload["comment"] = comment
|
|
|
|
response = safe_post(port, "structs/addfield", payload)
|
|
return simplify_response(response)
|
|
|
|
@mcp.tool()
|
|
def structs_update_field(struct_name: str, field_name: str = None, field_offset: int = None,
|
|
new_name: str = None, new_type: str = None, new_comment: str = None,
|
|
port: int = None) -> dict:
|
|
"""Update an existing field in a struct (change name, type, or comment)
|
|
|
|
Args:
|
|
struct_name: Name of the struct to modify
|
|
field_name: Name of the field to update (use this OR field_offset)
|
|
field_offset: Offset of the field to update (use this OR field_name)
|
|
new_name: New name for the field (optional)
|
|
new_type: New data type for the field (optional, e.g. "int", "pointer")
|
|
new_comment: New comment for the field (optional)
|
|
port: Specific Ghidra instance port (optional)
|
|
|
|
Returns:
|
|
dict: Operation result with old and new field values
|
|
"""
|
|
if not struct_name:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "MISSING_PARAMETER",
|
|
"message": "struct_name parameter is required"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
if not field_name and field_offset is None:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "MISSING_PARAMETER",
|
|
"message": "Either field_name or field_offset must be provided"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
if not new_name and not new_type and new_comment is None:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "MISSING_PARAMETER",
|
|
"message": "At least one of new_name, new_type, or new_comment must be provided"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
port = _get_instance_port(port)
|
|
|
|
payload = {"struct": struct_name}
|
|
if field_name:
|
|
payload["fieldName"] = field_name
|
|
if field_offset is not None:
|
|
payload["fieldOffset"] = field_offset
|
|
if new_name:
|
|
payload["newName"] = new_name
|
|
if new_type:
|
|
payload["newType"] = new_type
|
|
if new_comment is not None:
|
|
payload["newComment"] = new_comment
|
|
|
|
response = safe_post(port, "structs/updatefield", payload)
|
|
return simplify_response(response)
|
|
|
|
@mcp.tool()
|
|
def structs_delete(name: str, port: int = None) -> dict:
|
|
"""Delete a struct data type
|
|
|
|
Args:
|
|
name: Name of the struct to delete
|
|
port: Specific Ghidra instance port (optional)
|
|
|
|
Returns:
|
|
dict: Operation result confirming deletion
|
|
"""
|
|
if not name:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "MISSING_PARAMETER",
|
|
"message": "Struct name parameter is required"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
port = _get_instance_port(port)
|
|
|
|
payload = {"name": name}
|
|
response = safe_post(port, "structs/delete", payload)
|
|
return simplify_response(response)
|
|
|
|
# Analysis tools
|
|
@mcp.tool()
|
|
def analysis_run(port: int = None, analysis_options: dict = None) -> dict:
|
|
"""Run analysis on the current program
|
|
|
|
Args:
|
|
analysis_options: Dictionary of analysis options to enable/disable
|
|
(e.g. {"functionRecovery": True, "dataRefs": False})
|
|
port: Specific Ghidra instance port (optional)
|
|
|
|
Returns:
|
|
dict: Analysis operation result with status
|
|
"""
|
|
port = _get_instance_port(port)
|
|
response = safe_post(port, "analysis", analysis_options or {})
|
|
return simplify_response(response)
|
|
|
|
@mcp.tool()
|
|
def analysis_get_callgraph(
|
|
name: str = None,
|
|
address: str = None,
|
|
max_depth: int = 3,
|
|
port: int = None,
|
|
# Pagination parameters
|
|
page_size: int = DEFAULT_PAGE_SIZE,
|
|
grep: str = None,
|
|
grep_ignorecase: bool = True,
|
|
return_all: bool = False,
|
|
ctx: Context = None
|
|
) -> dict:
|
|
"""Get function call graph with cursor-based pagination on edges
|
|
|
|
Args:
|
|
name: Starting function name (mutually exclusive with address)
|
|
address: Starting function address (mutually exclusive with name)
|
|
max_depth: Maximum call depth to analyze (default: 3)
|
|
port: Specific Ghidra instance port (optional)
|
|
page_size: Edges per page (default: 50, max: 500)
|
|
grep: Regex pattern to filter edges (e.g., "malloc|free", "FUN_00")
|
|
grep_ignorecase: Case-insensitive grep (default: True)
|
|
return_all: Return all edges without pagination
|
|
ctx: FastMCP context (auto-injected)
|
|
|
|
|
|
Returns:
|
|
dict: Call graph with paginated edges. Use cursor_next(cursor_id) for more.
|
|
|
|
Examples:
|
|
# Get callgraph, filter for memory functions
|
|
analysis_get_callgraph(name="main", grep="alloc|free|memcpy")
|
|
|
|
# Deep analysis with pagination
|
|
analysis_get_callgraph(name="main", max_depth=10, page_size=100)
|
|
"""
|
|
port_to_use = _get_instance_port(port)
|
|
|
|
params = {"max_depth": max_depth}
|
|
|
|
# Explicitly pass either name or address parameter based on what was provided
|
|
if address:
|
|
params["address"] = address
|
|
func_id = address
|
|
elif name:
|
|
params["name"] = name
|
|
func_id = name
|
|
else:
|
|
func_id = "entry_point"
|
|
# If neither is provided, the Java endpoint will use the entry point
|
|
|
|
response = safe_get(port_to_use, "analysis/callgraph", params)
|
|
simplified = simplify_response(response)
|
|
|
|
if not simplified.get("success", False):
|
|
return simplified
|
|
|
|
# Extract graph data - typically has nodes and edges
|
|
result = simplified.get("result", {})
|
|
edges = result.get("edges", []) if isinstance(result, dict) else []
|
|
nodes = result.get("nodes", []) if isinstance(result, dict) else []
|
|
|
|
if not edges:
|
|
return simplified # Return as-is if no edges
|
|
|
|
# Build query params for cursor hashing
|
|
query_params = {
|
|
"tool": "analysis_get_callgraph",
|
|
"port": port_to_use,
|
|
"name": name,
|
|
"address": address,
|
|
"max_depth": max_depth,
|
|
"grep": grep
|
|
}
|
|
|
|
sid = _get_session_id(ctx)
|
|
|
|
# Paginate edges (nodes are typically smaller, include all)
|
|
paginated = paginate_response(
|
|
data=edges,
|
|
query_params=query_params,
|
|
tool_name="analysis_get_callgraph",
|
|
session_id=sid,
|
|
page_size=min(page_size, MAX_PAGE_SIZE),
|
|
grep=grep,
|
|
grep_ignorecase=grep_ignorecase,
|
|
return_all=return_all
|
|
)
|
|
|
|
# Reconstruct result with paginated edges
|
|
if paginated.get("success"):
|
|
paginated["result"] = {
|
|
"root_function": func_id,
|
|
"max_depth": max_depth,
|
|
"nodes": nodes, # Include all nodes for context
|
|
"edges": paginated.get("result", []),
|
|
"total_nodes": len(nodes),
|
|
}
|
|
|
|
return paginated
|
|
|
|
@mcp.tool()
|
|
def analysis_get_dataflow(
|
|
address: str,
|
|
direction: str = "forward",
|
|
max_steps: int = 50,
|
|
port: int = None,
|
|
# Pagination parameters
|
|
page_size: int = DEFAULT_PAGE_SIZE,
|
|
grep: str = None,
|
|
grep_ignorecase: bool = True,
|
|
return_all: bool = False,
|
|
ctx: Context = None
|
|
) -> dict:
|
|
"""Perform data flow analysis with cursor-based pagination on steps
|
|
|
|
Args:
|
|
address: Starting address in hex format
|
|
direction: "forward" or "backward" (default: "forward")
|
|
max_steps: Maximum analysis steps (default: 50)
|
|
port: Specific Ghidra instance port (optional)
|
|
page_size: Steps per page (default: 50, max: 500)
|
|
grep: Regex pattern to filter steps (e.g., "MOV|LEA", "EAX|RAX")
|
|
grep_ignorecase: Case-insensitive grep (default: True)
|
|
return_all: Return all steps without pagination
|
|
ctx: FastMCP context (auto-injected)
|
|
|
|
|
|
Returns:
|
|
dict: Data flow steps with pagination. Use cursor_next(cursor_id) for more.
|
|
|
|
Examples:
|
|
# Track data flow, filter for memory operations
|
|
analysis_get_dataflow(address="0x401000", grep="MOV|PUSH|POP")
|
|
|
|
# Backward flow to find data sources
|
|
analysis_get_dataflow(address="0x401000", direction="backward", grep="LEA|MOV")
|
|
"""
|
|
if not address:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "MISSING_PARAMETER",
|
|
"message": "Address parameter is required"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
port_to_use = _get_instance_port(port)
|
|
|
|
params = {
|
|
"address": address,
|
|
"direction": direction,
|
|
"max_steps": max_steps
|
|
}
|
|
|
|
response = safe_get(port_to_use, "analysis/dataflow", params)
|
|
simplified = simplify_response(response)
|
|
|
|
if not simplified.get("success", False):
|
|
return simplified
|
|
|
|
# Extract dataflow steps
|
|
result = simplified.get("result", {})
|
|
steps = result.get("steps", []) if isinstance(result, dict) else []
|
|
|
|
if not steps:
|
|
return simplified # Return as-is if no steps
|
|
|
|
# Build query params for cursor hashing
|
|
query_params = {
|
|
"tool": "analysis_get_dataflow",
|
|
"port": port_to_use,
|
|
"address": address,
|
|
"direction": direction,
|
|
"max_steps": max_steps,
|
|
"grep": grep
|
|
}
|
|
|
|
sid = _get_session_id(ctx)
|
|
|
|
# Paginate steps
|
|
paginated = paginate_response(
|
|
data=steps,
|
|
query_params=query_params,
|
|
tool_name="analysis_get_dataflow",
|
|
session_id=sid,
|
|
page_size=min(page_size, MAX_PAGE_SIZE),
|
|
grep=grep,
|
|
grep_ignorecase=grep_ignorecase,
|
|
return_all=return_all
|
|
)
|
|
|
|
# Reconstruct result with paginated steps
|
|
if paginated.get("success"):
|
|
paginated["result"] = {
|
|
"start_address": address,
|
|
"direction": direction,
|
|
"steps": paginated.get("result", []),
|
|
}
|
|
# Preserve other metadata
|
|
if isinstance(result, dict):
|
|
for key in ["sources", "sinks", "total_steps"]:
|
|
if key in result:
|
|
paginated["result"][key] = result[key]
|
|
|
|
return paginated
|
|
|
|
@mcp.tool()
|
|
def ui_get_current_address(port: int = None) -> dict:
|
|
"""Get the address currently selected in Ghidra's UI
|
|
|
|
Args:
|
|
port: Specific Ghidra instance port (optional)
|
|
|
|
Returns:
|
|
Dict containing address information or error
|
|
"""
|
|
port = _get_instance_port(port)
|
|
response = safe_get(port, "address")
|
|
return simplify_response(response)
|
|
|
|
@mcp.tool()
|
|
def ui_get_current_function(port: int = None) -> dict:
|
|
"""Get the function currently selected in Ghidra's UI
|
|
|
|
Args:
|
|
port: Specific Ghidra instance port (optional)
|
|
|
|
Returns:
|
|
Dict containing function information or error
|
|
"""
|
|
port = _get_instance_port(port)
|
|
response = safe_get(port, "function")
|
|
return simplify_response(response)
|
|
|
|
@mcp.tool()
|
|
def comments_set(address: str, comment: str = "", comment_type: str = "plate", port: int = None) -> dict:
|
|
"""Set a comment at the specified address
|
|
|
|
Args:
|
|
address: Memory address in hex format
|
|
comment: Comment text (empty string removes comment)
|
|
comment_type: Type of comment - "plate", "pre", "post", "eol", "repeatable" (default: "plate")
|
|
port: Specific Ghidra instance port (optional)
|
|
|
|
Returns:
|
|
dict: Operation result
|
|
"""
|
|
if not address:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "MISSING_PARAMETER",
|
|
"message": "Address parameter is required"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
port = _get_instance_port(port)
|
|
payload = {
|
|
"comment": comment
|
|
}
|
|
|
|
response = safe_post(port, f"memory/{address}/comments/{comment_type}", payload)
|
|
return simplify_response(response)
|
|
|
|
@mcp.tool()
|
|
def functions_set_comment(address: str, comment: str = "", port: int = None) -> dict:
|
|
"""Set a decompiler-friendly comment (tries function comment, falls back to pre-comment)
|
|
|
|
Args:
|
|
address: Memory address in hex format (preferably function entry point)
|
|
comment: Comment text (empty string removes comment)
|
|
port: Specific Ghidra instance port (optional)
|
|
|
|
Returns:
|
|
dict: Operation result
|
|
"""
|
|
if not address:
|
|
return {
|
|
"success": False,
|
|
"error": {
|
|
"code": "MISSING_PARAMETER",
|
|
"message": "Address parameter is required"
|
|
},
|
|
"timestamp": int(time.time() * 1000)
|
|
}
|
|
|
|
port_to_use = _get_instance_port(port)
|
|
|
|
# Try setting as a function comment first using PATCH
|
|
try:
|
|
func_patch_payload = {
|
|
"comment": comment
|
|
}
|
|
patch_response = safe_patch(port_to_use, f"functions/{address}", func_patch_payload)
|
|
if patch_response.get("success", False):
|
|
return simplify_response(patch_response) # Success setting function comment
|
|
else:
|
|
print(f"Note: Failed to set function comment via PATCH on {address}, falling back. Error: {patch_response.get('error')}", file=sys.stderr)
|
|
except Exception as e:
|
|
print(f"Exception trying function comment PATCH: {e}. Falling back.", file=sys.stderr)
|
|
# Fall through to set pre-comment if PATCH fails
|
|
|
|
# Fallback: Set as a "pre" comment using the comments_set tool
|
|
print(f"Falling back to setting 'pre' comment for address {address}", file=sys.stderr)
|
|
return comments_set(address=address, comment=comment, comment_type="pre", port=port_to_use)
|
|
|
|
|
|
# ================= Startup =================
|
|
|
|
def main():
|
|
register_instance(DEFAULT_GHIDRA_PORT,
|
|
f"http://{ghidra_host}:{DEFAULT_GHIDRA_PORT}")
|
|
|
|
# Use quick discovery on startup
|
|
_discover_instances(QUICK_DISCOVERY_RANGE)
|
|
|
|
# Start background discovery thread
|
|
discovery_thread = threading.Thread(
|
|
target=periodic_discovery,
|
|
daemon=True,
|
|
name="GhydraMCP-Discovery"
|
|
)
|
|
discovery_thread.start()
|
|
|
|
signal.signal(signal.SIGINT, handle_sigint)
|
|
mcp.run(transport="stdio")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main() |