IDAssist Documentation

Welcome to the IDAssist documentation. This guide covers installation, configuration, and usage of IDAssist — an AI-powered reverse engineering plugin for IDA Pro.

What is IDAssist?

IDAssist is an IDA Pro plugin that brings LLM-powered analysis directly into your reverse engineering workflow. It provides AI-assisted function explanation, interactive querying, automated rename suggestions, a semantic knowledge graph, RAG-powered document search, and collaborative symbol sharing through SymGraph.

IDAssist runs as a dockable panel inside IDA Pro 9.0+ and connects to LLM providers (Anthropic, OpenAI, Ollama, LiteLLM) to analyze binary code. All data is stored locally in SQLite databases under ~/.idapro/idassist/.

Tabs Overview

IDAssist organizes its functionality into seven tabs:

Tab	Description
Explain	Generate function and line explanations with security analysis
Query	Interactive chat with context macros, ReAct agent, and MCP tools
Actions	AI-powered rename and retype suggestions with confidence scores
Semantic Graph	Knowledge graph with visual explorer, search, and community detection
RAG	Upload reference documents for context-enriched analysis
Settings	Configure LLM providers, MCP servers, SymGraph credentials, system prompt, and database paths

Key Features

MCP Tool Integration

IDAssist provides built-in internal tools — function lookup, disassembly, pseudocode, cross-references, renaming, and graph queries — that LLMs can invoke during reasoning via function calling. You can also connect to external MCP servers for additional tool capabilities.

ReAct Agent

The Query tab supports an autonomous ReAct agent mode where the LLM plans an investigation, executes tools to gather information, reflects on findings, and synthesizes answers across multiple reasoning rounds.

Extended Thinking

Control reasoning depth with four effort levels:

Level	Token Budget	Use Case
None	Disabled	Quick, simple questions
Low	~2K tokens	Straightforward analysis
Medium	~10K tokens	Moderate complexity
High	~25K tokens	Deep analysis, complex functions

Semantic Graph

Build a searchable knowledge graph of the binary’s functions, relationships, and security characteristics. Includes: - Automatic function indexing via idautils.Functions() - LLM-generated summaries for each function - Security flag detection (buffer overflow, injection, format string, etc.) - Network flow and taint analysis - Community detection for module identification - Visual graph rendering with Graphviz layout

Supported LLM Providers

Type	Auth	Streaming	Tool Calling
`anthropic_platform`	API Key	Yes	Yes
`anthropic_oauth`	OAuth	Yes	Yes
`anthropic_claude_cli`	Local CLI	Yes	Yes
`openai_platform`	API Key	Yes	Yes
`openai_oauth`	OAuth	Yes	Yes
`ollama`	None (local)	Yes	Model-dependent
`litellm`	Proxy URL	Yes	Provider-dependent

Recommended Models

Provider	Model	Notes
Anthropic	`claude-sonnet-4-6`	Best balance of speed and quality
OpenAI	`gpt-5.3-codex`	Fast general analysis
Ollama	`qwen2.5-coder:32b`	Fully local, no API key

Architecture Overview

IDAssist uses an MVC architecture:

idassist_plugin.py          # IDA plugin entry point
src/
├── views/                  # PySide6 tab widgets (UI)
├── controllers/            # Signal handlers, state management
├── services/               # Business logic, DB access
│   ├── llm_providers/      # LLM provider implementations
│   ├── graphrag/           # Knowledge graph services
│   ├── streaming/          # Streaming response rendering
│   └── ...
└── mcp_server/             # Internal tool definitions and handlers

Views emit Qt signals on user interaction
Controllers connect signals to service methods
Services handle LLM calls, database access, and graph analysis
All IDA API calls run on the main thread via execute_on_main_thread()
LLM responses stream incrementally to the UI

Getting Started

New to IDAssist? Start with the Getting Started Guide for installation, provider setup, and your first analysis.

Workflows

Step-by-step guides for common tasks:

Explain Workflow — Analyze and document functions
Query Workflow — Ask questions with context macros, MCP, and ReAct
Semantic Graph Workflow — Build and explore the binary knowledge graph

Tab Reference

Detailed reference for each tab’s UI elements and capabilities: