ze-mu-zhou

ze-mu-zhou / IDACLI

Public

AI-native IDA Pro kernel — unrestricted IDAPython over JSONL, persistent sessions, zero dependencies. Let your agent drive IDA, not call tools.

agent ai binary-analysis claude-code cli
27
1
69% credibility
Found May 02, 2026 at 25 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

IDA-CLI is a command-line tool that enables AI agents to directly access and analyze IDA Pro databases for binary reverse engineering without graphical interfaces.

How It Works

1
📖 Discover IDA-CLI

You hear about a helpful tool that lets smart AI assistants dive deep into computer files to uncover their secrets.

2
🛠️ Set it up simply

Follow easy steps to install the tool on your computer, no complicated stuff needed.

3
💼 Choose your file

Pick the mysterious computer file you want your AI to explore and understand.

4
🤖 Team up with AI

Connect the tool to your friendly AI helper, giving it full access to peek inside the file.

5
🔍 Ask away

Chat with your AI, asking it to find functions, draw maps, or explain tricky parts.

6
✨ See insights flow

Watch as clear explanations, diagrams, and discoveries pop up right before your eyes.

🎉 Master the file

Your AI unlocks every detail, letting you rename parts, add notes, and save your new understanding.

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AI-Generated Review

What is IDACLI?

IDACLI delivers an AI-native IDA Pro kernel in Python, piping unrestricted IDAPython over JSONL for persistent sessions with zero dependencies. Fire up `ida-ai target.i64` and AI agents send arbitrary code via stdin, getting structured JSONL responses from a live IDA database—no GUI, no wrappers. It solves boxed-in tool-calling by letting agents drive IDA directly, with helpers for decompiles, xrefs, CFGs, and mutations like renames or patches.

Why is it gaining traction?

Unlike MCP/REST APIs with fixed schemas and network lag, IDACLI offers full IDAPython freedom, persistent caches, and parallel kernels on database copies—all local and low-latency. AI helpers like `ai.pwn_overview()` or `ai.focus()` cut boilerplate, while the agent bridge and installable skills for OpenAI/Claude make integration dead simple. Zero deps hook devs building agent-driven RE pipelines.

Who should use this?

Reverse engineers crafting AI agents for binary triage, CTF pwn teams automating vuln hunts, or ai-native development github workflows around IDA Pro. Perfect for folks chaining decompiles/xrefs into agent loops without predefined tools.

Verdict

Worth a spin for ai-native github prototypes—solid benches/tests despite 15 stars and 0.70% credibility score signal early promise over polish. Maturity lags, but persistent JSONL kernel nails the agent-drive-IDA pitch.

(198 words)

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