{"id":"reverse-engineering-assistant","name":"ReVa (Reverse Engineering Assistant)","homepage":"https://github.com/cyberkaida/reverse-engineering-assistant","repo_url":"https://github.com/cyberkaida/reverse-engineering-assistant","category":"security","subcategories":["mcp-server","reverse-engineering","binary-analysis"],"tags":["ghidra","reverse-engineering","binary-analysis","mcp","security","firmware","ctf","decompilation"],"what_it_does":"Ghidra extension that implements an MCP server, enabling AI language models to perform reverse engineering tasks like decompilation, symbol renaming, encryption detection, and binary analysis directly through Ghidra's analysis engine.","use_cases":["AI-assisted firmware analysis for embedded systems security research","Automated CTF binary challenge solving with LLM-guided exploration","Large binary examination with AI-directed decompilation and annotation","Encryption algorithm detection and analysis in compiled binaries","CI/CD pipeline integration for automated headless binary analysis"],"not_for":["Non-Ghidra reverse engineering workflows (IDA Pro, Binary Ninja users)","Dynamic analysis or runtime debugging — Ghidra is a static analysis tool","Teams without Ghidra 12.0+ installed"],"best_when":"You are doing security research, firmware analysis, or CTF work in Ghidra and want an AI assistant with deep, tool-native access to decompilation results, cross-references, and symbol information.","avoid_when":"You use IDA Pro, Binary Ninja, or other reverse engineering tools, or need dynamic/runtime analysis capabilities.","alternatives":["BinBot (IDA plugin)","Binary Ninja AI plugins","Capa (malware analysis)","manual Ghidra scripting"],"af_score":74.2,"security_score":55.0,"reliability_score":null,"package_type":"mcp_server","discovery_source":["github"],"priority":"low","status":"evaluated","version_evaluated":"latest","last_evaluated":"2026-03-01T09:50:06.146459+00:00","performance":{"latency_p50_ms":null,"latency_p99_ms":null,"uptime_sla_percent":null,"rate_limits":null,"data_source":"llm_estimated","measured_on":null}}