ghidra-cli: Automate Ghidra reverse engineering from the command line

by akiselev · Agent Tool · ★ 248

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install ghidra-cli

git clone https://github.com/akiselev/ghidra-cli

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 75/100

Flagged: sudo usage. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

ai-agentsautomationbinary-analysisclaude-codeclidecompilerghidraheadlessllmmalware-analysis

Quick Facts

Stars248
Forks28
LanguageRust
CategoryAgent Tool
LicenseGPL-3.0
Quality Score75/100
Open Issues10
Last Updated2026-10-18
Created2026-01-12
Platformsclaude-code, cli, rust
Est. Tokens~25k

About ghidra-cli

Ghidra CLI A high-performance Rust CLI for automating Ghidra reverse engineering tasks, designed for both direct usage and AI agent integration (like Claude Code). Features Direct bridge architecture - CLI connects directly to a Java bridge running inside Ghidra's JVM Auto-start bridge - Import/analyze commands automatically start the bridge Fast queries - Sub-second response times with Ghidra...

Compatible Skills

These tools work well together with ghidra-cli for enhanced workflows:

  • open-reverselab — semantic(0.48)+complementary+rare_topics+similar_pop+shared_platform (70%)
  • rea — semantic(0.40)+complementary+rare_topics+similar_pop+shared_platform (63%)
  • x64dbg_mcp — semantic(0.35)+complementary+rare_topics+similar_pop+shared_platform (61%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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