by mrphrazer · MCP Server · ★ 312
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Featured in: AI Reverse Engineering Tools
git clone https://github.com/mrphrazer/agentic-malware-analysis.gitTaken from the project's README on GitHub.
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.
| Stars | 312 |
| Forks | 47 |
| Language | YARA |
| Category | MCP Server |
| License | GPL-2.0 |
| Quality Score | 74/100 |
| Last Updated | 2026-03-22 |
| Created | 2026-03-18 |
| Platforms | claude-code, cli, codex, mcp |
| Est. Tokens | ~21k |
Agentic Malware Analysis Automated deep malware reverse engineering driven by AI agents. A Kali-based Docker environment pairs 50+ RE tools with MCP-connected disassembler backends ([Binary Ninja][binary-ninja-headless-mcp] or [Ghidra][ghidra-headless-mcp]) and a structured multi-phase orchestrator skill that turns a raw binary into a case directory of ranked evidence, validated hypotheses,...
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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: