x64dbg-rippy: AI reverse engineering assistant for x64dbg

by dariushoule · Agent Tool · ★ 62

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

Security audit verdict: SAFE · quality 73/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

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.

x64dbgx64dbg-plugin

Quick Facts

Stars62
Forks9
LanguageC++
CategoryAgent Tool
Quality Score73/100
Open Issues1
Last Updated2026-03-19
Created2026-03-19
Est. Tokens~17k

About x64dbg-rippy

Rippy AI reverse engineering assistant for x64dbg. Embeds a chat panel directly in the debugger with tool-use capabilities. The AI can read memory, disassemble, set breakpoints, step, and more. Installation Prerequisites x64dbg (snapshot 2025-08-19 or newer) Latest Visual C++ Redistributable (x64 and/or x86 to match your x64dbg) WebView2 Runtime (usually already installed on Windows 10/11) An API...

Compatible Skills

These tools work well together with x64dbg-rippy for enhanced workflows:

  • spectral — semantic(0.31)+complementary+shared_fw(anthropic,openai)+similar_pop (62%)
  • x64dbg_mcp — semantic(0.21)+complementary+rare_topics+same_lang+similar_pop (61%)

x64dbg-rippy alternative? Top 1 similar tools

Looking for a x64dbg-rippy alternative? If you're comparing x64dbg-rippy with other agent tool tools, these 1 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

  • x64dbg_mcp by bromoket · ⭐ 133

    Drive x64dbg with your AI. MCP server: 23 mega-tools / 153 endpoints for breakpoints, memory, disasm, tracing,

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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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