Raptor Loop Hunt
Description
RAPTOR autonomous looping multi-altitude security vulnerability hunt — Claude Code skill
Installation
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open the source below and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
README
raptor-loop-hunt
An autonomous, looping, multi-altitude **security vulnerability hunt** for a codebase, packaged as a Claude Code **skill**. It replaces the model's default "single pass, summarize, stop" behaviour with an explicit search procedure: traverse every altitude, generate candidates, adversarially verify them *from raw source*, run isolated parallel reasoners, and keep a persistent ledger so each loop is net-new coverage instead of rediscovery. In practice it finds far more real bugs than a one-shot scan — the "Karpathy auto-research" methodology.
It triggers whenever you point Claude at source code and want vulnerabilities found — "audit this", "find every bug", "security-review it", "find anything exploitable".
Install
**As a plugin — no clone needed.** Add the marketplace and install; Claude Code fetches it for you:
/plugin marketplace add dinosn/raptor-loop-hunt
/plugin install raptor-loop-hunt@raptor
Then `/reload-plugins` (or restart). The skill auto-triggers on audit requests, or invoke it directly.
**Or drop it in as a personal skill** — clone into your Claude Code skills directory and it is discovered automatically on the next session:
git clone https://github.com/dinosn/raptor-loop-hunt ~/.claude/skills/raptor-loop-hunt
Use
Invoke it explicitly:
/raptor-loop-hunt
…or just describe an audit task ("audit ./src for security", "find every exploitable bug in this service") and the skill triggers on its own. Point it at a repo, a service, a module, or a directory.
What it does
- Multi-altitude generate → judge → verify loop. Candidates are generated at every altitude (whole-system down to a single function), then adversarially judged and verified from raw source — never from the generator's own summary.
- Isolated parallel reasoners so independent findings don't contaminate one another.
- Monotonic-scrutiny knowledge base (
raptor-loop-kb) that can only ever raise scrutiny across
Related Skills
Fastapi Review
Review a FastAPI application for architecture, async correctness, dependency injection, Pydantic schemas, secu
Security Defense in Depth
Implement multi-layered testing and security best practices.
Security SecLists Official Repository
[OWASP Testing Guide](https://owasp.org/www-project-web-security-testing-guide/)
Security Threat Hunting with Sigma Rules
Use Sigma detection rules to hunt for threats and analyze security events
Security Maintenance Walkthrough - 2026-03-29
- Re-triaged the full 2026-03-15 security finding set against current `main` and wrote a fresh current-head re
Security Google Workspace Model Armor
Filter user-generated content for safety
Security Related Agents
Django Reviewer
Expert Django code reviewer specializing in ORM correctness, DRF patterns, migration safety, security misconfi
Token Auditor
Scans ui/src/ for hardcoded visual values, duplicate components, and shadcn replacement candidates; produces d
Gitnexus Security Boundary Reviewer
GitNexus security and trust-boundary reviewer. Use for auth, permissions, secrets, injection, unsafe parsing,