hunt-rag-vector

hunt-rag-vector is a RAG & retrieval skill for AI agents, published by elementalsouls in the Claude-BugHunter repository on GitHub. Skillspace rates hunt-rag-vector D (68/100) and it passed the safety scan; the rating is based on static analysis only.

Hunt vector-store / embedding-layer weaknesses in RAG pipelines (OWASP LLM08 Vector and Embedding Weaknesses) — persistent corpus poisoning that survives across sessions and users (distinct from one-shot indirect prompt injection, which is owned by hunt-llm-ai), cross-tenant vector-database IDOR (unauthenticated or unscoped queries against Pinecone/Weaviate/Chroma/Milvus/Qdrant/pgvector), source-text/metadata leakage in similarity-search results, and retrieval-hijack via adversarial embedding proximity ('SEO poisoning' for RAG). Targets: any app with a shared knowledge base, document upload feeding a chatbot, or a directly reachable vector-DB port. Validate: a second, clean session/account must inherit a poisoned result, or a cross-tenant artifact must be independently verifiable — confabulation is not a finding, same bar as hunt-llm-ai. Use when target is RAG-backed, exposes a vector-DB port, or lets users upload documents that other users' queries later retrieve.

Grade

D

Quality

68 / 100

Safety

Passed

GitHub stars

4,464

Unproven: rated by static analysis only, not yet compared head-to-head.

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