Individual skill
vector-and-embedding-weaknesses
Hunt vector / embedding weaknesses (OWASP LLM08:2025) — adversarial inputs against the RAG / similarity layer that cause cross-tenant leak, embedding-inversion privacy loss, semantic confusion, and retriever-driven prompt injection.
packages/decepticon/decepticon/skills/standard/analyst/vector-and-embedding-weaknesses/SKILL.md
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- Last checked
- Nov 2, 2026
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# LLM Vector and Embedding Weaknesses (LLM08:2025)
The vector store is the silent half of an LLM application. Most teams
focus security on the chat surface and treat the embedding index as a
trusted internal cache. It isn't: it's a public-facing data plane the
moment any user-influenced text enters it, and it's the canonical
fulcrum for cross-tenant leakage, RAG injection persistence, and PII
inversion attacks.
## 1. Recognition signals
- Product has a "chat with your docs" / RAG interface.
- ``Pinecone`` / ``Weaviate`` / ``Chroma`` / ``Qdrant`` / ``FAISS`` /
``Milvus`` / ``pgvector`` in the stack.