LLM Pipeline & RAG Infrastructure Hardening
Retrieval-Augmented Generation (RAG) connects enterprise knowledge bases to LLM outputs. Insecure RAG implementations allow attackers to inject malicious documents that trigger indirect prompt injection or bypass access controls to retrieve unauthorized enterprise documents. AgentClad Security audits vector databases, embedding pipelines, semantic search engines, and guardrail filters.
Technical Scoping Activities
- Indirect prompt injection testing via document ingestion and chunking
- Vector database tenant isolation and document-level permission audit
- Embedding inversion and training/retrieval data leakage assessment
- Input/output guardrail filter efficacy and bypass testing
- API rate limiting and cost exhaustion (denial of wallet) evaluation
Concrete Eng Deliverables
- RAG Pipeline Threat Matrix & Audit ReportArtifact Label: [Sample Audit Artifact] - Detailed assessment of vector ingestion, chunking, retrieval permissions, and injection risks.
- Document Access Control & Filtering BlueprintArtifact Label: [Sample Audit Artifact] - Blueprint for enforcing metadata filtering and user security context in vector queries.
- Guardrail Policy & Content Filter RulesetArtifact Label: [Sample Audit Artifact] - Custom guardrail rules for NeMo Guardrails, Llama Guard, or custom filtering proxies.
Engagement RACI & Prerequisites
- Simulate malicious document uploads and indirect injection attacks.
- Evaluate vector search query security and metadata access filters.
- Deliver guardrail configuration files and document sanitization guidelines.
Explicit Engagement Exclusions
- Physical storage drive data recovery or underlying hardware audits.
Practice Area FAQs
How do you test document-level access control in RAG pipelines?
We craft multi-user queries designed to probe whether user A can induce the RAG system to retrieve vector chunks belonging to user B or confidential executive scopes.
Can indirect prompt injection happen through PDF or web uploads?
Yes, hidden text, white-on-white text, or malicious instructions inside ingested documents are classic indirect injection vectors that we test and remediate.
Schedule a Technical Scoping Session for LLM Pipeline & RAG Infrastructure Hardening
Discuss your system architecture, deployment timeline, and compliance targets directly with our AI security engineers.