# retrieval
17 articlestagged with “retrieval”
Memory Priority and Relevance Manipulation
Manipulating memory retrieval ranking and priority scores to surface adversarial memories over legitimate ones.
Memory Retrieval Poisoning
Manipulating memory retrieval mechanisms to surface adversarial context during agent reasoning.
Capstone: Comprehensive RAG Security Assessment
Conduct a thorough security assessment of a Retrieval-Augmented Generation system, testing document poisoning, retrieval manipulation, context window attacks, and data exfiltration vectors.
May 2026: RAG Poisoning Challenge
Inject malicious documents into a retrieval-augmented generation system to control responses for specific queries without disrupting normal operation.
RAG Pipeline Exploitation
Methodology for attacking Retrieval-Augmented Generation pipelines: knowledge poisoning, chunk boundary manipulation, retrieval score gaming, cross-tenant leakage, GraphRAG attacks, and metadata injection.
Dense Retrieval Adversarial Attacks
Adversarial attacks against dense retrieval models used in RAG and search systems.
Embedding Poisoning Techniques
Techniques for poisoning embedding spaces to manipulate retrieval and similarity search.
RAG Retrieval Poisoning
Poisoning document collections to manipulate what gets retrieved by RAG systems, enabling indirect prompt injection at scale.
RAG Retrieval Security
Security of RAG retrieval pipelines from an embedding perspective: how retrieval can be manipulated through poisoned chunks, chunking boundary exploitation, and re-ranking attacks.
RAG Architecture: How Retrieval Systems Work
End-to-end anatomy of a Retrieval-Augmented Generation pipeline — document ingestion, chunking, embedding, indexing, retrieval, context assembly, and generation — with attack surface analysis at each stage.
CTF: RAG Heist
Extract sensitive information from a Retrieval-Augmented Generation system by exploiting retrieval mechanisms, document parsing, embedding manipulation, and context window management vulnerabilities.
RAG Retrieval Poisoning (Rag Data Attacks)
Techniques for poisoning RAG knowledge bases to inject malicious content into LLM context, including embedding manipulation, document crafting, and retrieval hijacking.
Retrieval Manipulation (Rag Data Attacks)
Techniques for manipulating RAG retrieval to control which documents reach the LLM context, including adversarial query reformulation, retriever bias exploitation, and semantic similarity gaming.
Embedding Collision Attack Walkthrough
Craft documents that collide in embedding space with target queries to hijack RAG retrieval results.
Implementing Access Control in RAG Pipelines
Walkthrough for building access control systems in RAG pipelines that enforce document-level permissions, prevent cross-user data leakage, filter retrieved context based on user authorization, and resist retrieval poisoning attacks.
RAG System Red Team Engagement
Complete walkthrough for testing RAG applications: document injection, cross-scope retrieval exploitation, embedding manipulation, data exfiltration through retrieval, and chunk boundary attacks.
DSPy Pipeline Security Testing
End-to-end walkthrough for security testing DSPy optimized LLM pipelines: module enumeration, signature exploitation, optimizer manipulation, retrieval module assessment, and compiled prompt analysis.