LLM Security
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How to Secure Vector Database Access in RAG Systems
Vector stores in RAG pipelines carry auth gaps, embedding inversion risk and cross-tenant exposure. How to lock down both the read and write path.
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AI Security Review: A Checklist for LLM Systems
An AI security review checklist for LLM systems: trust boundaries, data flows, control mapping, evidence to demand, and the findings reviewers miss.
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How Prompt Injection Detection Works, Tier by Tier
How prompt injection detection works, from input scanning and embedding classifiers to fine-tuned guardrails and runtime monitoring, with the trade-offs.
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OWASP LLM Top 10 2026: Mitigations for Every Risk
A practical OWASP LLM Top 10 2026 mitigation guide covering all ten current risk categories, controls, implementation gaps, and layered defenses.
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PyRIT Review: Microsoft's AI Red Teaming Framework
A review of PyRIT 1.1, Microsoft's open-source AI red teaming framework: its target, attack, converter, scorer and memory design, and multi-turn attacks.
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Rebuff: Open-Source Prompt Injection Defense, Layer by Layer
Rebuff is a self-hosted prompt injection detector with four layers: heuristics, LLM-based detection, a vector database of past attacks, and canary tokens.
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Lakera Guard: Prompt Injection Detection in Practice
Lakera Guard is built for prompt injection detection rather than content moderation. What the documentation shows about coverage, latency, and cost.