#llm-security

• Indirect Prompt Injection Explained: Defenses That Hold

  How indirect prompt injection works, why LLMs cannot separate instructions from data, and the layered defenses Microsoft and Google use.

• Jailbreak Detection for LLMs Explained: How Runtime Filters Work

  A plain-language breakdown of jailbreak detection for LLMs: how perplexity heuristics and classifiers work, where they sit, and where they fail.

• Secure RAG Architecture Best Practices for Production LLM Systems

  A practitioner's guide to secure RAG architecture best practices: threat vectors, access control, retrieval isolation, and vector database hardening.

• Prompt Injection Detection Methods: A Practitioner's Guide

  A comparative guide to prompt injection detection methods: classifier scanning, representation analysis, canary tokens, and output monitoring.

• Output Filtering Architecture for Production LLMs

  How to architect a multi-layer output filtering pipeline for production LLMs: deterministic guards, classifiers, schema validation, and async sequencing.

• LLM Output Filter Latency: Budgeting Each Layer

  What each output-filter layer costs in latency, from sub-millisecond regex checks to LLM-as-judge, and how to sequence them inside a real p95 budget.

• Prompt Injection Prevention: Defense in Depth

  A systems-level guide to preventing prompt injection in production LLMs, covering layered controls, structural prompt design, and privilege separation.

• System Prompt Hardening Against Prompt Injection

  How to harden an LLM system prompt against injection: explicit trust models, instruction hierarchy, and privilege separation between model roles.

• Building an Internal Adversarial Testing Pipeline for LLMs

  How to build an internal adversarial testing pipeline for LLM applications with garak, promptfoo, and custom probes, including a CI integration pattern.

• AI Defense Techniques for LLMs: A Practitioner's Guide

  A technical breakdown of LLM defense techniques, from input guardrails and prompt hardening to dual-model architectures, mapped to OWASP and NIST.

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