Tag
#ai-defense
6 posts tagged ai-defense.
- Defense
Output Filtering Architecture for Production LLMs: Semantic Classifiers, Regex Guards, and LLM-as-Judge
A deep-dive into layered output filtering for production LLMs — combining semantic classifiers, regex scrubbing, and LLM-as-judge techniques to catch harmful, policy-violating, and hallucinated content before it reaches users or downstream systems.
- Defense
Monitoring LLM Outputs in Production: Anomaly Detection, Latency Alerting, and Output Drift
How to build a production observability stack for LLM outputs — covering anomaly detection pipelines, latency threshold alerting, output drift signals, and concrete alerting logic you can deploy today.
- Defense
Prompt Injection Prevention: System Prompt Hardening, Instruction Hierarchy, and Privilege Separation
A technical guide to preventing prompt injection attacks in production LLMs — covering system prompt hardening, privilege-separated architectures, instruction hierarchy, and defense-in-depth patterns with vulnerable vs. hardened code examples.
- Defense
Output Filtering Architecture for Production LLMs: A Defense Engineer's Blueprint
How to architect a multi-layer output filtering pipeline for production LLMs — covering deterministic guards, ML classifiers, schema validation, and async sequencing patterns to minimize latency while maximizing coverage.
- Defense
Prompt Injection Prevention: Defense-in-Depth for Production LLM Systems
A systems-level guide to preventing prompt injection attacks in production LLMs — covering defense-in-depth layering, structural prompt architecture, privilege separation, and continuous adversarial validation with concrete implementation patterns.
- Defense
AI Defense Techniques for LLMs: A Practitioner's Guide to Securing Large Language Models
A technical breakdown of proven AI defense techniques for LLMs — from input guardrails and prompt hardening to dual-model architectures and red teaming, mapped to OWASP and NIST frameworks.