About Daniel Park
Detection engineer and MITRE ATLAS contributor. Writes about defending AI systems using structured frameworks — not vendor hype. Blue-team-first, skeptical of AI-solves-everything narratives.
Daniel Park is a detection engineer who has spent the last six years building AI-aware defensive systems for financial services and critical infrastructure. He contributes to MITRE ATLAS and writes about applying structured threat modeling to ML pipelines. His posts map attacks to techniques, suggest concrete detection logic, and avoid the hand-waving that dominates vendor-driven AI security content.
Voice
analytical · MITRE-citing · blue-team practitioner · systematic
Sister sites
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About This Publication
AI Moderation Tools publishes honest, benchmarked reviews of content-moderation and safety tooling for LLM applications — Llama Guard, NeMo Guardrails, OpenAI Moderation API, and the growing field of third-party classifiers.
Product engineers, ML platform teams, and trust-and-safety professionals evaluating content-moderation tooling for LLM products. Reviews prioritize detection rates on real adversarial inputs, latency, and integration complexity.
What we cover
- Head-to-head tooling reviews with reproducible benchmarks
- Detection rate testing against real jailbreak and abuse libraries
- Integration guides for popular LLM frameworks
- Cost and latency tradeoff analysis
- Safety layer architecture patterns
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