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Defensive Techniques Tracebit research shows a single planted string engineered to trigger an AI model's safety guardrails can cut successful AI-driven AWS attacks by more than 80 percent.
Defensive Techniques
Practical architectures, frameworks, and controls to secure AI systems in production.
6 min read
Defensive Techniques Canary tokens planted in system prompts, RAG corpora, and training datasets give defenders a zero-false-positive tripwire for detecting prompt extraction attacks, cross-tenant data leakage, and model distillation theft. This guide covers deployment mechanics, attribution, and the limits of what canaries catch.
6 min read
Defensive Techniques When prompt injection succeeds, unconstrained LLM outputs give attackers unlimited action space. Output schema enforcement and grammar-constrained generation shrink that surface meaningfully, even when injection itself can't be fully prevented.
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Defensive Techniques Planting honeypot secrets and canary tokens in locations AI agents browse gives defenders a reliable, low-noise signal when an agent has been compromised or manipulated into exfiltrating credentials.
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Defensive Techniques Microsoft released two open-source tools in May 2026 to bring security testing into the AI agent development lifecycle. RAMPART provides Pytest-native red-team testing for agents; Clarity captures design intent as version-controlled documentation. Both target the gap between building agents and securing them.