AI Security Monitoring

3 articles

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Map

The AI Security Buyer’s Guide: How to Evaluate Vendors for LLM Firewalls, Guardrails, Evals, and Monitoring

AI security buyers should judge vendors by the job to be done: filtering, testing, evals, access, logs, leaks, rules, and proof. Choosing a vendor should start with design and risk, not just labels.

9 min read

Defend

Security Monitoring for AI Agents: How to Detect Dangerous Tool Use Before Damage Happens

Security monitoring for AI agents requires tool-call telemetry, action-sequence detection, approval-state tracking, memory monitoring, credential visibility, anomaly detection, and kill-switch response paths. Dangerous tool use should be detected before it becomes data leakage, unauthorized change, financial impact, or customer-facing error.

10 min read

Defend

AI Logging and Telemetry: What to Capture Without Creating a Privacy Disaster

AI systems need logs because you cannot rebuild what happened from vibes. Security teams need to know what prompt was used, what docs were found, what the model said, what tool was called, who approved it, and what happened next.

9 min read