SECAI Core · phase 13 of 15
Log monitoring
The continuous collection, review, and analysis of system and application logs that record an AI model's inputs, outputs, and errors so that issues can be detected, investigated, and corrected
The Explain card
- Plain English
- Log monitoring is the continuous collection, review and analysis of system and application logs that record an AI model's inputs, outputs and errors, so problems can be detected, investigated and corrected.
- Example
- A team reviewing their chatbot's logs notices a growing number of responses containing internal URLs, and traces it to a retrieval source that was recently misconfigured to include an intranet index.
- Why it matters
- Logs are the flight recorder of an AI system. Without them you cannot investigate an incident, prove what the model said, or notice slow-burning abuse.
- Hook
- If it is not logged, it did not happen, and you cannot prove otherwise.
Where it sits in the deck
Phase 13: Detection, Monitoring, and Threat Intelligence
Defences eventually fail — learn how to detect, correlate, and investigate anomalies in real time across both AI-specific and traditional security telemetry.
