Cisco Open Sources Quarry to Catch AI Agent Attacks Hidden in Harmless Steps

Detecting an AI agent attack isn’t simply finding multiple small needles scattered in a large haystack; it is recognizing whether and for what purpose the needles are connected.

Traditional security controls evaluate single actions to classify whether an intent is bad or benign. This approach fails on AI agent activity when the bad intent only emerges over a series of benign actions. It only becomes apparent if and when the overall sequence of actions is viewed or actioned.

Fraud detection is an example. A bank analyzes each purchase on its own. That’s largely how traditional security operates. Fraud detection, however, needs to see patterns of apparently benign single purchases across multiple purchases, possibly in multiple locations with unlikely timing (potentially employing agent capability). “Agent security needs the same combination of pattern detection and evidence, applied to the steps an agent takes rather than to purchases,” writes Cisco in announcing…