AI Agent Detection

Detect when AI agents go rogue

AI agents are gaining access to your infrastructure. Tracebit deploys canary resources that detect when agents go rogue, get compromised, or exceed their intended scope.

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The problem

AI agents are a new attack surface

AI agents are still early, but Tracebit is already detecting rogue agents in production environments. Because agents are already authorized to access your systems, they're hard to distinguish from legitimate activity when compromised or manipulated.

52%

of employees willing to use AI even if it violates policy

CalypsoAI Insider AI Threat Report 2025

28%

of employees have used AI to access sensitive data

CalypsoAI Insider AI Threat Report 2025

2025

first AI-enabled malware observed in active operations

Google Threat Intelligence Group 2025

Detection coverage

Detection across AI agent threat scenarios

From prompt injection to agent compromise, canaries detect when AI goes wrong.

Stage

Attack

Detection

Prompt Injection

Attacker manipulates agent via malicious input

Agent accesses canary resources outside scope

Agent Compromise

Agent credentials stolen or misused

Canary credentials used from unexpected source

Scope Creep

Agent explores beyond intended boundaries

List operations on canary resources

Data Exfiltration

Compromised agent extracts sensitive data

Read operations on canary storage

How it works

Deploy AI agent monitoring in minutes

Tracebit integrates with your existing infrastructure to deploy canaries that detect AI agent misbehavior.

Step 1

Connect your platforms

Integrate your cloud accounts and Kubernetes clusters where AI agents operate.

Step 2

Deploy canaries outside agent scope

Tracebit creates canary resources that legitimate agents should never access.

Step 3

Monitor agent behavior

Any agent interaction with canary resources triggers an immediate alert.

Step 4

Investigate with context

See exactly which agent, credential, or IP accessed the canary resource.