The problem
A compromised or misbehaving agent does not look like a classic intrusion — it looks like an agent doing slightly more than usual, then a lot more. Static rules miss it because every agent is different. AI-Attack Detection watches each agent against its own normal behavior and surfaces the phases of an attack as they unfold. To be clear about the boundary: this detects and notifies — you choose the response.
What you get
Outcomes you can take to a skeptical security team.
- Surfaces recon, privilege escalation, exfiltration, and lateral movement
- Catches coordinated multi-agent campaigns, not just a single rogue agent
- Measured against each agent’s own baseline, so different agents are judged fairly
- Honest scope: detection and notification — the response decision stays yours
How it works
Three steps, no surprises.
01
Learn each baseline
Every agent’s normal behavior is established so deviations stand out instead of drowning.
02
Surface the phases
Recon, escalation, exfiltration, lateral movement, and multi-agent activity are flagged as they appear.
03
You decide the response
You get the notification with context; the platform does not act for you here.
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