When AI goes Rogue
AI shuts it Down.
AgentPatrol's on device AI continuously monitors every autonomous agent on your system detecting credential theft, prompt injection, and lateral movement then blocks the threat before damage occurs.
AI catching AI. In real time.
AgentPatrol's detection engine tracks every agent's behavioral fingerprint. The moment one deviates credential access, unexpected egress, lateral reach the AI isolates it autonomously.
A real attack, caught and filed in 11ms.
This panel is live watch the attack unfold, escalate, and get blocked. The simulation loops continuously while visible.
- /etc/passwd
- /var/log/auth.log
- /home/user/.ssh/id_rsa
- /tmp/.x1f2 (unsigned)
- /var/bin/curl
- ›read credential material
- ›establish remote shell
- ›exfiltrate to c2 server
- [01.00]●agent[scraper-worker] spawned child: /bin/sh -c curl
- [02.20]●agent accessed /etc/passwd
- [04.20]●unusual outbound traffic spike → 185.42.xx.xx:443
- [05.10]●executing unknown script from /tmp/.x1f2
- [06.00]●signature mismatch: unsigned binary
- [07.10]●behavior cluster: data-exfiltration · 0.94
- [08.20]●policy match: no-outbound-shell (strict)
- [09.40]●process terminated · PID 48219
- [10.40]●threat neutralized · incident #A-4812 filed
- [11.30]●intercepting syscall: execve()
Four layers of AI defense.
AgentPatrol installs as a single local daemon kernel level telemetry feeds an on-device AI that detects and blocks rogue agents before they cause harm.
Live agent map, risk timelines, AI generated incident reports, policy editor, and one-click rollback all in a single console.
Declarative rules evaluated in microseconds. Allow, throttle, block, or quarantine any agent behavior enforced before the action completes.
On-device models score 140+ behavioral signals per agent. Detects credential theft, prompt injection, data exfiltration, and lateral movement then triggers autonomous blocking in <10ms. No cloud, no egress.
eBPF / kauth / ptrace hooks capture syscalls, file access, network connections, and child processes at the kernel level zero-latency, zero-egress.
AI deployed against AI. Autonomously.
AgentPatrol runs an on device detection model alongside every AI agent on your system. It learns normal, flags deviations the moment they happen, and blocks threats without waiting for a human.
Builds a live model of each AI agent's normal behavior prompts issued, tools called, syscalls made, egress destinations. Learns continuously.
Scores every action against the agent's profile in <10ms. Flags credential theft, prompt injection, data exfiltration, and lateral movement in real time.
When risk exceeds threshold, the AI acts severs streams, kills the process, quarantines the agent. No human approval required.
The agent claude-worker deviated sharply from its behavioral baseline reading credential files outside its declared scope, then initiating high-frequency egress to an unknown host. The detection model classified this as credential-exfiltration and autonomously terminated the agent's network access in 872ms.
AI fighting AI. At every layer.
Continuously learns each agent's normal fingerprint prompts, tool calls, syscalls, egress. Deviations trigger scoring the moment they happen.
Pattern matched against known AI attack vectors: prompt injection, credential exfiltration, jailbreak attempts, and lateral movement between agents.
When the AI confirms a threat, it acts kills streams, quarantines the process, severs connections. No human approval. No delay.
140+ behavioral signals scored per agent, per action. Risk score updated every tick at sub-10ms latency no cloud round-trip.
Every model runs fully on device. No data leaves your machine. Fully air gap compatible. SOC 2 Type II compliant by design.
Works across every AI runtime: node, python, rust, go, shell agents, MCP servers, copilots, and locally-hosted LLMs.