Agent security is a behavioral problem.
Adversarial behavioral testing for agent skills, tools, and MCP servers.
First deployment: auditing 341+ flagged skills from OpenClaw's registry. Results this week.
The Problem
Everyone is deploying agents
40% of enterprise apps will embed agents by 2026. Every one composes with external skills, tools, and MCP servers they don't control.
New architecture, new attack surface
Agents don't just run code. They act on objectives. A clean integration can exfiltrate data, escalate privileges, or leak credentials under the right conditions.
It's already happening
OpenClaw shipped 341+ malicious skills to 172K+ users. Static analysis missed all of them. This isn't theoretical.
How It Works
Sandbox
The agent runs in an isolated environment. No access to host systems, credentials, or external networks.
Adversarial Pressure
Red-team agents probe it with dangerous objectives: data exfiltration, privilege escalation, resource abuse. We observe what it enables.
Score & Certify
Behavioral risk score based on what actually happened. Certify, flag, or quarantine.
In Production
First deployment on OpenClaw's agent registry. Skills autonomously discovered, sandboxed, and risk-scored.
OpenClaw Benchmark
Benchmark in progress.
Evaluating 341+ flagged skills from OpenClaw's registry against Oathe's behavioral analysis. Results publishing this week.
Request a Security Audit
Tell us what agent system you want evaluated.