$ adversarial scan --target ci
Adversarial agents for your CI/CD
Offensive-grade AI agents that attack your code the way a real adversary would — then hand you the fix. Every pull request is scanned, exploited, and patched before it ships. Humans approve; agents do the hunting.
# how it works
Three steps between merge and breach — closed.
01Connect
Install the GitHub or GitLab app, or drop one step into your existing workflow. No agents to babysit, no dashboards to learn.
02Attack
On every pull request, adversarial agents fork the change, model the attack surface, and attempt real exploits — not pattern matching.
03Patch
Confirmed findings arrive with severity, a reproduction, and a proposed patch as a PR comment or branch. You approve; it merges.
# services
Offensive capability, defensive outcomes
Purpose-built models for finding and fixing bugs and security issues — run as continuous red-team agents inside your pipeline.
CI/CD red-teaming
Continuous adversarial review of every PR: injection, auth flaws, logic bugs, and pipeline misconfigurations.
Automated bug-fix agents
Findings ship with tested, minimal patches pushed as branches your team can review and merge.
Adversarial prompt testing
We attack the AI agents in your own repo — poisoned CLAUDE.md files, malicious tool configs, prompt injection via code comments.
Create a model with us
Custom finding-and-fixing models built with our professional services team — bring your own data, or we generate validated synthetic data for your stack.
# signal, not noise
Built to be believed
# get started
Put an adversary on your payroll
A 30-minute security review of one repository. We'll show you what our agents find — before someone else does.