Break It
Before Release
Expose exploitable AI failures before customers, attackers, or regulators discover them first in a live environment.
Benchmarks Do Not Prove Security
An AI system can pass internal QA and still fail under attack. Expected inputs test expected behavior. Mindgard searches for the unexpected paths: the edge cases, evasions, and attack chains that expose real risk.
Attack Before Every Release
Mindgard finds meaningful failures early by testing the right attack paths first, with fewer prompts and less manual effort.
Turn Failures Into Fixes
A failure report is not enough. Mindgard shows how the weakness was reached, what an attacker could achieve, and where remediation matters. Teams fix the exploitable path, then rerun the attack.
Build Security Into Delivery
Give engineering teams repeatable attack evidence before exploitable weaknesses become production incidents or delay releases.
- Make security a release signal. Add adversarial testing to delivery workflows so teams can identify exploitable regressions before a new version reaches users.
- Give developers reproducible evidence. Capture the attack sequence, affected component, and observed impact so engineering teams can move directly from finding to remediation.
- Track improvement release by release. Compare results over time to show whether changes reduce exploitable risk or quietly reopen weaknesses previously believed fixed.
Learn More
Mindgard has helped some of the world's leading businesses to secure their AI agents, systems and infrastructure against real-world attacks. Learn more about real-life use cases from real customers.
