Meet GitGuardian's Machine Learning-Powered Risk Scoring

The GitGuardian Platform now automatically ranks every secrets incident with a risk score from 0–100, turning alert floods into a prioritized, trustworthy work queue.

Scores are computed from incident context (like validity, exposure, where it was found, and exploitability) and build on existing ML capabilities like Secret Enricher and our False-Positive Remover, which cuts false positives by 80%+.

Want the technical deep dive on how we trained it? Check out our blog post
https://blog.gitguardian.com/how-machine-learning-transforms-security-alert-chaos-into-actionable-intelligence/

https://docs.gitguardian.com/releases/saas/2025/12/17/2-changelog

More on GitGuardian's False Positive Remover:
https://blog.gitguardian.com/ai-false-positive-remover-v2/

More on GitGuardian's Secrets Enricher:
releases/saas/2025/12/17/changelog

#GitGuardian #SecretsManagement #AppSec #DevSecOps #NHI #SecurityAutomation