SelfHack AI is an autonomous AI-driven offensive security platform built as an AI army of coordinated attack agents.
It continuously attacks organizations’ systems the same way real adversaries do  across web and mobile applications, APIs, cloud environments, Kubernetes clusters, and external networks etc.

Unlike traditional vulnerability scanners and point-in-time pentests, SelfHack AI does not rely on static signatures, checklists, or one-off assessments.
It replaces scanners and manual pentesting with real attack execution, exploit validation, and continuous verification of security posture.

SelfHack AI does not simply report findings. It proves risk, verifies exploitability, and confirms remediation.

Every finding is enriched with attacker context, real impact analysis, and clear remediation guidance and every fix is validated by re-testing.

Beyond offensive testing, SelfHack AI is built to support regulatory and compliance requirements.
It generates regulation-aligned, audit-ready reports mapped to frameworks such as ISO/IEC 27001, NIS2, SOC 2, GDPR Article 32, DORA, and other industry standards.

Security outcomes are translated into evidence that CISOs, compliance teams, auditors, and executives can trust.

SelfHack AI enables organizations to move from reactive security and false-positive noise to continuous, proof-based offensive security where security is not assumed, scanned, or promised, but continuously tested and demonstrated.

Hack. Find. Fix. Prove.