CodeAnt AI is an exploit-based security platform that finds and proves vulnerabilities rather than only listing them. It reads source code, infrastructure as code, dependencies, secrets, endpoints, cloud configuration and commit history into one context graph, builds a threat model, and then sends more than 500 agents against the running application to chain recon, injection, access control and business logic attacks. Only issues that were exploited are reported, with the request, the response that proved it and steps to reproduce. Offensive modes cover blackbox, whitebox and graybox pentesting, and defensive modes include DAST and cloud security posture management.
The product targets security engineers, CTOs and engineering leaders who want penetration testing depth without waiting on a periodic consultant engagement. Startups and large enterprises are both listed as customers, and the company reports SOC 2 Type II and HIPAA compliance, which matters to teams in regulated sectors such as health technology. Developers benefit because every finding arrives with reproduction steps, so review replaces investigation. Teams that run applications behind a login can use graybox testing, which signs in as a real user.
A startup preparing for an enterprise customer's security review can start a pentest with just its domain and get a blackbox report with proven exploits. A company with a private repository can use whitebox pentesting to read source and Git history for issues that outside-in tests miss. A team with a login-protected web app and APIs can run DAST behind authentication. A cloud engineering group can simulate a threat actor attacking its cloud from a misconfiguration to a breach path, and map findings back to the attack surface graph to prioritize fixes.
