AI security review on every pull request, with a working exploit attached to each finding

Hacktron's operating principle is borrowed from the disclosure culture its founders come from: proof of concept or nothing. The platform hooks into GitHub, GitLab, or Bitbucket and reviews each pull request as it lands, tracing tainted input through the change and into the surrounding architecture rather than matching patterns within the diff. Where it finds a reachable flaw it attempts to exploit it and attaches the working proof to the finding. That design choice is aimed squarely at the failure mode that has made static analysis unpopular with engineers, which is a queue of theoretical issues nobody can confirm or prioritise, and it changes the triage question from whether the finding is real to how fast it gets fixed.

Around the pull request loop, the platform proposes AI-assisted fixes and opens remediation workflows, runs white-box penetration tests the company says compress weeks of manual work into hours, builds threat models from uploaded design documentation, and produces audit-ready pentest reports. Security rules are customisable and versioned alongside the code, and integrations cover Slack, Jira, Linear, and MCP. Named customers include Perplexity, Supabase, Rocket.Chat, and Gumroad. Hacktron was founded by competitive security researchers Zayne Zhang, Mohan Pedhapati, and Harsh Jaiswal, and raised a $2.9M pre-seed round in May 2026 led by Crane Venture Partners with Project Europe, Vercel Ventures, Plug and Play Ventures, and Cambridge Enterprise Ventures. Pricing is published per developer per month with an enterprise tier.