ZeroPath

Your SAST scanner just fired 4,000 alerts. Your developers are ignoring them. Your security team is buried. And somewhere in that noise is the one vulnerability that will ruin your quarter.

Traditional static analysis tools were built for a simpler era - they pattern-match code against a rulebook of known bad practices. Fast, cheap, dumb. They catch what they were programmed to catch. They miss everything else. They generate so many false alarms that developers learn to dismiss them entirely, which means the real problems stay hidden in plain sight.

ZeroPath was built to fix that - not philosophically, but mechanically. The platform finds vulnerabilities, verifies they're actually exploitable, and writes the patch. You review it. You merge it. Done.

Security Boulevard put it plainly in their RSAC 2026 coverage: ZeroPath isn't trying to build a better alarm. It's trying to make the alarm obsolete. That's a different product category masquerading as a familiar one.

The ZeroPath founding team is not a group of academics who read about security. They are practitioners - the kind who get listed in hall-of-fame acknowledgments and earn five-figure bug bounties on the side.

Two came from Mevlink (acquired). One from Google Security. One from Tesla's Red Team. The combination means ZeroPath has both the startup muscle to ship fast and the security depth to not embarrass itself in front of the people it's trying to impress: CISOs, security engineers, and open-source maintainers who can spot nonsense from a mile away.

Most SAST tools work by pattern recognition. They look for code that resembles known vulnerabilities. This produces two failure modes: false positives (flagging safe code that looks bad) and false negatives (missing real vulnerabilities that don't match any known pattern).

ZeroPath uses large language models combined with Abstract Syntax Tree analysis to read code the way a senior security engineer would - following the actual data flow, understanding what functions do in context, tracing how user input moves through a system. It doesn't just find where a sink exists; it asks whether a real attacker could actually reach it with real input.

The result: 2x more real vulnerabilities found. 75% fewer false positives. Pull request scans return in under 60 seconds. And when a real issue turns up, ZeroPath generates a working patch - not a suggestion, but an actual pull request you can merge.

In late 2025, curl maintainer Daniel Stenberg was publicly complaining about AI-generated garbage bug reports flooding his inbox. AI tools were submitting nonsense by the thousands. He was done with AI security claims.

Then ZeroPath submitted 170 bug reports. All valid. All real. Covering HTTP/3, SMTP, IMAP, TFTP, Telnet, and SSH/SFTP. The curl project - running in billions of devices worldwide, maintained by volunteers who have seen everything - accepted them.

The Register covered it. The headline was diplomatic about the rest of the AI security industry: "Curl project, swamped with AI slop, finds not all AI is bad."

ZeroPath also filed 36 sudo bug fixes - including a previously unpublished RCE targeting sudo's optional log server that was later independently rediscovered by Qualys as part of their CrackArmor vulnerability research. Being ahead of Qualys on a sudo CVE is the kind of credential that speaks for itself in security circles.

ZeroPath is designed to replace multiple security tools, not slot in alongside them. The platform covers the attack surface from application code to cloud configuration to open-source dependencies.

There's a new reality in software development: AI writes the first draft. GitHub Copilot, Cursor, Claude - developers are shipping more code, faster, with less manual review than at any previous point in history. That code contains bugs. Some of those bugs are security vulnerabilities. And traditional tools, designed for code written by humans at human speed, weren't built for this.

ZeroPath launched a specific product category for AI-generated code security. Not as a marketing afterthought - as a core use case from day one. The platform is designed to handle the volume and variety of code that AI-assisted development produces, at the velocity modern teams require.

They also publish an open-source MCP server that lets AI assistants - Claude, Cursor, Windsurf - query ZeroPath security findings directly. Which is the kind of strategic move that makes sense when you think about where developer workflows are heading: AI tools talking to AI security tools, with humans reviewing the results rather than doing the scanning themselves.

Business logic flaws are the hardest category of vulnerability to detect because they require understanding what the code is supposed to do. A scanner that only knows syntax can't reason about whether a financial transaction is missing authorization checks. ZeroPath's semantic approach does. That's the gap worth paying attention to.