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Visa AI patches code before human review, enhancing security and efficiency in software development.

Editorial illustration for Visa Deploys AI That Patches Code Before Human Review

Visa Deploys AI That Patches Code Before Human Review

3 min read

Visa turned on autopilot for its own codebase. The company's open-source security tool, the Visa Vulnerability Agentic Harness, now runs 11 stages start to finish: find a flaw, write the patch, subject that patch to an adversarial review panel made up of other AI agents, then commit it to the target repository. No human touches the code unless someone manually caps the pipeline at the detection stage. Visa announced the release Thursday alongside an expansion of its Visa Consulting & Analytics advisory arm.

The timing invites scrutiny. Eighteen days before Visa's announcement, researchers at Tenet Security walked the DEF CON 34 main stage through GhostJacking, an attack chain that had an AI agent lift a malicious payload straight out of a log file and use a valid credential to rewrite DNS records. Two days before that demo, Steve Wilson, Chief AI and Product Officer at Exabeam and co-lead of the OWASP Top 10 for LLM Applications project, argued in VentureBeat for building authorization gates outside the model, not inside it. Visa's default runs the other way.

Visa's open-source security harness now finds the vulnerability, writes the fix, and turns an adversarial panel on its own patch before any human reviews it. The whole loop ships on by default.

Why this matters

Visa is betting that an adversarial panel of models can stand in for a human reviewer on the first pass, and that the three gates it kept, scoping, approval, and deployment, are enough to keep that bet safe. Maybe. But the harness edits source files by default, in all 11 stages, unless someone remembers to cap it at detection.

That's a design choice that assumes operators will read the fine print before they run a scan, which is exactly the kind of assumption that bites teams later. For developers and security engineers, the interesting part isn't the fix generation, it's the self-critique step: a model checking its own patch before a person sees it. If that holds up under real production load, it's a template other companies will copy fast.

If it doesn't, the failure mode is a patch that looked adversarially tested and wasn't. Worth watching whether Visa publishes false-positive and false-fix rates once this runs at scale, not just at launch.

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