SECURITY AND TRUST When AI Accelerates Risk, Defense Must Move Faster

As artificial intelligence accelerates, cyber threats are evolving just as quickly. For defenders, that requires speed, discipline, and a continued focus on resilience.

Why this matters

Visa moves billions of transactions every day. Our network has been hardened over many years through zero trust architecture, layered defenses, and automated security operations and platforms built for the scale and reliability that global payments demand. We joined Project Glasswing, Anthropic’s defensive cybersecurity initiative, to test those defenses at AI speed and better understand where advanced AI can help us go further.

Anthropic’s initial update helps quantify the scale of the shift. Project Glasswing participants identified more than 10,000 high- or critical-severity vulnerabilities across widely used, systemically important software in the first month of testing. Anthropic also said that progress in software security is no longer limited by how quickly vulnerabilities can be found, but by how quickly they can be verified, disclosed, and patched.¹

Testing our defenses at AI speed

To support these efforts, our team developed a multi-model security test suite (now in its fifth generation) built around an advanced scanning harness that systematically maps our codebase, deploys AI agents across our environment to uncover vulnerabilities, categorizes and prioritizes findings, and generates detailed reports for developers and remediation agents. We are making the Visa Vulnerability Agentic Harness available through open source to help advance defensive innovation across the broader community.

Human oversight remains essential at every key point in the workflow. Our security and engineering teams review findings, validate severity, and determine remediation paths before changes are advanced. Patch validation agents then address and validate fixes autonomously, streamlining the process and improving reliability to accelerate expert decision-making, not replace it.

The latest generation of the suite can interpret plain-language objectives, adapt to changes across our systems, and operate continuously without manual script maintenance. This allows our teams operate at a tempo that matches how quickly threats are now discovered, without sacrificing the human judgment that keeps our network resilient.

Three lessons so far

High-fidelity analysis at system scale – The model demonstrated the ability to perform system-wide, intent-aware, and context-aware analysis, producing findings that were high fidelity, low noise, and actionable. Mythos showed particular strength in identifying vulnerabilities deep in the stack and highlighting issues that may become more serious when chained together.

Mean Time to Adapt matters more than time to detect – Finding vulnerabilities is no longer the hard part. The real challenge is how quickly a team can confirm that an issue is truly exploitable, fix it, and then prove the attack path is closed rather than simply showing that a patch was applied. We call this Mean Time to Adapt. We track it by how current our inventory is, how many real attack paths remain after each release, and how quickly we can show that a fix works in production.

Supply chain risk is rising – Supply chain risk matters even more in an AI-accelerated threat environment. Vulnerabilities in open-source and third-party software can quickly become real exposure. Visa is actively engaging in industry efforts such as IBM and Red Hat’s Project Lightwell to strengthen open-source security at scale through AI-driven validation and coordinated patching. In parallel, we are sharpening our focus on vendor security, using vulnerability metrics and exploitability insights to identify where risk is highest and ensure vendors meet the resilience standards required for our technology stack.

What Mythos confirmed

What did Mythos show at Visa? Our defenses held. Some findings were flagged as critical, but our zero trust controls, network segmentation, and existing safeguards would have prevented exploitation. In other words, the kill chain was broken before an external actor could act on those vulnerabilities. It found new vulnerabilities and showed where we can improve, while also confirming that our security foundations, including our zero trust architecture, remain effective and appropriate to the challenge.

What comes next

In a post-Mythos world, the implications go beyond faster discovery. As AI compresses the time between defect creation, discovery, exploit construction, and operationalization, cyber defense will need to evolve from models built around alerts and human triage toward architectures that can reason across signals, apply policy guardrails, and take bounded action at machine speed.

Furthermore, Mythos is not an outlier. Other Frontier models and rapidly advancing alternatives are quickly closing the gap, signaling that these capabilities will become broadly accessible.

Visa’s response is organized around three priorities:

• Reduce the attack surface by shifting security further left in our code and build pipelines, so exploitable vulnerabilities are designed out before they reach production.
• Remove structural dependency on the supply chain by replacing high‑risk, under‑supported open source and commercial components before they turn into material exposure.
• Refactor our defenses to be increasingly autonomous so detection, validation, and response can scale with threat volume and zero‑day sophistication, while staying under clear human governance.

These priorities reflect how Visa sees the future of defensive AI: not simply as a better way to find issues, but as a way to strengthen validation, prioritization, and response within a framework defined by governance and human oversight. The future attacker will not think, operate, or scale like a human, which is why traditional protection mechanisms built on signatures, static posture models, and reactive human response are no longer sufficient. We are addressing this challenge by designing a control plane for AI agents, engineered for autonomous real‑time detection, defense, and containment at AI speed, with resilience built in at every layer and human accountability preserved at every critical decision point.

This shift reinforces a principle that has long guided Visa’s approach to security: resilience must be built in at every layer. Our multilayered security model is designed to detect, prevent, respond, and recover from threats in real time while maintaining the reliability and integrity of our network. As the threat landscape evolves, we are deploying and evaluating advanced defensive AI capabilities to further enhance our security posture and apply those learnings to strengthen protections across the ecosystem we serve.

Attackers are already using these tools. The organizations that move early to deploy defensive AI with this level of discipline will be the ones that hold the line. For Visa, the goal is simple and constant: keep the global movement of money secure for everyone who depends on it.

For a deeper look at Visa's learnings from Project Glasswing, and what this means for cyber resilience, explore the full technical briefing below.