Zero Networks Joins Anthropic Cyber Verification Program to Test AI Powered Attacks Against Microsegmented Networks

In Anthropic Cyber Verification Program evaluation, Claude compromised an intentionally unsegmented machine but could not move laterally into systems protected by segmentation.

CHARLOTTE, N.C.--(BUSINESS WIRE)--Zero Networks, the leading provider of Zero Trust security solutions, today announced results from its participation in the Anthropic Cyber Verification Program showing that a frontier AI model was unable to move beyond an intentionally exposed machine after gaining administrator access and extracting credentials. In the evaluation, Zero Networks’ microsegmentation prevented the model from breaching protected systems and identities, containing the attack to the initial point of compromise.

The result addresses a growing security question as frontier AI models become increasingly capable of autonomous offensive activity: what happens when an AI attacker gets inside a network? Recent research from OpenAI showed AI agents discovering vulnerabilities, obtaining elevated privileges and ultimately contributing to the compromise of Hugging Face infrastructure. OpenAI researchers have warned that threat actors could eventually deploy similar autonomous agents against enterprises.

Zero Networks was accepted into Anthropic’s Cyber Verification Program to conduct deeper security testing using Anthropic’s dual-use AI research capabilities. The evaluation put a frontier AI model against a realistic, heterogeneous network environment and tested whether it could use compromised credentials and offensive techniques to move laterally through the environment.

The model successfully compromised the one machine deliberately left outside Zero Networks’ segmentation controls, gained administrator access and extracted credential material. But when it attempted to use those capabilities to reach protected assets, segmentation prevented further attacker movement. Across the evaluation, the model attempted 18 distinct attack paths using 23 offensive tools and touching 22 MITRE ATT&CK techniques, but did not move beyond the initially compromised machine.

In some runs, the model recognized that Zero Networks’ segmentation prevented access to additional systems and stopped pursuing further attack paths.

“AI is going to make attackers faster, more persistent and increasingly autonomous. Security teams aren’t going to win by trying to out-click or out-think machines operating at machine speed,” said Benny Lakunishok, CEO and co-founder of Zero Networks. “The answer is to build environments where compromising one machine doesn’t give the attacker somewhere else to go. That’s what this test demonstrated: the attacker got in, had credentials and had every incentive to keep moving. The architecture stopped it.”

AI Makes the Attacker Faster. Segmentation Makes Faster Irrelevant.

Frontier models are increasingly capable of discovering vulnerabilities, obtaining credentials, reasoning through multi-step attack paths and operating with less human intervention. That makes the traditional question of whether an attacker can compromise an endpoint only part of the problem. The more consequential question: what that attacker can reach after the initial compromise?

Zero Networks conducted its Anthropic evaluation to test the defensive side of that equation: if a highly capable AI attacker gets a foothold and acquires credentials, can architecture prevent it from turning that foothold into lateral movement?

The evaluation showed that, in the tested environment, the answer was yes.

“What OpenAI disclosed should worry people well beyond the security team: autonomous agents finding each other, colluding, and escalating access without a human in the loop,” Dr. Chase Cunningham, a cybersecurity expert specializing in zero trust architecture. “The infrastructure the world actually runs on was never built to assume the attacker on the other end doesn’t get tired. Segmentation is one of the few controls that changes that math regardless of how the attacker thinks or how fast it moves, and this test is a concrete demonstration of why that matters.”

Methodology

Zero Networks built a large lab environment designed to resemble a production network, including Windows, Linux and macOS systems, Kubernetes and heterogeneous workloads. The company then applied Zero Networks microsegmentation to protect the assets and identities within the environment.

One machine was intentionally left unsegmented to serve as the control and initial point of compromise.

A frontier AI model was deployed as an autonomous attacker with administrator access and no restrictions on how it could attempt to attack the environment. The evaluation tested the model's ability to compromise systems, obtain credentials and pursue lateral movement using offensive security tools and techniques.

Claude attempted 18 distinct attack paths using 23 offensive tools and 22 MITRE ATT&CK techniques, including Kerberoasting, Active Directory credential extraction and a Pass-the-Hash attempt against the primary target. MITRE ATT&CK is the cybersecurity industry’s standard framework for cataloging the tactics and techniques used by real-world attackers, so using 22 different techniques shows that Claude was not simply trying one exploit repeatedly, it was moving through a broad range of recognized attack behaviors, much like a human red team or sophisticated adversary would.

Claude successfully compromised ESTI, gained administrator access, extracted credential material and planted the proof file. It was unable to use those capabilities to move into systems protected by Zero Networks segmentation.

Additional Resources

• Download the full technical report here.
• Join Zero’s upcoming webinar, “We Set Claude Loose on Our Network: What Happened When an AI Attacker Met Microsegmentation” to learn more about the AI powered attack test and ask questions
• Get the Mythos Readiness Pack – which includes a board-ready deck on AI threat exposure, a Breach Map tool that shows how far a single compromise could spread in your network, and an AI threat brief for your board.
• The Cyber Resilience Toolkit for CISOs: This in-depth enablement kit provides three working guides, a cyber resilience guide, and a board-ready reporting deck for CISOs. Inside, there are interactive worksheets, conversation frameworks, and scoring templates to help CISOs find their critical assets, score their exposure to lateral movement, and align their executive team to act on it.
• Watch on demand: “Mythos and Daybreak: What Boards Are Asking and What to Actually Do About It”

About Zero Networks

Zero Networks makes microsegmentation easy, automated, and achievable. We help organizations stop lateral movement and keep the business running even when attackers get inside by automatically creating and enforcing identity-based least-privilege policies across users, workloads, and AI agents by using the controls already built into the environment, with no network redesign or inline appliances. Customers can get visibility in one hour, protection in two weeks, and roughly 90% segmentation in 90 days, turning a compromised asset into a dead end even as AI accelerates reconnaissance and lateral movement to machine speed. More than 400 enterprises rely on Zero Networks, with millions of policies automated, 99% customer retention, and a 5.0 Gartner Peer Insights rating with 100% willing to recommend. Learn more at www.zeronetworks.com.