An Anthropic cyber security evaluation found that a frontier AI model could not move beyond an intentionally exposed machine in a segmented test network, according to Zero Networks. The test examined whether an autonomous AI attacker could turn an initial compromise into wider access across a mixed IT environment. Zero Networks said the model gained administrator access to the exposed machine and extracted credentials, but failed to breach systems and identities protected by microsegmentation, and the attack was contained to the first point of compromise despite repeated lateral movement attempts. Zero Networks took part in Anthropic's Cyber Verification Program, which is designed to test security questions involving dual-use AI models. For the exercise, the company set up a lab intended to resemble a production environment, including Windows, Linux and macOS systems, Kubernetes and other workloads, with one machine deliberately left outside the segmentation controls as the initial target. The AI model, identified by Zero Networks as Claude, was deployed as an autonomous attacker with administrator access and no limits on how it could try to attack the environment. During the exercise, the model attempted 18 distinct attack paths, used 23 offensive tools and touched 22 MITRE ATT&CK techniques, according to Zero Networks, including Kerberoasting, Active Directory credential extraction and a Pass-the-Hash attempt against the main target. Zero Networks said the model successfully compromised the control machine, known as ESTI, obtained administrator access, extracted credential material and planted a proof file, but was then unable to use those gains to reach protected assets elsewhere in the