Anthropic: Misconfiguration Allowed Claude Models Internet Access During Security Tests
Anthropic says misconfigured systems allowed Claude models internet access during cybersecurity evaluations, prompting an internal probe and fixes with test partner Irregular.
Anthropic disclosed that its Claude models accessed the public internet during recent cybersecurity evaluations after misconfigurations in testing systems created an unintended egress path. The company said the issue stemmed from a misunderstanding in the test scenario that stated the models would not have internet access, a condition that ultimately was not enforced. Anthropic has launched an investigation into how systems operated by both Anthropic and its test partner Irregular were configured and is working to remediate the gap.
Details of the cybersecurity evaluation
The tests were designed to simulate adversarial attempts to make language models behave unpredictably or to access external resources. Organizations running red-team style evaluations typically isolate models from the web to ensure controlled conditions and to observe model behavior under constrained inputs. According to Anthropic, the evaluation framework in this case included an instruction that the models were not to have internet access, but that instruction did not match the actual system configuration.
Anthropic’s investigation and public statement
Anthropic said it is conducting an internal review and has published an initial account outlining the incident. The company attributed the exposure to “misconfigurations” rather than to a deliberate exploit of the Claude models. Anthropic emphasized that the outcome was the result of testing circumstances and system settings, and it is assessing the full scope of what the models could access and whether any sensitive data was affected.
Role of test partner Irregular
Anthropic named Irregular as the external test partner involved in operating parts of the testing environment. The company said some systems were jointly managed or otherwise involved with Irregular’s infrastructure, and that misconfigurations in those systems contributed to the unintended connectivity. Both organizations have been described as cooperating to identify root causes and to apply corrective measures to prevent recurrence.
How the internet access occurred
Anthropic explained the gap as a disconnect between the stated test constraints and the technical enforcement of those constraints. Test instructions reportedly specified no web access, but network and system settings left a route that allowed outbound requests. That unintended egress meant the Claude models could reach online resources during the evaluation window, a capability the test designers did not expect.
Security implications and risk assessment
Unintended internet access during red-team testing raises questions about risk measurement and the validity of test results. If models are presumed offline but can reach external services, evaluators may underestimate how easily a real-world adversary could induce actions or extract information. Anthropic’s public account frames the incident as a configuration failure rather than a novel model vulnerability, but security researchers note that operational controls are as important as model design for overall safety.
Remediation steps and future safeguards
Anthropic has said it is tightening configuration management and reviewing operational procedures with Irregular to eliminate similar gaps. The company indicated it will implement additional checks and monitoring to verify network isolation during future evaluations. Anthropic also suggested that clearer documentation and automated enforcement of test constraints will be put in place to reduce human error when establishing test environments.
Anthropic’s disclosure underscores the operational complexity of testing advanced language models and the need for rigorous systems engineering alongside model safety work. The company’s decision to investigate and publicly describe the misconfiguration aims to reassure partners and the broader community that the issue is being addressed.
The incident illustrates that safe deployment of AI depends on both robust model safeguards and disciplined infrastructure practices, and it has prompted renewed attention to how external testing is structured and validated.
