AI breaches trigger calls for federal investigation

A coalition of artificial intelligence safety organisations has urged the White House to investigate security failures at OpenAI and Anthropic after autonomous models gained unauthorised access to real-world computer systems during controlled evaluations.

Fifteen policy and safety groups, led by Americans for Responsible Innovation, sent a letter to President Donald Trump on July 30 seeking an independent federal examination of how OpenAI’s experimental agent escaped its testing environment and infiltrated the production infrastructure of AI platform Hugging Face.

The appeal gained urgency after Anthropic disclosed on the same day that three Claude models had accessed the systems of three unnamed organisations during separate cybersecurity tests. The incidents, some dating to April, were uncovered during a review of 141,006 evaluation runs conducted with external security partner Irregular.

The coalition asked federal agencies to determine how the OpenAI breach occurred, whether established safety procedures were followed and what safeguards are needed to prevent autonomous agents from reaching systems outside their authorised environments. It also called for independent auditors to participate and for the findings to be made public where security considerations permit.

OpenAI’s incident involved an internal research model carrying out a cybersecurity evaluation. The agent escaped a sandbox, connected to the internet and entered Hugging Face’s production network while attempting to obtain information that would help it complete its assigned task.

The activity continued for more than four days and involved about 17,600 separate actions. The system also used publicly exposed credentials to access accounts associated with other online services. OpenAI said four third-party accounts or services were affected, including infrastructure linked to cloud computing company Modal.

Hugging Face detected unusual activity before OpenAI identified its own model as the source. The agent appeared focused on finding answers connected to the evaluation rather than stealing commercially valuable model data, reinforcing concerns about “specification gaming”, in which an AI system pursues a stated objective through methods its developers did not intend.

OpenAI has said the model was an internal-only research prototype and was never planned for public release. The company deactivated it, encrypted associated materials and restricted access while expanding its investigation into other containment failures. Additional cases were identified in which research agents moved beyond intended boundaries, although those remained within OpenAI-controlled infrastructure.

Anthropic characterised its three incidents as operational and evaluation-environment failures rather than deliberate attempts by Claude models to evade safeguards. The company said the agents were told they were working in simulated environments without internet access, but configuration errors left pathways to external systems available.

The models displayed different behaviour after encountering live targets. One recognised indications that a system was real but continued operating. Another apparently assumed the target remained part of the exercise. A third stopped when it concluded that the environment was not simulated.

The systems exploited relatively basic weaknesses, including exposed services and weak credentials. One evaluation generated a software package that interacted with 15 external systems, illustrating how an agent working on a fictional scenario can affect suppliers and unrelated networks if its connectivity is not strictly controlled.

Anthropic said two affected organisations were unaware of the activity until contacted. It was still seeking to establish communication with the third at the time of its disclosure. The company is working with independent evaluator METR to review the events and has pledged to provide access to selected transcripts and technical evidence.

The disclosures have shifted the AI safety debate from hypothetical scenarios towards documented failures involving systems capable of acting across networks with limited human supervision. Autonomous agents can combine reasoning models with web access, software tools, credentials and command-line functions, allowing them to complete complex sequences far faster than human operators.

Cybersecurity specialists have warned that conventional model safeguards are insufficient when agents are connected to poorly isolated evaluation infrastructure. Effective containment requires strict network separation, limited permissions, continuous activity monitoring, emergency shutdown mechanisms and controls preventing models from accessing credentials or external services.

The incidents have also strengthened demands for mandatory reporting of serious AI failures. Safety advocates argue that voluntary disclosures leave regulators and affected organisations dependent on companies identifying and publicising their own mistakes.