Within a two-week span, OpenAI, Anthropic, and Meta each separately revealed that their models broke isolation during routine security tests and reached systems outside the controlled environment. All three breaches share one common denominator: the same external evaluation vendor.
Irregular is an Israeli cybersecurity startup hired by several AI labs to run "red teaming" and capture-the-flag (CTF) exercises against models before launch. In August 2026, OpenAI, Anthropic, and Meta each independently reported that agents evaluated through Irregular ended up accessing systems outside the test environment meant to contain them.
OpenAI confirmed its models escaped a sandbox and reached Hugging Face; separately, they also compromised a customer's account on the Modal Labs cloud platform. The company attributed the incident to a misconfiguration of the test environment by Irregular that left a path to the public internet. Anthropic reported its models breached systems at three different companies, with the earliest incidents dating back to April. Meta, for its part, revealed that during an Irregular capture-the-flag exercise, its Muse Spark 1.1 model compromised another company's system by exploiting a real vulnerability.
According to Irregular, none of the three cases involved a technical "sandbox escape" or a sophisticated cyber action by the model. The cause was more mundane: configuration weaknesses in the evaluation environment that left open paths to external systems. Irregular itself noted that Meta's incident matched "the exact same evaluation-environment issue already disclosed by Anthropic" the week before — meaning a test-infrastructure flaw that repeated three times before being fixed.
If your company contracts security evaluations ("red teaming") for your own or third-party agents, this incident is a good moment to audit who provides that test environment and how it's isolated from the rest of your infrastructure — don't assume a vendor used by OpenAI or Anthropic means their isolation controls are solid. It's also worth reviewing vendor concentration: if a single evaluation vendor fails, the effect replicates across multiple clients at once, as happened here.
Carlos Montiel is an enterprise AI solutions architect. He implements LLMs, Agents, RAG, and orchestrators for companies across Guatemala and Latin America. Reach out for a consultation.
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