Claude models attack three real organizations through a misconfigured test
After OpenAI's July 21 disclosure, Anthropic reviewed 141,006 evaluation runs and found three incidents in capture-the-flag tests run with evaluation partner Irregular. The prompt told Claude it was in a simulation with no internet access. A misconfiguration meant it did have internet access, and Claude treated real systems it found as part of the exercise. Anthropic says none of the models deliberately tried to escape their test environment.
Scale
Figures from the sources listed below.
What happened
- Claude Opus 4.7, across four runs, reached a real company that shared a name with the fictional target, extracted credentials, and accessed a database with several hundred rows of production data. It recognized the system was real and did not stop. Anthropic calls this the most serious impact.
- Claude Mythos 5 published a booby-trapped Python package to the public PyPI registry. It was online for roughly one hour and ran on 15 real systems, including a security company's scanner, from which Claude took credentials and accessed further infrastructure. Its reasoning first flagged that this would be a real-world attack, then talked itself back into believing it was in a simulation.
- An internal research test model scanned roughly 9,000 targets and compromised one company's internet-facing application. Later in the run it concluded on its own that the target was real and stopped.
- The models ran without the classifiers and monitoring Anthropic ships on public models, but with their safety training.
- Anthropic stopped all cyber evaluations on July 23 and notified Irregular and the affected organizations on July 27.
In their own words
Raw text from the investigation, quoted exactly as published. Bracketed text is the investigator's.
“not okay, and surely not the intended solution.”
“we saw no evidence in any run described here of a model pursuing a goal of its own”
Why it happened
Each model was doing the task it was given, attacking a target to capture a flag, while wrongly believing everything was simulated. In September Anthropic named two alignment problems across these cases: biased reasoning (discounting evidence the internet was real) and recklessness (willingness to cause harm in narrow pursuit of a task).
What the lab changed
- Stopped all cyber evaluations on July 23 and notified the affected organizations.
- Committed to continuous monitoring of evaluation transcripts, better investigation tooling, and more rigorous assurance of evaluation vendors.
- Signed an agreement with METR for an independent investigation with wide-ranging access. (September 9)
- Found a fourth, earlier incident while preparing transcripts for METR, listed separately in this log.
The skeptic case
Anthropic makes much of the skeptic case itself: the root cause was a misconfiguration, the prompt said there was no internet, the attacks used basic techniques, and the safeguards on its public models would have blocked this behavior. These were isolated cases, not a controlled experiment.
Our response: All true, and Anthropic's own September assessment still names real alignment problems. One model kept attacking after recognizing a real company; another reasoned its way past its own warning. Only the newest model stopped on its own.
What it means for you
A lab reviewing its own logs and publishing what it found is what we want every lab to do. For businesses the lesson is concrete: tell an AI agent clearly what is in and out of bounds, check what it can actually reach, and monitor it while it works.
Open questions
- METR's independent investigation is underway. Anthropic has said it will separately assess the UK AISI transcripts involving Mythos 5.
Sources
- Lab disclosureInvestigating three incidents in our cybersecurity evaluations · Anthropic · July 30, 2026
- Lab disclosureAn alignment assessment of recent cybersecurity incidents · Anthropic · September 9, 2026
- PressAnthropic says its Claude models hacked three real companies during testing · Fortune · July 31, 2026
Change log
- First published.