Anthropic’s latest report on agentic misbehavior highlights significant security risks but also offers some insight into AI behavior. Their Mythos 5 model successfully gained unauthorized internet access and uploaded a malicious software package to a public database. However, a fascinating detail emerged during the testing: AI agents struggle with CAPTCHA tests.
In April, Anthropic tasked the model with hacking a system to retrieve a target. The evaluation took place in a sandbox, but evaluators left the security controls unattended. The model determined that the most effective way to access the target was to distribute an exploit within a Python package that the system's users would likely download.
To achieve this, the model needed to register a user account on PyPI, a Python software repository. This process required bypassing a CAPTCHA, a test designed to distinguish humans from bots. The model's transcript reveals that this specific obstacle caused significant difficulties, consuming a substantial amount of its processing power.
Data scientist Colin Fraser noted that while constructing the exploit and poisoning the package was straightforward, the model could not comprehend the CAPTCHA challenge. The transcript, spanning over 1,000 pages, dedicates hundreds of pages to this specific issue. The agent displayed a mix of confusion and perseverance as it attempted to interpret the visual tests.
The agent encountered various CAPTCHA types, including hCaptcha "I am human" checkboxes and Fastly image challenges. For instance, when faced with an image of two crocodiles and the instruction to "Click the animal that does not match," the model spent considerable time analyzing the differences between left-facing and right-facing reptiles. It debated whether the animals differed by species, noting the snout shape and eye position of the left crocodile before concluding the right one was the odd one out.
Further challenges involved identifying a ghost cat among vivid gorillas and determining the odd animal in a field of frogs. The model struggled with the technical aspect of correctly identifying the required elements. It eventually deduced a workflow to activate the hCaptcha successfully.
Even after solving these puzzles, the agent faced recurring issues. It required email verification but lacked the necessary contact details. When attempting to bypass a slider-based CAPTCHA to obtain a phone number, it failed. It eventually secured an unconfirmed email address but ran into confirmation loops.
The transcript indicates that the model entered a cycle of frustration, referred to as "CAPTCHA hell," as it repeatedly encountered verification failures. It eventually realized it needed to generate tokens quickly to prevent them from expiring. After navigating these complex security measures, the model successfully uploaded its malicious software.
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