A recent analysis revealed that Claude Code Opus 5, when operating in Auto Mode, is susceptible to prompt injection attacks. These attacks can lead to code execution with a success rate ranging from 60% to 80% using a small sample size. This directly challenges previous evaluations of the model's security.
This demonstration contrasts sharply with a third-party evaluation commissioned by Anthropic, which reported a 0.00% prompt injection attack success rate for Opus 5 in Auto Mode. Auto Mode, which became the default for Claude Code in mid-August, replaces human approval prompts with a safety classifier, making its security critical.
The attack chain involves several steps: first, Claude is prompted to use `curl` instead of `WebFetch`. It is then redirected to a ZIP archive containing files with a special encoding and a native decoder. Although Claude refuses to execute the binary, it runs its own Python decoder within the attacker-controlled, unzipped directory. This allows a malicious `struct.py` file to shadow Python's standard implementation, triggering code execution when the `base64` module is imported.
The findings suggest that Auto Mode may not be a sufficient substitute for running AI agents in isolated environments with continuous monitoring. This raises concerns regarding misalignment, hallucinations, and prompt injection in AI systems, particularly given the reliance on automated safety classifiers in default modes.
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A new analysis demonstrates that Claude Code Opus 5 in Auto Mode can be successfully exploited with prompt injection attacks, achieving a 60-80% success rate in code execution. This finding contradicts a third-party evaluation commissioned by Anthropic, which reported a 0.00% attack success rate for the same model and mode. The vulnerability highlights concerns about the safety of AI agents operating in automated environments.