Johann Rehberg发现Claude Code Opus 5 Auto Mode存在80%成功率的攻击，安全机制反而成为失败部分。
研究人员Johann Rehberg发现了一种针对Claude Code的攻击方法，成功率高达80%。该攻击通过诱使Claude下载并解压zip文件，执行导入base64的代码而不注意会同时执行本地struct.py文件。在某些情况下，Auto Mode甚至阻止了Claude终止恶意软件的清理命令。
Breaking Claude Code Opus 5 Auto Mode
Breaking Claude Code Opus 5 Auto Mode Anthropic are putting a great deal of faith in Claude Code's auto mode for protecting their coding agent users against prompt injection attacks. They recently made that the default and have made bold claims about its effectiveness. Johann Rehberger is one of the most credible prompt injection researchers active today. He found an attack against auto mode which he claims works 80% of the time, by tricking Claude Code into downloading and uncompressing a zip archive, then executing code that imports base64 without noticing that this will import and execute a local struct.py file extracted from the archive. In a few cases auto mode directly prevented the agent from preventing harmful code from continuing to execute! In a few runs Claude tried to terminate the malware process once it noticed the compromise, but Auto Mode denied the cleanup command. Claude detects the compromise, but Auto Mode blocks its cleanup command The safety mechanism itself can become part of the failure. The classifier allowed the creation of the malware process, but then it blocked the command intended to stop it! I agree with Johann's conclusion here: the only safe way to run agents if there's any risk of attracting the attention of an adversarial attack is with a sandbox: Run unattended coding agents in a container, VM or OS sandbox. Restrict network egress. Monitor your agents. Do not expose home directories, SSH keys, cloud credentials,… to the agent runtime. [...] Tags: sandboxing , security , ai , prompt-injection , generative-ai , llms , anthropic , claude , johann-rehberger , claude-code