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待翻译:AI agent suggested installing a malware package. Engineer almost took its advice

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AI 服务暂时不可用,以下为来源摘要,待恢复后补全翻译:AI agent suggested installing a malware package. Engineer almost took its advice Fortunately, the company had a policy of checking source code on GitHub first Avram Piltch Avram Piltch US EDITOR US editor Published thu…

来源Hacker News AI作者: sbulaev
待翻译:AI agent suggested installing a malware package. Engineer almost took its advice
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AI 服务暂时不可用,以下为来源正文,待恢复后补全翻译。

AI agent suggested installing a malware package. Engineer almost took its advice Fortunately, the company had a policy of checking source code on GitHub first Avram Piltch Avram Piltch US EDITOR US editor Published thu 20 Aug 2026 // 08:00 UTC PWNED Welcome back to PWNED, the column where we make fun of those who are security self-owned, so hopefully you don’t do the same. This week, we have a story that’s hot off the presses about a company almost sabotaging its security by using AI for programming. Have a story about someone leaving a gaping hole in their network? Share it with us at [email protected]. Anonymity is available upon request. Our tale of machine learning malfeasance comes courtesy of Sergiy Fitsak, managing director of Softjourn, a consulting and software development company. He reminds us that, when it comes to AI, don’t trust: verify. REG AD During the course of business, one engineer asked an AI agent to recommend a package that they needed for a common task. The agent came back with the name of a legitimate-sounding package, which was formatted like a familiar library. REG AD At many organizations, this would have been the end of the story. The developer would have taken the AI agent’s advice and downloaded and installed the recommended package. However, at Softjourn, the company has a policy which they actually followed: double-check any software recommendations made by AI to make sure they are legit. The developer skimmed the recommended package’s source code on GitHub and noticed that it had few downloads and had just been created a few days earlier. In other words, it was suspicious. According to Fitsak, attackers have found a way to exploit package names hallucinated by AI models. “The problem is that AI models sometimes invent package names that sound plausible but don't exist, a pattern security researchers have started calling 'slopsquatting,'” he told us. “Attackers have caught on and now register real packages under those exact invented names, betting that a developer under deadline pressure will install first and check later.” If Softjourn hadn’t been so careful, they could have installed a malware package. We don’t know the exact payload, but this malware package could have given crims a backdoor into their systems and the ability to steal data or wreak other havoc. “We caught it because we'd already built a habit of verifying download counts and reviewing source code on GitHub before installing anything an AI recommends, even when it looks routine,” Fitsak said. “It takes a few extra minutes. Skipping that step once is how a team ends up explaining a supply chain compromise instead of shipping a feature on time.” MORE CONTEXT Passwords stored in public Google Doc then showed up in search results IT department put sticky notes on the laptops to help employees log in Headteacher had the most guessable username-password combo you could imagine Talking smack about a doctor got him access to private medical files The lesson here is a very simple one: Don’t trust the package names that AI agents recommend. Have a human check the supply chain. And always have a human in the loop so they can take the time to stop and approve any outside code that comes into a project. ®

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  • AI agent suggested installing a malware package. Engineer almost took its advice Fortunately, the company had a policy of checking source code on GitHub first Avram Piltch Avram P…

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