Three scary AI safety errors haunting enterprises

We dwell in a world the place anybody can publish to npm or PyPI, and we’ve seen attackers slip malicious packages into these ecosystems or compromise ones which can be extensively used. A few of the latest incidents have concerned safety and devops instruments themselves pulling a compromised dependency, operating it as a part of CI/CD with elevated privileges, and quietly exfiltrating secrets and techniques or tampering with builds. I personally skilled such a compromise a few months in the past, and needed to replace all of my credentials in GitHub.

Pulling unvetted code is dangerous; now layer AI brokers on prime of that. They default to no matter is best to find and combine. If a package deal solves an issue in entrance of the agent, the agent will add it. That is the previous “obtain a random library from the Web” downside, however now it’s on autopilot, at scale, and shifting at a tempo we’ve by no means seen earlier than.

To unravel this downside, we should present the brokers with an innate sense of our threat tolerance, an authorized elements record, our wishes round logging, and many others. We are able to do that with spec information and what the trade calls constitutions. Collectively, that is referred to as harness engineering, which we’ll discuss extra about later.

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