Quoting Greg Kroah-Hartman

📰 Simon Willison's Blog

AI-generated security reports have improved significantly, now providing high-quality and accurate reports for open source projects, which is a crucial development for the industry

intermediate Published 3 Apr 2026
Action Steps
  1. Monitor AI-generated security reports for open source projects
  2. Evaluate the quality and accuracy of these reports
  3. Integrate AI-generated reports into existing security workflows
  4. Configure tools to automate the review and prioritization of AI-generated reports
  5. Test the effectiveness of AI-generated reports in identifying security vulnerabilities
Who Needs to Know This

Security teams and open source project maintainers can benefit from this development, as it can help them identify and address potential security vulnerabilities more efficiently

Key Insight

💡 AI-generated security reports have improved significantly in quality and accuracy, making them a valuable tool for security teams and open source project maintainers

Share This
🚨 AI-generated security reports have gone from 'slop' to superb! 🚨

Key Takeaways

AI-generated security reports have improved significantly, now providing high-quality and accurate reports for open source projects, which is a crucial development for the industry

Full Article

Months ago, we were getting what we called 'AI slop,' AI-generated security reports that were obviously wrong or low quality. It was kind of funny. It didn't really worry us. Something happened a month ago, and the world switched. Now we have real reports. All open source projects have real reports that are made with AI, but they're good, and they're real. &mdash; <a
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