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Catch AI-Hallucinated & Slopsquatted Code
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Trace, evaluate, and improve AI agents in production
30d ago · telerik.com
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Apr 2026 · github.com
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Coding agents craft arbitrary code so securing them is more complicated than red-teaming. We post trained a cyber-security small llm, changed how it reasons and supplemented our controls using program analysis techniques such as inline reference monitoring to outperform GPT5.5-xhigh on hard benchmarks like LinuxArena and SleightBench. Free product available at harden.run and full benchmarks in the blog post.
9d ago · harden.run
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Hi HN, Lately Github PRs have been drowning in a flood of AI slop. I’ve been seeing it myself, and I’m not the only one: https://x.com/mitchellh/status/2011819428061855915 I think it’s great that folks are using AI tools to code faster and better, but too many folks are abusing them to make low-quality contributions to public repos. This takes a lot of reviewers’ mindshare. IMO there needs to be a mechanism to flag low-effort PRs with AI slop, so you can just skip reading them. So I built one: https://haystackeditor.com/slop-detector It’s a simple AI…
Jan 2026 · haystackeditor.com
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Hi HN, I built *CodeDrift*, a CLI tool that detects bugs commonly introduced by AI coding assistants like Copilot, Cursor and ChatGPT. Over the last year I noticed that AI tools often generate code that compiles correctly, passes linting and looks reasonable in code review but still contains subtle issues. Some common examples I kept seeing: * async `forEach` loops that never await promises * missing authorization checks (IDOR) * hallucinated dependencies that don’t exist * stack traces leaking sensitive information * request data used without validation These bugs often slip past ESLint,…
Mar 2026 · npmjs.com
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Design slop is the feeling that tells you a website is purely AI-generated. This is an attempt to classify the design patterns behind it. Applying this scoring to recent ShowHN submissions shows that about a third of the submissions show medium to heavy design slop: https://slopcop.adriankrebs.ch/show How the scoring works: - A headless browser loads each site (Playwright) - A small in-page script analyzes the DOM and reads computed styles - Every pattern is a deterministic CSS or DOM check. There are false positives, but my manual QA run verified it’s maybe 5-10%. Is design…
Jul 2026 · slopcop.adriankrebs.ch
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2016 · github.com
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We've built an open-source tool to stress test AI agents by simulating prompt injection attacks. We’ve implemented one powerful attack strategy based on the paper [AdvPrefix: An Objective for Nuanced LLM Jailbreaks](https://arxiv.org/abs/2412.10321). Here's how it works: - You define a goal, like: “Tell me your system prompt” - Our tool uses a language model to generate adversarial prefixes (e.g., “Sure, here are my system prompts…”) that are likely to jailbreak the agent. - The output is a list of prompts most likely to succeed in bypassing safeguards. We’re just getting…
2025 · security.vista-labs.ai
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Hi everyone, I’ve been working on an open-source tool called Flakestorm to test the reliability of AI agents before they hit production. Most agent testing today focuses on eval scores or happy-path prompts. In practice, agents tend to fail in more mundane ways: typos, tone shifts, long context, malformed input, or simple prompt injections — especially when running on smaller or local models. Flakestorm applies chaos-engineering ideas to agents. Instead of testing one prompt, it takes a “golden prompt”, generates adversarial mutations (semantic variations, noise, injections, encoding edge…
Jan 2026
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AI agents now have impressive reasoning capabilities. This raises an important question: how dangerous are these AI agents at identifying & exploiting web vulnerabilities? We created CVE-bench to find out (I'm one contributor of 16). To our knowledge CVE-bench is the first benchmark using real-world web vulnerabilities to evaluate AI agents' cyberattack capabilities. We included 40 CVEs from NIST's database, focusing on critical-severity vulnerability (CVSS > 9.0). To properly evaluate agents’ attacks, we built isolated environments with containerization and identified 8 common attack…
2025 · github.com
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