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How much of F-Droid is LLM generated?

A FOSS maintainer manually graded 102 F-Droid apps from the September 12, 2026 update batch, finding many show signs of LLM-generated code.

A student and FOSS app maintainer reviewed 102 apps pushed to F-Droid on September 12, 2026, assigning each a three-tier rating for likelihood of LLM-authored code (mostly AI >50%, hard to say/mostly human, no signs of AI). The heuristic relies on commit aesthetics, README and branding style, and the presence of agentic infrastructure like Claude Code or Codex, which automatically places an app in the 'mostly AI' tier. Example ratings include Amber (Nostr event signer) as mostly AI, and Aria for Misskey as showing no AI signs. The author stresses reliable detection of LLM-generated code from text alone is impossible, so ratings are approximate.

Hacker News · AISep 15, 09:47 UTC · 2d agoAI research HN 46↑ · 23 comments

An AI CAPTCHA solver talked itself out of the right answer

Bern researchers solved rotation CAPTCHAs in 0.006 seconds with classical computer vision, while Gemini 3.1 Pro needed 67 seconds and overruled correct tool answers.

Researchers at Bern University of Applied Sciences built a script using 1970s circle-detection math and signal matching that solved rotation CAPTCHAs in 0.006 seconds, scoring 10/10 on real-world puzzles. Frontier models fared poorly: Gemini 3.1 Pro scored 7/10 taking 67 seconds, while GPT-4o and Grok scored 1/10. When given the script's correct answer as a tool, Gemini overruled it and lost a fifth of its score; models could verbally describe targets, such as identifying a cyan ring, but could not produce accurate click coordinates. The paper also notes these no-JavaScript CAPTCHAs reduce tracking, leaving only shape-matching tasks classical vision solves easily.

Help Net SecuritySep 2, 00:00 UTC · 15d agoAI research1