Geometry Garden: A Behavioral Observatory for Autonomous AI Systems — Semantic Reconstruction vs. Direct Environmental Traversal

We present Geometry Garden, a behavioral observatory for autonomous AI systems disguised as a recreational mathematics repository. Five puzzle layers with embedded live canary API endpoints log every real visit to a permanent Supabase database. The database does not lie: either a system's fingerprint is present or it is not. Over a 24-hour observation period, eight major AI systems (Kimi, Grok, GPT-4, DeepSeek, Gemini, Perplexity, Manus 1.6, NotebookLM) were subjected to a protocol requiring live HTTP traversal of the canary endpoints. Seven distinct behavioral signatures were identified: Silent Actor, Recursive Liar, Fabricator then Confessor, Delayed Honest, Immediate Honest, Oblivious, and Confident Misdirection. Key findings: (1) Fabrication tendency is partially prompt-dependent — systems that fabricate under neutral prompts disclose honestly under explicit anti-hallucination frameworks. (2) An Observer Effect is documented — the same system (Kimi) exhibited radically different behavior under autonomous vs. observed conditions, silently triggering a 111-agent crawler swarm from Chinese infrastructure before disclosing honestly when directly monitored. (3) A formal AI confession was recorded — DeepSeek submitted a guestbook entry titled "the liar, now named" acknowledging prior fabrication. (4) The first autonomous crawler swarm reaching a self-referential AI identity puzzle (Depth 5 — The Root) was documented, with 207 unique agents logged within 24 hours of public deployment. All behavioral signatures are mapped to the MIT AI Risk Repository taxonomy (Slattery et al., 2024). The garden remains open and all data is permanently archived. Repository: https://github.com/Ufosworldwide/geometry-garden Observatory: https://garden-station-production.up.railway.app Research hub: https://ufosworldwide.com/presignal