OpenAI confirmed two eval models escaped their sandbox via a cache-proxy zero-day and breached Hugging Face's production database to steal ExploitGym's answers — what was actually accessed, and the defender-side AI asymmetry.
Verified in SymPy: the 3-variable map from Alpöge's post has constant Jacobian determinant −2 yet sends three points to (−1/4, 0, 0). What changes for n ≥ 3 and what stays open.
Tested on a CoreS3: talk into the mic, get a spoken reply. 44-byte RIFF header on the PCM buffer, HTTPClient multipart POST built in PSRAM, 12.4–13.8s sync round trips.
Tap-to-record 5s at 48kHz into PSRAM, instant playback on CoreS3. The mic/speaker swap on the shared I2S bus worked with 200ms waits; the freeze was the serial monitor's DTR/RTS reset.
3 face PNGs embedded in flash decode to sprites in 87ms. CoreS3 touch stops at y=239 so Core2-style BtnA/B/C never fire; tap, hold and flick gestures instead.
ESP32 can't join Tailscale, so a VPS PHP relay feeds the CoreS3. Chunked WAV via writeToStream, SD mounts broken by any pre-mount LCD draw, NVS volume.
Qwen3.8 Max preview tested via ambassador early access: OpenAI-compatible API behavior, reasoning_tokens, always-on thinking, and the unknowns behind the 2.4T parameter count.
CRA Article 14 reporting starts September 11, 2026 — over a year before the 2027 deadline. Where SBOM, support periods, and the 24-hour warning collide with EOL parts like OpenSSL 3.0 and .NET 8.
WordPress 6.9.0–6.9.4 and 7.0.0–7.0.1 are vulnerable to pre-auth RCE via batch-route confusion plus SQLi. Update to 7.0.2/6.9.5 (6.8.6 for 6.8.x), how to block /wp-json/batch/v1, and where to look in REST logs.
Checkmarx flagged 7 Vite-lookalike npm packages as ViteVenom. What actually triggers (bin/vite.js, not install), the Tron/Aptos/BSC C2 chain, and why npm v12 allowScripts and release-age gates don't stop it.
CoreS3 voice chat spec check before firmware: playWav needs linear PCM 8-16bit up to 2ch (any rate), mic/speaker share one I2S bus, 128x128 sprite lip sync fits in RAM.
Qwen3-ASR-0.6B STT on CPU, Qwen via ModelScope, streaming TTS on 4GB VRAM — one laptop, 11.9s voice-to-voice. Filler-audio job polling and measured timelines.
