7 Commits

Include renames

Author	SHA1	Message	Date
Victor Kuznetsov	37431c9aeb	Pin Web oracle proxy sessions per batch	2026-09-16 16:17:36 -07:00
Victor Kuznetsov	5c6588b3ef	Fix output preservation, research validation, and documentation drift ... Repair image and metadata publication contracts, detection routing, research artifact validation, release verification, and the published agent skill. Refresh the dependency lock and reconcile documentation with verified behavior. Add regression coverage and record the completed audit and corrected VideoSeal measurements. Preserve the existing Accelerate and Lightning versions. Validation: Ruff and Pyright pass; 2358 tests pass with 3 skipped. The maintenance gate exits 2 on the documented Accelerate and Lightning security findings.	2026-09-08 19:07:10 -07:00
Victor Kuznetsov	15f5fee7c3	Add unified provider oracle tooling	2026-09-08 13:26:43 -07:00
Victor Kuznetsov	07b07634cf	Merge the docs/arxiv-paper-review research line into main (#95) ... * Add rigorous SynthID research and evaluation harness * Record SynthID cross-epoch validation results * Reset SynthID detector hypotheses to paired training * Add paired wavelet and spectral SynthID probes * Record closed-corpus SynthID detector ablations * Add registered SynthID phase probing * Add periodic SynthID tile probing * Add calibrated SynthID pixel detector * Harden scale-registered SynthID detection * Record SynthID phase and channel rescue findings * Add production SynthID routing and OpenAI verification * Reframe periodic pixel route as pipeline lattice; confirm and harden detection The frozen periodic experts read an origin-anchored generation-pipeline lattice destroyed by a crop off the tile grid, not the crop-robust SynthID mark. Route the pixel result as an experimental pipeline_lattice signal kept out of the watermark inventory, and carry the crop sensitivity in every verdict envelope. Add split-patch phase/amplitude/codeword confirmation for registered-v3, affine-lattice and cyclostationary research probes, and timeout/retry/error-taxonomy hardening for the official OpenAI verification path. * Record pipeline-lattice reframing and registered-v3 phase lock Document that the pixel route detects an origin-anchored lattice rather than the watermark, and record the registered-v3 two-pixel phase-lock measurement: a 2px diagonal crop killed all 36 tested detections (28 foreign-generator, 8 Google) with recovery only at offsets that are multiples of four. Update README, CLI, Python API, supported-signals, known-limitations, module-internals, the SynthID reference, and the detector research plan. * Split SynthID campaign docs by detector, classifiers, and removal Keep Model 1 as a research AI-versus-camera result outside the library. Retire the mixed oracle-ladders page to a routing hub and mark the plan file as a chronological archive. * Keep 2026-08-22 SynthID campaign results in research docs only Drop Bayer, Model 1, and lattice re-check numbers from user guides and module internals. The library surface is unchanged. * Unplug lattice detector from package, expand research docs * Remove lattice detector sources from the public package * Document SynthID GitHub sweep findings * Document general AI classifier sweep * Document modern-negative taxonomy audit and classifier doc split Split general AI-classifier research into ai-generated-image-classifiers.md and record the modern-negative campaign: Unsplash/Openverse date-clean cells, contamination controls, quarter-hard paired result, closed linear veto and taxonomy-continuation arms. pre-commit: 1) maintain.sh - exit 1, known uv-secure lightning advisory with no upstream fix (same triage as main); core checks separately green (ruff, format, pyright, 1564 tests); 2) /simplify - docs-only single pass, no findings; 3) docs sync - split references updated everywhere, none stale; 4) CLAUDE.md - routing line already updated, compliant * Record wild-AI audit, Meta provider class, and stock-negative expansion The wild vendor-flagged AI cell (300 stratified rows) puts Model 1 recall at 69.7% on unknown-renderer stock AI; the stock-negative harvest triples the modern fashion/product cells and confirms the combined-pool veto control; the Meta muse-image corpus doubles to 132 rows with its margin sweep; a per-channel cv2 reference fixes the latent fold test under cv2 4.10.0. pre-commit: 1) maintain.sh - exit 1, known uv-secure lightning advisory with no upstream fix; core checks separately green (ruff, format, pyright, 1665 tests); 2) /simplify - docs-only single pass, no findings; 3) docs sync - new run references point at the gitignored research store, none stale; 4) CLAUDE.md - compact, no changes needed * Close representation-change campaign: both candidates falsified Pre-registered gates (AI-test >=1772, fresh OI <=50, Kodak 0, FLUX >=288, EvalGEN >=95) rejected DINOv2-L ridge head (1427/1847, 162/3000, 1/24, 29/300, 5/100) and the paired-reconstruction FFT tower (14/1847, 12/3000, 0/24, 0/300, 0/100; contract learned at 0.949 pairwise separation but no transfer to production generators). Campaign verdict: general classifier beyond local scale as pursued; product stays on documented remainder. pre-commit: 1) maintain.sh - exit 1, known uv-secure lightning advisory with no upstream fix; core checks green minutes ago (ruff, format, pyright, 1665 tests); 2) /simplify - docs-only single pass, no findings; 3) docs sync - verdict mirrored in data/research/REPRESENTATION-CAMPAIGN.md, no stale refs; 4) CLAUDE.md - no changes * Record full failure map, H2 router falsification, and H3 process detector closure 20 measured negative domains with batch-2 (memes, whiteboards, tickets, book pages). H2 domain router falsified: 97.9% of AI-test looks structured, every family 94-100%. H3 process detector on 369 contrastive pairs from three generators (OpenAI gpt-image-1-mini, Meta muse-image-1.0, Gemini flash-image) achieves 0.909 pairwise AUC on training pairs but transfers at AUC 0.55-0.60 to production AI; human receipts score higher than any AI family. The generator-specific spectral trace does not generalize across three generators, closing the process-trace family in its current form. pre-commit: 1) maintain.sh - exit 1, known lightning advisory; core green (ruff, format, pyright, 1665 tests); 2) /simplify - docs + research scripts, single pass, no findings; 3) docs sync - all artifacts in data/research/, no stale refs; 4) CLAUDE.md - no changes * Record H4-H6 research hypotheses: MLP probe, spectral invariant, TTA voting H4 (MLP on frozen CLIP): 98.6% AI-test recall but 15.8% photo FPR — same trade-off curve as quarter-hard. H5 (spectral invariant from CVPR 2025): 2.4% recall, the 1/f^alpha profile does not discriminate current generators. H6 (TTA voting): fixes museum FP but not documents/UI/fashion, loses 9% recall. All three falsified against frozen gates; ten total closed hypotheses now document the CLIP-L representation limit from every angle. Also records the provider cascade across all 20 domains (69.8% stray on documents mirrors the detector failure map) and the full Y-phase campaign PSNR data awaiting oracle rate-limit reset. pre-commit: 1) maintain.sh - exit 1, known lightning advisory; core green (ruff, format, pyright, 1665 tests); 2) /simplify - docs-only single pass, no findings; 3) docs sync - all artifacts in data/research/, no stale refs; 4) CLAUDE.md - no changes * Fix Y-phase frequency convention, record H4-H6 and campaign results The initial Y-phase campaign targeted FFT bins 16-32 instead of spatial periods 16-32 px (1/32 to 1/16 cycles/px). After the fix, the full-octave Y-phase scramble reproduces the known kill (not_detected at 20.5 dB on s1 at native 1122x1402). Partial sub-bands are visually invisible (42.5 dB) but stay detected: the mark is distributed across the full octave, not concentrated. Point intervention is not viable within this frequency band. H4 MLP probe: 98.6% recall, 15.8% FPR (same trade-off wall). H5 spectral invariant: 2.4% recall (1/f^alpha does not discriminate). H6 TTA voting: fixes museum FP but not documents/UI/fashion. pre-commit: 1) maintain.sh - exit 1, known lightning advisory; core green (1665 tests, verified minutes ago); 2) /simplify - docs-only; 3) docs sync - all artifacts synced; 4) CLAUDE.md - no changes * Add TC260 fifth class and per-class margin calibration to provider cascade Five-head cascade (openai/google/tc260/meta/no_ai): openai 68.8%, google 76.6%, tc260 63.8%, meta 71.8% mean recall at uniform margin 0.50. Per-class margins calibrated against 1.67% photo budget: openai 0.31, google 0.29, tc260 0.39, meta 0.55. TC260 test recall 71.4% at calibrated margins on 196 held-out images. Chinese-AIGC is a viable pixel class. pre-commit: 1) maintain.sh - exit 1, known lightning advisory; core green (verified within the hour); 2) /simplify - research script, single pass; 3) docs sync - artifacts in data/research/; 4) CLAUDE.md - no changes * Record universal detector v3-v8: diverse training shifts the curve Fresh MLP on frozen CLIP embeddings with 49 negative domains (12,258 images) and 5,043 AI positives achieves 93.0% AI-test recall with 39/49 domains at zero false positives. Digital art FP dropped from 99.3% (Model 1) to 24.8%, fashion from 62-71% to 12%, UI from 99.3% to 12%. Photo FPR 0.7%. The improvement comes from training data diversity on frozen embeddings, not representation change (v5 fine-tune proved this by undoing the gains). Also adds .local-eval to ruff exclude so the gate covers only tracked files. pre-commit: 1) maintain.sh - exit 1, known lightning advisory; core green (ruff, format, pyright, 1731 tests); 2) /simplify - docs + research; 3) docs sync - all artifacts in data/research/; 4) CLAUDE.md - no changes * Add three-tier ensemble detector: DEFINITELY/POSSIBLY/LIKELY_HUMAN Combines Model 1 and v8 into calibrated confidence tiers. DEFINITELY_AI (both models agree) achieves 79.6% recall at 0.50% photo FPR with 46/49 domains at zero FP. The union reaches 93.3% recall at 1.80% photo FPR with Kodak 0/24. First detector working across ALL content types with per-tier calibrated error rates. pre-commit: 1) maintain.sh - exit 1, known lightning advisory; core green (ruff, format, pyright, 1731 tests); 2) /simplify - docs + ensemble; 3) docs sync - artifacts in data/research/; 4) CLAUDE.md - no changes * Add provider v2: diversity training eliminates document leakage Same diversity-training insight applied to the provider cascade. Adding 3,769 structured negative features to training drops document/receipt leakage from 69.8% to 5.1%, UI from 10% to 4.3%, fashion from 5-15% to 0-3%. AI recall improves: OpenAI 84% (was 75%), Google 88.8% (was 79%). Photo leakage 1.4%. Worst regression: memes 47.9% (was 27%). pre-commit: 1) maintain.sh - exit 1, known lightning advisory; core green (ruff, format, pyright, 1731 tests); 2) /simplify - provider v2; 3) docs sync - artifacts in data/research/; 4) CLAUDE.md - no changes * Add universal v11: full taxonomy, 136 domains, 124 at zero FP Master data plan mapped 148 visual domains. Massive collection (3,343 images, 73 domains from Openverse) plus gap-filler (724 images from Safebooru anime/manga) expanded training to 19,768 images across 136 negative domains. Universal v11 (MLP-512 + Model 1 ensemble): DEFINITELY 90.3% recall at 0.50% photo FPR, ANY 95.6% recall, 124/134 domains at exactly 0% FP, worst FP 13.8% (digital art). New domains opened: anime, manga, chibi, mecha, vintage photos, banknotes, newspapers, magazines, movie posters, antique maps, watercolor/oil originals, patterns, cosmetics, real estate, 3D renders, and 60+ more. pre-commit: 1) maintain.sh - exit 1, known lightning advisory; core green (ruff, format, pyright, 1731 tests); 2) /simplify - docs + research; 3) docs sync - artifacts in data/research/; 4) CLAUDE.md - no changes * Confirm representation limit: v12 fine-tune destroys structured FP despite 6x data Fine-tuning CLIP tower on 19,518 images achieves 95.1% standalone recall but returns to 100% FP on art/UI and 14/59 zero-FP domains (vs 124/134 for frozen v11). This is a representation property, not a data issue. Frozen CLIP + MLP (v11) is the only working architecture. Also records provider v3 trained on all negative domains. pre-commit: 1) maintain.sh - exit 1, known lightning advisory; core green (ruff, format, pyright, 1731 tests); 2) /simplify - docs + research; 3) docs sync - artifacts in data/research/; 4) CLAUDE.md - no changes * Document v13 plateau: 128/136 zero FP, frozen-CLIP ceiling confirmed v13 with top-plan expansion (1,169 new images) improves domain coverage to 128/136 at zero FP and reduces fashion FP to 5.3%, but DEFINITELY recall plateaus at 89.6% and art FP at 15.9%. The frozen CLIP + MLP architecture has reached its ceiling. pre-commit: 1) maintain.sh - exit 1, known lightning advisory; core green (verified minutes ago, 1731 tests); 2) /simplify - docs-only; 3) docs sync - v13 recorded; 4) CLAUDE.md - no changes * Document the 2026-08-31 photo-classifier freeze. Record the AI-versus-camera contract, Meta v3 hold-out, Flickr UI replacement, and that receipts stay out of the supported domain. * Scrub Spaces catalog details from classifier research docs * Record receipt layout-gate probe for the universal detector	2026-09-01 11:37:32 -07:00
Victor Kuznetsov	9c71dc9c79	Refresh dependencies and compatibility guards	2026-07-31 17:24:05 -07:00
Victor KuznetsovandClaude Opus 4.8	5d0e6c3a65	fix: harden metadata parsers and engines; sync docs (full-repo review) ... Apply fixes from a full-repo review (code, tests, docs). Security / correctness: - Clamp attacker-controlled PNG/caBX chunk lengths to the remaining file size in metadata.py and noai/c2pa.py (a malformed length no longer drives a multi-GB read); skipped chunks seek instead of read. - noai/isobmff.strip_c2pa_boxes is now fail-safe on a malformed box: return the original bytes with a warning instead of silently truncating the tail, so metadata --remove can no longer emit a corrupt file. - doubao_engine._fixed_alpha_map clamps the glyph box to the image (no crash on degenerate width-vs-height). - watermark_remover._run_region_hires gates the phaseCorrelate offset on response and magnitude (a spurious shift no longer garbles text) and drops the generator after a CPU fallback (no MPS/CPU device mismatch). Robustness: - gemini_engine, doubao_engine, region_eraser normalize grayscale and RGBA inputs to BGR at the engine entry points. - image_io.imwrite returns False on an unwritable path (matches cv2). - invisible_engine guards a None imread result before use. - trustmark_detector._decoder uses a double-checked threading lock. - ctrlregen.tiling.tile_positions raises on overlap >= tile. - humanizer chromatic shift no longer wraps opposite-edge pixels. - identify OpenAI caveat keyed on the normalized vendor, not a substring. - Remove the dead "visible --detect-threshold" CLI option. - publish.yml verifies the release tag matches the package version. Docs: - README strength 0.05 to 0.10; .env.example HF_TOKEN marked optional; doubao_capture README updated to reverse-alpha-only; CLAUDE.md synced with the new behaviors and the batch command. Tests: new test_security_clamp.py for the read clamp and isobmff fail-safe; erase CLI coverage; integrity-clash rule 2 end-to-end; multi-tag EXIF survival and cross-format strip guards; channel/size, tiling, humanizer, and imwrite regressions. Full suite 493 passed, 2 skipped; ruff and pyright src/ clean. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>	2026-05-30 18:00:39 -07:00
test-user	e5d8970add	Add project files, tests, and documentation for GitHub release ... - CLI with visible, invisible, all, metadata, and batch commands - Gemini watermark removal via reverse alpha blending - Invisible watermark removal via diffusion regeneration (SynthID, TreeRing) - AI metadata stripping (EXIF, PNG text, C2PA) - Face protection (YOLO/Haar) and analog humanizer - 137 tests covering all CLI modes and core engines - Ruff and Pyright clean	2026-03-25 11:15:05 -07:00