mirror of
https://github.com/wiltodelta/remove-ai-watermarks.git
synced 2026-10-14 21:40:47 +02:00
Victor Kuznetsov
07b07634cf
* 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
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OpenAI SynthID oracle ladders
This page is a routing hub. The mixed 2026-08 campaign log was split by purpose on 2026-08-22. Numeric tables now live on the page for that purpose. Raw images stay gitignored under
.local-eval/synthid/prc-oklab-attack-2026-08-15/.Seeds s1, s2, s3 are listed in SynthID local detector research.
| Page | Use it for |
|---|---|
| SynthID local detector research | Hunt for a keyless local mark detector. Open. Closed routes on that page. |
| AI-generated image classifiers | Primary metadata-free AI-generation task, Model 1 partial result, and frozen-checkpoint sweep. |
| SynthID source classifiers | OpenAI/Gemini source finding and pipeline_lattice as google-lineage. |
| SynthID mark removal research | Quiet-remover hunt. Closed except ~19-24 dB 16-32 scramble and blur sigma 7. |
| Mechanism reference | How SynthID works, provenance, robustness, regeneration. |
| Chronological plan archive | Dated H-gates, corpora, and session notes in original order. |
Where former sections went
| Former heading | Now |
|---|---|
| 2026-08-21 pairs, flats, L1 labels | detector |
| Identity, token/layout, tomography, preprocess E1 | detector (presentation gate) |
| L1 repair, L1 geometry, camera vs edit pair, E3 | detector |
| CLIP-L photo vs AI, provider CLIP, union | AI classifiers, source classifiers |
| 124-d three-class and binary AI | source classifiers |
pipeline_lattice re-check, Spaces census |
source classifiers |
| Attack / kill / flip / add / surround ladders | removal |
| 16-32 titration, E2 scramble, Bayer and geometry | removal |
S4 provider split, M2 Imagen addWatermark, reverse-SynthID, Bypass |
detector |
Photo d' budget 13.4 dB, 128-photo student, 16-32 residual without flat G |
detector |
| OKLab codeword replacement, add-context as presentation | removal |
| Three-class OpenAI / Gemini / photo ask | source classifiers |
| Wild hypotheses 2026-08-23 (sort, CDMA, bispectrum, PRNU, affine 16-32 NCC no lock) | detector |
Wild oracle 2026-08-23: misnamed polar-1632 is cartesian scramble replicate not_detected; band-transplant not_detected; palette64 detected |
removal |
| External literature 2026-08-23 (Gowal, AWPD, PRC, Zhao, UnMarker, CtrlRegen, MarkNull, reverse-SynthID) | detector, removal, AI classifiers |
| Adjacent literature, not SynthID (Cox, HiDDeN, StegaStamp, Tree-Ring, Ojha CLIP, Corvi Fourier, DCCT CFA, PRNU PCE) | detector, AI classifiers, removal |
| Image investigation and data hiding (LSB, UNIWARD, Baluja, HiNet, Gaussian Shading, ELA, JPEG ghosts, DIRE, CNNDetect) | detector, AI classifiers |
| Waveforms in a picture (DFT, Fourier-Mellin, Zernike, chirps, Fresnel, DRPE, cyclostationary) | detector |
| Remaining hypotheses 2026-08-23 (CFA, JPEG ghost, Paeth, face-gate, Baker, Poisson, nested LSB, angular scramble) | detector, removal, AI classifiers |
| Non-local 2026-08-23 (HEIF/AV1 survive, print-scan sim 24.95 dB still detected, gpt-image-1.5/mini encoder-off, dated gpt-image-2 same stamp, DIRE DDIM texture) | detector, removal, AI classifiers |
| Waveform shells 2026-08-23 (Mellin/Zernike/PCET/Fresnel no photo lock; Y scramble kills, chroma and 90° sector do not; radial-phase kills) | detector, removal |
Public decoder sweep 2026-08-23/24 (Rinne414 fixed templates 0/400 on current OpenAI/Google images; injected template spoofs the public correlator, but 0.25-2x subtraction stays official detected at 43.13-25.72 dB) |
detector, removal |
Public CNN sweep 2026-08-24 (newideas99 retains 172/200 OpenAI but accepts 110/200 Google; a whole-frame gradient makes the ensemble effectively zero but stays official detected through ±8/255 / 34.30 dB) |
detector, source classifiers, removal |
reverse-SynthID V4 repeat 2026-08-24 (77/200 Google and 76/200 OpenAI at the published cut; Round-06 manual Gemini verdicts are not published as per-image evidence) |
detector, source classifiers, removal |
| Broad GitHub sweep 2026-08-24 (133 unique primary repositories; REGRET and the vordme flat-field SVM fail the strict v7 transfer; literal ports and generic heuristics add no signal) | detector, source classifiers |
Additional public removal sweep 2026-08-24 (DeSynth stays official detected; froggeric and other ControlNet/diffusion projects corroborate lossy regeneration; PortOS closes high-fidelity phase/noise jamming) |
removal |
Google verifier surfaces 2026-08-24 (retired Vertex imageverification@001; live but unlisted and inaccessible synthid.googleapis.com/upload/v1:verifyContent) |
detector |
| Metadata-free source hunt 2026-08-24 (1% cascades rejected; frozen multiscale fusion found 276/600 OpenAI-or-Google targets, 0/1,000 photographs and 1/25 TC260 on blind v4) | source classifiers |
| Original-export source hybrids 2026-08-24 (frozen v7 215/400 exact; post-hoc v8 292/400 and per-codec v11 316/400 exact) | source classifiers |
| Frozen general-detector transfer 2026-08-24 (Community Forensics and SPAI do not replace or safely fuse with Model 1 at the 1% calibration FPR; B-Free weights unavailable and license noncommercial) | AI classifiers |
| General-classifier GitHub sweep 2026-08-25 (2,006 unique repositories found; DDA and PGC expose complementary frozen signals, but DDA raises independent FPR and PGC's OpenAI gain confounds 24/24 Kodak scans; DGS-Net, SAFE, RINE, and Nonescape Mini rejected) | AI classifiers |