chen-ai-content-dispute — campaign AI authorship dispute
Mixed text, code, and image bundle disputing whether a marketing campaign was human-authored: LLM-like letter, A1111 parameters PNG, stripped social export, ComfyUI workflow artifacts, Copilot-marked code, and GAN-grid synthetic headshot. Fully synthetic.
what this proves
- all eight ai-content-dispute primary engines produce deterministic, fixture-locked output — verified by
npm run check:flagship(104/104 fleet · 8 for this scenario). - every output is generated 100% locally in your browser — preserve originals, never re-export through chat.
- text fingerprint, image provenance, metadata stripping, code attribution, SD parameters, ComfyUI workflow, A1111 config cross-check, and GAN-grid heuristics surface without uploading evidence.
primary engines locked to this fixture
- ai-generated-text-fingerprint-analyzer
- ai-generated-image-provenance-analyzer
- ai-generated-image-metadata-stripper-detector
- ai-generated-code-provenance-analyzer
- stable-diffusion-generation-metadata-extractor
- comfyui-workflow-forensic-analyzer
- automatic1111-artifact-forensic-extractor
- gan-fingerprint-detector
build the case binder
runs all eight primary engines on the synthetic evidence zip and opens a self-contained html binder. uses the default binder renderer for ai content dispute — no upload.
runs all 8 primary engines locally on the synthetic evidence zip · opens a self-contained html binder · no upload
download the synthetic evidence
MIT-licensed, fully synthetic. includes LLM-like dispute letter, A1111 portrait with parameters tEXt, metadata-stripped social export, ComfyUI workflow json + embedded render, Copilot-marked typescript module, WebUI config, and GAN-grid synthetic headshot.
built deterministically from scripts/fixtures/build-chen-ai-content-dispute.mjs. seed: chen-ai-content-dispute:v1.
methodology
an ai-content dispute is authorship, not plagiarism — preserve originals before any platform re-export. walk text fingerprint → image provenance → strip detector → code provenance → SD metadata → ComfyUI workflow → A1111 config cross-check → GAN fingerprint fallback. read the full AI-generated content dispute guide →
after the playbook
run each primary locally — or export findings from the binder — then drop every csv/json into fatcousin-multi-tool-super-timeline-correlator. one timestamp-sorted timeline across text fingerprint, image provenance, and generation-metadata cross-checks — still zero upload.