if you or someone you know is in this situation right now

you are not stupid. you were targeted by a professional operation. this page exists so the next person has somewhere to start — on synthetic reference data only.

// reference investigation

miranda-pig-butchering — long-con investment scam

Miranda met David Chen on Hinge, moved to WhatsApp, and was groomed over four months into depositing $148,000 on fake TaiKun Capital USDT staking. Test withdrawal built trust; tax-hold scam triggered realization. On-chain deposits trace to Tornado Cash. Fully synthetic.

what this proves

  • all eight pig-butchering primary engines produce deterministic, fixture-locked output — verified by npm run check:flagship (40/40 fleet · 8 for this scenario).
  • every output is generated 100% locally in your browser — chat exports and wallet data never upload.
  • grooming timeline, fake-platform screenshot bursts, ETH deposit decode, and mixer-adjacent graph surface without sending evidence to a server.

primary engines locked to this fixture

build the case binder

runs all eight primary engines on the synthetic evidence zip and opens a self-contained html binder — 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 ChatStorage.sqlite, Hinge export, photos burst sqlite, ETH/BTC traces, and wallet csv.

built deterministically from scripts/fixtures/build-miranda-pig-butchering.mjs. seed: miranda-pig-butchering:v1.

methodology

long-con scams are chat + chain — export WhatsApp first, screenshot the fake platform, then walk deposits through decoders and graph tools. read the full pig butchering / long-con investment scam guide →

after the playbook

export findings from all eight primaries — chat, screenshots, deposits, graph — then run them through fatcousin-multi-tool-super-timeline-correlator. grooming, fake-platform burst, and drain events on one local timeline — no upload.

synthetic scenario only · no real victim · no real funds · grading rubric

ready