Hello HN,

I’m a solo developer who realized that in high-conflict divorce cases, the party with the most organized data wins. Forensic accountants charge $400/hour to trace assets, which makes financial justice inaccessible for many.

I built Exit Protocol to automate this. It’s a forensic intelligence tool that ingests PDF bank statements and uses the Lowest Intermediate Balance Rule (LIBR) (See v. See, 1966) to mathematically separate marital funds from separate property.

My very first post: https://news.ycombinator.com/item?id=46350044

The "Defense-Grade" Features (v2 Update):Realizing my users are often under digital surveillance by a spouse, I overhauled the security model to be "adversarial-ready":

-Protocol 0 (Anti-Coercion): I implemented a "Duress Password." If a user is forced to unlock their device, entering this secondary password loads a fully functional "Decoy Dashboard" (a generic budgeting app) with fake data, hiding the forensic evidence.

-Deposition Killer: A feature that cross-references financial transactions with text message timestamps to find contradictions (e.g., User texts "I have no money" on Tuesday -> System flags a $5k Casino withdrawal on Wednesday).

-Sovereign Architecture: For law firms, the system supports a "Bring Your Own Key" (BYOK) model where the entire stack runs in an air-gapped Docker container.

Stack:

-Backend: Django 5.0 (Monolith)

-Queue: Celery + Redis (for parsing 1,000+ page PDF discoveries)

-Logic: Custom Python implementation of LIBR tracing algorithms

-Security: Fernet (AES-256) encryption at rest

Try the Simulation (No Login Required): I know HN hates sign-up walls, so I built a "Live Tactical Simulation" (link in the footer) that pre-loads a fake case ("Operation Sterling") so you can play with the Asset Graph and LIBR engine immediately without registering.

I’d love feedback on the Duress implementation specifically. Is a decoy dashboard enough, or should it trigger a silent nuke of the local session storage too?