docs: add design for email unredaction via known email dictionary

Co-Authored-By: Claude Opus 4.6 <[email protected]>

docs/plans/2026-02-16-email-unredaction-design.md

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+# Email Unredaction via Known Email Dictionary
+
+## Problem
+
+Many redactions in the Epstein case files are email addresses, typically enclosed in `< >` angle brackets. Some have a visible `@` splitting the redaction into username/domain sub-gaps. The current solver supports name and word matching but has no email-specific mode.
+
+## Solution
+
+Add a known-email dictionary mode to the solver. Given a pixel-width gap and font/size, scan a list of known Epstein-network email addresses and return any that fit the gap within tolerance, using kerning-aware width computation with the surrounding context characters (typically `<` and `>`).
+
+## Data Sources
+
+Build `unredact/data/emails.txt` (one email per line, lowercased, deduplicated, sorted) from:
+
+1. **Hugging Face `notesbymuneeb/epstein-emails`** — 5,082 email threads (16,447 messages) with sender/recipient fields. Extract unique email addresses from `sender` and `recipients` fields. Parquet format, free download.
+
+2. **Epstein Exposed Black Book API** (`epsteinexposed.com/api/v1/persons`) — ~395 email addresses from the seized address book. Free REST API, no auth, 60 req/min rate limit.
+
+3. **rhowardstone `extracted_entities_filtered.json`** — 357 emails from DOJ document entity extraction. Already used by the project for associates data.
+
+4. **Court-verified (hardcoded)** — 8 addresses from primary court documents:
+   - `[email protected]` (Epstein, Giuffre v. Maxwell Exhibit J)
+   - `[email protected]` (State Dept FOIA)
+   - `[email protected]` (State Dept FOIA)
+   - `[email protected]` (State Dept FOIA)
+   - `[email protected]` (FOIA + Bryant v. Indyke)
+   - `[email protected]` (Bryant v. Indyke)
+   - `[email protected]` (NM State Land Office)
+   - `[email protected]` (Maxwell, court testimony)
+
+### Build Script
+
+`scripts/build_emails.py` — fetches from sources, merges, deduplicates, writes `emails.txt`. Added as `make build-emails` Makefile target.
+
+## Integration
+
+### Backend (`app.py` / `solver.py`)
+
+When solve mode is `"emails"`:
+- Load `emails.txt` into memory (lazy, cached like other wordlists)
+- For each email, compute kerning-aware width: `font.getlength(left_ctx + email + right_ctx) - left_width - right_width`
+- Return matches within tolerance, sorted by width error
+
+This is the same linear-scan approach `dictionary.py` already uses. The left/right context (typically `<` / `>`) is already sent in `SolveRequest`.
+
+### Frontend (`index.html`)
+
+Add `"emails"` option to the solve mode dropdown, alongside `"enumerate"`, `"dictionary"`, and `"both"`.
+
+### No changes needed to:
+- Rust solver (not involved in dictionary-style scans)
+- Width table construction
+- Charset constraints / state machines
+- Font detection pipeline
+- OCR pipeline
+
+## Key Sources
+
+- smw.ai/epstein-files/epstein-email-accounts — verified Epstein email addresses
+- epsteinexposed.com — Black Book API with contact emails
+- github.com/notesbymuneeb/epstein-emails — Hugging Face email threads dataset
+- github.com/rhowardstone/Epstein-research-data — extracted entities