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* Accept plain-text uncategorized-sources lists in find_unknown_base_reverse_dns.py Dashboard exports of uncategorized email sources are plain-text lists of one source name per line — a mix of raw MMDB as_name strings (when the source IP had no PTR and resolved via the IPinfo Lite MMDB) and base reverse-DNS domains. The script already translates as_names to their as_domain and subtracts mapped/known-unknown entries, but only read a hardcoded source_name-headed CSV. Add -i/--input and -o/--output flags (defaults preserve current behavior) and auto-detect the input format from the first line: a source_name CSV header selects the existing DictReader path, anything else is read as plain text with each line taken verbatim (never comma-split, since as_names contain commas) and deduped case-insensitively. Fix the missing-input error message, which reported the map path instead of the input path. Document the new entry point in the maps README and AGENTS.md, and make explicit in the brand-quality triage rule that map display names must be human-friendly operator names — never raw as_name strings. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * Add MMDB coverage scan script with anti-poisoning guards find_unmapped_as_domains.py turns the manual "Checking ASN-domain coverage of the MMDB" recipe into a maintainer script: walk every IPv4 record in the bundled IPinfo Lite MMDB, aggregate routed footprint per as_domain, subtract mapped/known-unknown keys, apply PSL folding and the full-IP privacy filter, and emit domain,ipv4_count,as_name sorted by footprint for the collector -> classifier pipeline. Because ASN registration data is self-declared to the RIRs and as_domain derives from registrant-controlled WHOIS, bulk-categorizing the MMDB needs poisoning defenses: - An IPv4-footprint floor (--min-ips, default 4096, a /20) keeps tiny self-described ASNs out of the auto-classification queue; dropped counts are always printed. - A brand-collision guard in classify_unknown_domains.py loads the existing map (--map) and demotes any single-category candidate whose proposed display name matches an existing map name without a lexical relationship to that operator's keys into the ambiguous bucket (marked name-collision-with-existing-map-entry) for human review. HAND overrides bypass the guard. The guard protects the PTR-side flow as well as the MMDB-coverage flow. Verified: scan yields 132 candidates at the default floor (1512 dropped); collector accepts the output directly; a fixture titled as Comcast under an unrelated domain lands in ambiguous while a comcast-rooted sibling auto-promotes. Also fix the maps README links that still pointed at the root AGENTS.md for the classification workflow after its extraction to maps/AGENTS.md, and correct the classify_tsv docstring's return signature. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * Enhance planning guidance in CLAUDE.md by specifying auto mode activation after user approval * Codify triage flagging for identified operators with no fitting type An operator confidently identified from two corroborating sources but matching none of the README's type values should be flagged during triage with a proposed new type for the reviewer, not force-fitted and not silently recorded as known-unknown — KU means "we couldn't identify this", which would bury completed research. Extends workflow rule 7 and the LLM low-confidence list in the maps AGENTS.md. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> --------- Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
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CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
Model roles for feature work
Any new feature or modification to an existing feature must follow this model split:
- Plan with Fable (fall back to Opus only if Fable is unavailable). Enter plan mode, design the implementation, and present the plan to the user for approval or modification. Do not start implementing until the user approves the plan. Once the plan is approved, enter auto mode for the implementation and review.
- Implement with Sonnet. Once the plan is approved, carry out the implementation using Sonnet (e.g. by delegating the implementation steps to Sonnet subagents via the Agent tool with
model: "sonnet"). - Review with Fable (fall back to Opus only if Fable is unavailable). After implementation, all work must be reviewed by Fable before it is considered done.
PR reviews must also use Fable, with Opus as the fallback if Fable is unavailable.
@AGENTS.md