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Sean Whalen
6665a6794c
Adds three pieces of map-maintenance context learned while building this PR: - New subsection "Discovering overrides from the live PSL private-domains section" — distinct source from live DMARC data (unknown_base_reverse_dns.csv) and MMDB coverage-gap analysis. The private section is itself a list of brand-owned suffixes; each is a candidate (psl_override + map entry) pair. Emphasizes ruthless selectivity — most of the 600+ private-section orgs are dev sandboxes or hobby zones that will never appear in DMARC reports. - Two-path coverage as a single linked step, not two round-trips: when adding a PSL override for a hosted-content suffix (netlify.app), also add a map row for the brand's corporate as_domain (netlify.com) in the same pass. The override fixes the PTR path; the ASN-domain alias fixes the ASN-fallback path. - The load_psl_overrides() fetch-first gotcha. The no-arg form pulls the file from master on GitHub, so end-to-end testing of local overrides silently uses the old remote version. offline=True is required to test local changes against get_base_domain(). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
parsedmarc
parsedmarc is a Python module and CLI utility for parsing DMARC
reports. When used with Elasticsearch and Kibana (or Splunk), it works
as a self-hosted open-source alternative to commercial DMARC report
processing services such as Agari Brand Protection, Dmarcian, OnDMARC,
ProofPoint Email Fraud Defense, and Valimail.
Note
Domain-based Message Authentication, Reporting, and Conformance (DMARC) is an email authentication protocol.
Sponsors
This is a project is maintained by one developer. Please consider sponsoring my work if you or your organization benefit from it.
Features
- Parses draft and 1.0 standard aggregate/rua DMARC reports
- Parses forensic/failure/ruf DMARC reports
- Parses reports from SMTP TLS Reporting
- Can parse reports from an inbox over IMAP, Microsoft Graph, or Gmail API
- Transparently handles gzip or zip compressed reports
- Consistent data structures
- Simple JSON and/or CSV output
- Optionally email the results
- Optionally send the results to Elasticsearch, Opensearch, and/or Splunk, for use with premade dashboards
- Optionally send reports to Apache Kafka
Python Compatibility
This project supports the following Python versions, which are either actively maintained or are the default versions for RHEL or Debian.
| Version | Supported | Reason |
|---|---|---|
| < 3.6 | ❌ | End of Life (EOL) |
| 3.6 | ❌ | Used in RHEL 8, but not supported by project dependencies |
| 3.7 | ❌ | End of Life (EOL) |
| 3.8 | ❌ | End of Life (EOL) |
| 3.9 | ❌ | Used in Debian 11 and RHEL 9, but not supported by project dependencies |
| 3.10 | ✅ | Actively maintained |
| 3.11 | ✅ | Actively maintained; supported until June 2028 (Debian 12) |
| 3.12 | ✅ | Actively maintained; supported until May 2035 (RHEL 10) |
| 3.13 | ✅ | Actively maintained; supported until June 2030 (Debian 13) |
| 3.14 | ✅ | Supported (requires imapclient>=3.1.0) |