fa905e41fd Keep aggregate identifiers and reasons within their schema (#950)
* Keep aggregate identifiers and reasons within their schema

AI assistance: OpenAI Codex.

* Expand the #948 CHANGELOG entry and tighten its tests

RFC 9990 Appendix A and RFC 7489 Appendix C define only header_from,
envelope_from and envelope_to under identifiers, and only type and
comment in a reason. Cite them in the test, check that envelope_from
and envelope_to survive next to a dropped nested unknown element, and
cover an unknown key on the legacy identities path. The CHANGELOG
entry now names the affected outputs and the compatibility change.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

---------

Co-authored-by: Sean Whalen <44679+seanthegeek@users.noreply.github.com>
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
2026-11-10 13:09:12 -05:00
2018-02-05 20:23:07 -05:00
2026-03-09 18:24:16 -04:00

parsedmarc

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A screenshot of DMARC summary charts in Kibana

parsedmarc is a Python module and CLI utility for parsing DMARC reports. When used with Elasticsearch and Kibana (or Splunk), or with OpenSearch and Grafana, 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 project is maintained by one developer. Please consider sponsoring my work if you or your organization benefit from it.

Features

  • Parses aggregate/rua DMARC reports: the legacy draft and 1.0 schemas (RFC 7489) and the new RFC 9990 schema for the final DMARC standard (RFC 9989)
  • Parses failure/ruf DMARC reports (RFC 6591 and RFC 9991; formerly called forensic reports)
  • Parses reports from SMTP TLS Reporting (TLS-RPT, RFC 8460)
  • 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, Splunk, or PostgreSQL, for use with premade dashboards
  • Optionally send the results to Apache Kafka, Amazon S3, Azure Log Analytics (Microsoft Sentinel), a Graylog (GELF) endpoint, a syslog server, Grafana Loki, or an HTTP webhook

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 ❌ End of Life (EOL)
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)
3.15 ✅ Supported
S
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