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67ebe4834463894205636d2c0834a79d7caa25fe
- Add time import for sleep() function - Add default_gmail_api_scope variable before use in gmail_api config - Initialize clients dict with retry loop before processing (lost in merge) - All 10 ruff linter errors resolved (F401 unused imports, F821 undefined names)
fix: OSD Global-tenant import + dropped report files with glob metacharacters; validate dev stack on OpenSearch 3.x with PostgreSQL (#781)
fix: OSD Global-tenant import + dropped report files with glob metacharacters; validate dev stack on OpenSearch 3.x with PostgreSQL (#781)
fix: OSD Global-tenant import + dropped report files with glob metacharacters; validate dev stack on OpenSearch 3.x with PostgreSQL (#781)
fix: OSD Global-tenant import + dropped report files with glob metacharacters; validate dev stack on OpenSearch 3.x with PostgreSQL (#781)
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 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, an HTTP webhook, or Google SecOps (Chronicle) in UDM format via API or stdout
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) |
Description
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Python
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Shell
1.7%
