A Python module and CLI for parsing aggregate DMARC reports
Project description
pasedmarc is a Python module and CLI utility for parsing aggregate DMARC reports.
Features
Parses draft and 1.0 standard aggregate reports
Transparently handles gzip or zip compressed reports
Consistent data structures
Simple JSON or CSV output
Python 2 and 3 support
CLI help
usage: parsedmarc.py [-h] [-f FORMAT] [-o OUTPUT]
[-n NAMESERVER [NAMESERVER ...]] [-t TIMEOUT] [-v]
file_path [file_path ...]
Parses aggregate DMARC reports
positional arguments:
file_path one or more paths of aggregate report files
(compressed or uncompressed)
optional arguments:
-h, --help show this help message and exit
-f FORMAT, --format FORMAT
specify JSON or CSV output format
-o OUTPUT, --output OUTPUT
output to a file path rather than printing to the
screen
-n NAMESERVER [NAMESERVER ...], --nameserver NAMESERVER [NAMESERVER ...]
nameservers to query
-t TIMEOUT, --timeout TIMEOUT
number of seconds to wait for an answer from DNS
(default 6.0)
-v, --version show program's version number and exit
Sample output
Here are the results from parsing the example report from the dmarc.org wiki. It’s actually an older draft of the the 1.0 report schema standardized in RFC 7480 Appendix C. This draft schema is still in wide use.
parsedmarc produces consistent, normalized output, regardless of the report schema.
JSON
{
"xml_schema": "draft",
"report_metadata": {
"org_name": "acme.com",
"org_email": "noreply-dmarc-support@acme.com",
"org_extra_contact_info": "http://acme.com/dmarc/support",
"report_id": "9391651994964116463",
"begin_date": "2012-04-27 20:00:00",
"end_date": "2012-04-28 19:59:59",
"errors": []
},
"policy_published": {
"domain": "example.com",
"adkim": "r",
"aspf": "r",
"p": "none",
"sp": "none",
"pct": "100",
"fo": "0"
},
"records": [
{
"source": {
"ip_address": "72.150.241.94",
"country": "US",
"reverse_dns": "adsl-72-150-241-94.shv.bellsouth.net",
"base_domain": "bellsouth.net"
},
"count": 2,
"policy_evaluated": {
"disposition": "none",
"dkim": "fail",
"spf": "pass",
"policy_override_reasons": []
},
"identifiers": {
"header_from": "example.com",
"envelope_from": "example.com",
"envelope_to": null
},
"auth_results": {
"dkim": [
{
"domain": "example.com",
"selector": "none",
"result": "fail"
}
],
"spf": [
{
"domain": "example.com",
"scope": "mfrom",
"result": "pass"
}
]
}
}
]
}CSV
xml_schema,org_name,org_email,org_extra_contact_info,report_id,begin_date,end_date,errors,domain,adkim,aspf,p,sp,pct,fo,source_ip_address,source_country,source_reverse_dns,source_base_domain,count,disposition,dkim_alignment,spf_alignment,policy_override_reasons,policy_override_comments,envelope_from,header_from,envelope_to,dkim_domains,dkim_selectors,dkim_results,spf_domains,spf_scopes,spf_results draft,acme.com,noreply-dmarc-support@acme.com,http://acme.com/dmarc/support,9391651994964116463,2012-04-27 20:00:00,2012-04-28 19:59:59,[],example.com,r,r,none,none,100,0,72.150.241.94,US,adsl-72-150-241-94.shv.bellsouth.net,bellsouth.net,2,none,fail,pass,,,example.com,example.com,,example.com,none,fail,example.com,mfrom,pass
What about forensic DMARC reports?
Forensic DMARC reports are emails with an attached email sample that failed a DMARC check. You can parse them with any email message parser, such as mail-parser.
Very few recipients send forensic reports, and even those who do will often provide only the message headers, and not the message’s content, for privacy reasons.
Installation
parsedmarc works with Python 2 or 3, but Python 3 is preferred.
On Debian or Ubuntu systems, run:
$ sudo apt-get install python3-pipPython 3 installers for Windows and macOS can be found at https://www.python.org/downloads/
To install or upgrade to the latest stable release of parsedmarc on macOS or Linux, run
$ sudo -H pip3 install -U checkdmarcOr, install the latest development release directly from GitHub:
$ sudo -H pip3 install -U git+https://github.com/domainaware/parsedmarc.gitDocumentation
Bug reports
Please report bugs on the GitHub issue tracker
Release history Release notifications | RSS feed
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