Files
parsedmarc/docs/source/kibana.md
T
07bca1ad28 Make the output and mailbox integrations optional extras (#888)
* Make the output and mailbox integrations optional extras (#883)

Breaking change for the next major release: pip install parsedmarc now
installs the parsing core plus a working core CLI (file, IMAP, Maildir,
and mbox input; CSV/JSON, Splunk HEC, webhook, and syslog output).
Everything else moves behind an extra: elastic, opensearch, kafka, s3,
gelf, loganalytics, msgraph, and gmail, joining the existing postgresql
extra, with an umbrella [all] that deliberately excludes postgresql
(psycopg's binary wheels do not exist on every platform, so
parsedmarc[all] must never fail to install there).

cli.py imports the six SDK-dependent output modules behind the #884
TYPE_CHECKING/try-except guard; a configured section whose extra is
missing fails fast with a ConfigurationError naming the section and the
exact pip install command — including the msgraph and gmail_api mailbox
sections (detected via parsedmarc.mail's placeholder classes) and
postgresql (checked before the constructor so the startup retry loop
does not retry a missing dependency for a minute). The Azure/kiota Graph
error types fall back to never-raised sentinel classes.

The Docker image installs [all,postgresql], so container users see no
change. CI lint installs [build,all,postgresql]; the unit-test job
installs [build,all], deliberately without postgresql so
test_postgres.py's absent-psycopg arm stays exercised. The
never-imported dateparser dependency is dropped in favor of declaring
python-dateutil, which utils.py actually imports; pytz moves to the
build extra for the one test that uses it.

Verified live: a no-extras wheel install imports, parses samples, and
reports the install hint for each gated section; a [all] install
restores every integration; the Docker image builds with every SDK
importable.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* Patch psycopg presence in the PostgreSQL CLI wiring tests

CI's unit-test job deliberately installs [build,all] without the
postgresql extra, so parsedmarc.cli.postgres.psycopg is None there and
the new missing-extra presence check correctly made _main exit 1 before
the wiring under test ran. The tests simulate the SDK being available
(PostgreSQLClient is mocked at the SDK boundary), so the module-level
psycopg handle is now patched present in setUp. Verified against a
simulated psycopg-absent environment as well as the local full install.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* Address Copilot review: narrow guards to ModuleNotFoundError, fix docs

- The optional-integration and Graph error-type import guards now catch
  ModuleNotFoundError instead of ImportError, so only a genuinely absent
  package reads as a missing extra; a broken-but-present SDK fails
  loudly with its real error instead of masquerading as one. The test
  blocker raises ModuleNotFoundError accordingly — the exact exception a
  missing package produces.
- _missing_extra_hint docstring no longer calls every gated integration
  an output module (it also serves the msgraph/gmail_api mailbox
  sections).
- Fix the pre-existing passsword typo in usage.md's kafka section; the
  INI key the code reads is password (cli.py _parse_config).

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* Quote extras specs in copy-paste install commands

From Copilot's second review round: zsh treats an unquoted .[build,all]
as a glob and fails with 'no matches found', so the commands shown in
AGENTS.md, CONTRIBUTING.md, dashboards/README.md, and the bootstrap
script's comment are now quoted. The CI workflows keep the unquoted
form: they run under bash, which passes unmatched globs through
literally. The suggestion to change the 'Choosing what to install'
heading level was rejected — it is a subsection of 'Installing
parsedmarc', matching the file's existing hierarchy.

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* Fix upgrade command in the changelog

* Documentation review: accuracy, spelling, grammar, and clarity pass

A full prose review of docs/source, README, CONTRIBUTING, and the
dashboards README, with every accuracy claim verified against the code
before changing it. Highlights:

- usage.md: documented six missing [general] options (the CSV/JSON
  filename options, prettify_json, normalize_timespan_threshold_hours),
  the required kafka smtp_tls_topic, [imap] timeout/max_retries, and
  the postgresql env-var prefix; corrected the maildir_path default
  (None, not INBOX — cli.py Namespace defaults), the mailbox
  check_timeout option name, the systemd restart interval (RestartSec
  is 5m), and merged the duplicate silent entry; quoted every
  copy-paste extras spec for zsh safety.
- elasticsearch.md: fixed an invalid openssl command (rsa:4096 -nodes),
  the dashboards filename (opensearch_dashboards.ndjson, matching the
  file the link serves), and assorted grammar.
- davmail.md: the service-enable command now enables davmail.service
  (was parsedmarc.service — a copy-paste error that left DavMail
  unenabled), plus a view typo and DavMail capitalization.
- output.md: the example schema reference is RFC 7489 Appendix C
  (7480 is RDAP). kibana.md: SPF relies on the SMTP envelope, not
  session headers (RFC 7208). dmarc.md: DKM -> DKIM.
- README: the intro now also names the OpenSearch/Grafana stack,
  matching the feature list. CONTRIBUTING: pre-PR checks now include
  ruff format --check and pyright, matching CI's lint job.
- dashboards/README: the service table and seed description now include
  the PostgreSQL backend the compose stack runs.

Sample data blocks, the CLI-help mirror block, and released CHANGELOG
entries were deliberately left untouched.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* Docstring review: accuracy, spelling, grammar, and clarity pass

Every docstring in parsedmarc/, parsedmarc/mail/, the maps maintainer
scripts, and the test suite reviewed with each claim verified against
the code it documents. Text-only — no behavior changes. Highlights:

- Copy-paste errors corrected: parsed_smtp_tls_reports_to_csv and
  splunk/loganalytics save functions described aggregate or failure
  reports they do not handle; LogAnalyticsException claimed to be an
  Elasticsearch error.
- Docstring/behavior mismatches: parse_report_email's report_type
  enumeration omitted smtp_tls; parse_failure_report typed msg_date as
  str (it is datetime); strip_attachment_payloads claimed payloads are
  replaced with None (the key is deleted); kafkaclient's failure and
  SMTP TLS savers claimed per-record slicing while sending the whole
  list in one message (docstrings now describe reality — whether
  slicing was intended is flagged for follow-up); the postgres savers
  claimed to take parse_report_file's return value but receive the
  inner report dict; elastic/opensearch save functions' Raises listed
  only AlreadySaved.
- None-as-semantic-state documented where missing (get_base_domain,
  get_ip_address_country), enumeration completeness fixed
  (get_ip_address_info's 9 result keys, maps script outputs, TSV
  columns), and the stale 44-industry-types count corrected to the
  46 the authoritative README list defines.
- Test docstrings aligned with what the tests actually assert,
  including two that overstated coverage of the elastic/opensearch
  address-list tests.
- Two argparse help strings fixed: file_path now names SMTP TLS report
  files alongside aggregate and failure, mirrored into usage.md's
  CLI-help block; --offline's doubled spaces removed (rendered help
  unchanged).
- elasticsearch.md's security claim corrected against Elastic's docs:
  security is enabled and auto-configured on first startup since 8.0
  (not "8.7 secure mode"), so the settings are verified, not
  hand-written.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

---------

Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
2026-08-28 17:33:18 -04:00

7.0 KiB

Using the Kibana dashboards

The Kibana DMARC dashboards are a human-friendly way to understand the results from incoming DMARC reports.

There is no separate Kibana export — Kibana 8.x's saved-object migration handlers accept the OpenSearch Dashboards format directly, so Kibana users import the bundled dashboards/opensearch/opensearch_dashboards.ndjson in Stack Management → Saved Objects → Import. A CI check imports the same file into a Kibana 8.x container on every change so this stays compatible.

:::{note} The default dashboard is DMARC aggregate reports. To switch between dashboards, click on the Dashboard link on the left side menu of Kibana. :::

DMARC aggregate reports

As the name suggests, this dashboard is the best place to start reviewing your aggregate DMARC data.

Across the top of the dashboard, three pie charts display the percentage of alignment pass/fail for SPF, DKIM, and DMARC. Clicking on any chart segment will filter for that value.

:::{note} Messages should not be considered malicious just because they failed to pass DMARC, especially if you have just started collecting data. It may be a legitimate service that needs SPF and DKIM configured correctly. :::

Start by filtering the results to only show failed DKIM alignment. While DMARC passes if a message passes SPF or DKIM alignment, only DKIM alignment remains valid when a message is forwarded without changing the from address, which is often caused by a mailbox forwarding rule. This is because DKIM signatures are part of the message headers, whereas SPF relies on the SMTP envelope.

Underneath the pie charts, you can see graphs of DMARC compliance and message disposition over time.

Under the graphs you will find the most useful data tables on the dashboard. On the left, there is a list of organizations that are sending you DMARC reports. In the center, there is a list of sending servers grouped by the base domain in their reverse DNS. On the right, there is the "Message volume and DMARC compliance by from domain" table, which lists email from domains with their message volume and a percentage of those messages that passed DMARC.

By hovering your mouse over a data table value and using the magnifying glass icons, you can filter on or filter out different values. Start by looking at the Message Sources by Reverse DNS table. Find a sender that you recognize, such as an email marketing service, hover over it, and click on the plus (+) magnifying glass icon, to add a filter that only shows results for that sender. Now, look at the Message volume and DMARC compliance by from domain table to the right. That shows you the domains that a sender is sending as, and what share of that traffic is passing DMARC, which might tell you which brand/business is using a particular service. With that information, you can contact them and have them set up DKIM.

:::{note} The "Message volume and DMARC compliance by from domain" table is a TSVB visualization, used because per-domain compliance percentages require a Filter Ratio metric that agg-based data tables can't compute. It renders correctly on Kibana 8.x as imported, but editing it requires first enabling the metrics:allowStringIndices advanced setting, since it references the dmarc_aggregate* index as a string pattern, which Elastic has deprecated. :::

:::{note} If you have a lot of B2C customers, you may see a high volume of emails as your domains coming from consumer email services, such as Google/Gmail and Yahoo! This occurs when customers have mailbox rules in place that forward emails from an old account to a new account, which is why DKIM authentication is so important, as mentioned earlier. Similar patterns may be observed with businesses who send from reverse DNS addresses of parent, subsidiary, and outdated brands. :::

Further down the dashboard, you can filter by source country or source IP address.

Tables showing SPF and DKIM alignment details are located under the IP address table. Each row of the DKIM details table is one real DKIM signature, shown as a combined selector / domain / result value; the SPF details table shows scope / domain / result the same way. Combining the values into one column keeps each signature's selector, domain, and result paired together, rather than aggregating them as separate columns. Because a message that carries multiple DKIM signatures appears once per signature, summing the messages column across rows can exceed the total number of messages.

The "Auth result filters" panel above the details tables provides dropdowns for the individual auth-result components — DKIM selector, DKIM domain, DKIM result, SPF scope, SPF domain, and SPF result — and filters the whole dashboard by them. Because components from different signatures of the same message are indexed together, combining two of these component filters matches documents where any signature satisfies each condition individually, not necessarily the same signature; the combined selector / domain / result (scope / domain / result) column remains the per-signature source of truth.

:::{note} The alignment tables (SPF details, DKIM details) and the per-IP source table live on the same dashboard, further down. To view failures only, use the pie chart at the top of the page as a filter. :::

Any other filters work the same way. You can also add your own custom temporary filters by clicking on Add Filter at the upper right of the page.

DMARC failure reports

The DMARC failure reports dashboard (formerly DMARC Forensic Samples) contains information on DMARC failure reports (also known as forensic or ruf reports). These reports contain samples of emails that have failed to pass DMARC.

:::{note} Most recipients do not send failure/ruf reports at all to avoid privacy leaks. Some recipients (notably Chinese webmail services) will only supply the headers of sample emails. Very few provide the entire email. :::

SMTP TLS reporting

The SMTP TLS reporting dashboard surfaces aggregate counts of TLS-RPT reporting organizations, the policy domains they report on, and the specific failure types — certificate expiry, STARTTLS not supported, STS policy fetch errors, validation failures, and similar — together with the sending and receiving MTA addresses involved.

Like the DKIM and SPF details tables above, the "SMTP TLS domains" and "SMTP TLS failure details" tables show one row per policy and one row per failure detail, respectively, using combined policy (domain / type) and failure detail (domain / type / result / sending mta / receiving ip / mx) columns so that each policy's or failure detail's fields stay paired together, rather than aggregating them as separate columns. The successful_sessions and failed_sessions columns are summed per report document, though, not per policy: when a single report carries multiple policies, a row's session sums include the sibling policies from that report as well as its own. Fully attributing session counts to a single policy would require restructuring the stored documents.