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parsedmarc/docs/source/kibana.md
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62514bd72a Add per-domain DMARC compliance percentage to all aggregate dashboards (#834)
* Add per-domain DMARC compliance percentage to all aggregate dashboards (#112)

The from-domain volume table on every provider's aggregate dashboard is
now "Message volume and DMARC compliance by from domain" with columns
From Domain | Messages | % DMARC Compliant:

- OpenSearch Dashboards/Kibana: the agg-based data table is replaced by
  a TSVB table using a Filter Ratio metric (passed_dmarc:true over all,
  sum of message_count), pivoted on header_from.keyword. The time field
  is date_begin rather than the multi-valued date_range, which TSVB's
  per-value date histogram would double-count. Editing (not rendering)
  the panel on Kibana 8.x requires the metrics:allowStringIndices
  advanced setting.
- Grafana (Elasticsearch): a second passed_dmarc:true query joined by
  field with a binary calculation (Sum 2 / Sum 1) rendered as percentunit.
- Grafana (PostgreSQL): compliance column via an aggregate FILTER clause,
  COALESCEd so zero-pass domains show 0 instead of NULL.
- Splunk: sum(eval(if(passed_dmarc="true", message_count, 0))) inside
  stats, per the SPL eval-in-stats syntax.

All four providers were verified against the same seeded sample data in
the dashboard dev stack; each returns identical per-domain values
(example.com: 2425 messages, 5.3% compliant).

Dev stack fixes found along the way: cap Elasticsearch heap at 2g (the
unset heap auto-sized to 50% of host RAM and was OOM-killed with
bootstrap.memory_lock on large hosts), and install the elasticsearch
datasource plugin in Grafana, which is no longer bundled as of
Grafana 13.

Closes #112

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

* Fix over-time charts double-counting reports via multi-valued date_range

date_range on ES/OpenSearch aggregate and SMTP TLS documents is a
two-element array [begin, end]. A date histogram buckets a document once
per value, so every over-time chart bucketing on date_range counted a
report twice whenever its begin and end dates fell in different buckets.
Range filtering on it was also wrong: a report spanning the whole window
matches neither endpoint.

Measured on the dev-stack sample data: a 1d histogram on date_range
returns doc_count 4592 / message sum 4724 against true totals of
2300 / 2427; the same histogram on date_begin returns exactly
2300 / 2427.

All date histograms (2 OSD/Kibana visualizations, 10 Grafana ES panels
including the summary pies) and all time-range filters (24 Grafana
target timeFields, the dmarc_aggregate* and smtp_tls* index-pattern
timeFieldName, the dev-stack dmarc-ag datasource) now use the
single-valued date_begin, matching the report-begin semantics of the
PostgreSQL (begin_date) and Splunk (_time = interval begin) dashboards.
Failure-report panels already used the single-valued arrival_date and
are unchanged.

Dev stack: installing the Elasticsearch datasource plugin via
GF_INSTALL_PLUGINS crash-loops Grafana >= 13 (the image ships a
root-owned plugins-bundled/elasticsearch remnant the background
installer cannot replace), so the bootstrap script now installs it via
grafana cli and restarts Grafana instead.

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

* Address Copilot review comments on PR #834

- kibana.md: "filter on our filter out" -> "filter on or filter out".
- OSD/Kibana export: fix "filed  DMARC" -> "failed DMARC" and the
  backticked `ruf ` trailing space in the RUF explainer panel, and
  rename the "SMPT TLS failure details" visualization to "SMTP TLS
  failure details" (object title and visState).
- dashboard-dev-bootstrap.sh: reuse wait_for() after the Grafana
  plugin-install restart so a hang fails with a clear timeout message
  instead of an opaque downstream curl error.

The ndjson changes were round-tripped through the dev-stack OSD
(import -> re-export from the global tenant) and re-import cleanly into
both OSD and Kibana 8.19.

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

* AGENTS.md: reviews must cover prose and hunk context, not just function

Codifies the lessons from the PR #834 Copilot review: whole-file
canonical dashboard exports put pre-existing titles/markdown in the
diff, so they get a text-level pass; proofread the full hunk around
prose edits, not only changed lines; and mid-incident glue code gets
the same review bar (and helper-reuse check) as planned code.

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

* Address second round of Copilot review comments

- CHANGELOG.md: rename the premature "10.2.5" heading to "Unreleased",
  matching the repo convention where the release commit assigns the
  version number (see 855d267 for 10.2.4).
- docker-compose.yml: make the dev-stack Elasticsearch heap overridable
  via ES_JAVA_OPTS in .env (default unchanged at 2g), using the compose
  file's existing ${VAR:-default} idiom, for smaller machines.

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

---------

Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
2026-07-21 19:23:55 -04:00

5.2 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 SMTP session headers.

Underneath the pie charts. you can see graphs of DMARC passage 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 addressees 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.

:::{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.