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https://github.com/domainaware/parsedmarc.git
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SMTP TLS reports have the same cross-product defect as the DKIM/SPF alignment tables (issue #169), one level deeper: policies is an object array and each policy's failure_details is an object array inside it, so stacked terms aggregations on their subfields fabricate rows. Documents now also carry policies_combined ("domain / type" per policy) and failure_details_combined ("domain / type / result / sending mta / receiving ip / mx" per failure detail), composed at save time with the same "none" fallbacks as the aggregate fields. migrate_indexes() gains smtp_tls_indexes and backfills old documents with the same guarded, non-blocking update_by_query pattern; cli.py wires the index name in on both backends, and the manual _update_by_query command is documented. Also fixes two adjacent dead fields: add_failure_details stored additional_information_uri under the wrong constructor kwarg (additional_information), and receiving_mx_hostname had no declaration despite always being stored. Verified live on ES 8.19 and OpenSearch 3: a two-policy repro report yields exactly 2 policy rows and 2 failure-detail rows via the combined fields where the old stacked aggregations return 4 of each; the startup backfill converted the 4 pre-existing sample documents on both engines with zero recompute mismatches. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
392 lines
14 KiB
Markdown
392 lines
14 KiB
Markdown
# Elasticsearch and Kibana
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To set up visual dashboards of DMARC data, install Elasticsearch and Kibana.
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:::{note}
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Elasticsearch and Kibana 8 or later are required (parsedmarc's 8.x Python
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client also supports Elasticsearch 9). OpenSearch users must use the
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`[opensearch]` configuration section instead — the Elasticsearch 8.x client
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refuses to connect to non-Elasticsearch clusters.
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:::
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## Installation
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On Debian/Ubuntu based systems, run:
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```bash
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sudo apt-get install -y apt-transport-https
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wget -qO - https://artifacts.elastic.co/GPG-KEY-elasticsearch | sudo gpg --dearmor -o /usr/share/keyrings/elasticsearch-keyring.gpg
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echo "deb [signed-by=/usr/share/keyrings/elasticsearch-keyring.gpg] https://artifacts.elastic.co/packages/8.x/apt stable main" | sudo tee /etc/apt/sources.list.d/elastic-8.x.list
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sudo apt-get update
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sudo apt-get install -y elasticsearch kibana
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```
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For CentOS, RHEL, and other RPM systems, follow the Elastic RPM guides for
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[Elasticsearch] and [Kibana].
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:::{note}
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Previously, the default JVM heap size for Elasticsearch was very small (1g),
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which will cause it to crash under a heavy load. To fix this, increase the
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minimum and maximum JVM heap sizes in `/etc/elasticsearch/jvm.options` to
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more reasonable levels, depending on your server's resources.
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Make sure the system has at least 2 GB more RAM than the assigned JVM
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heap size.
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Always set the minimum and maximum JVM heap sizes to the same
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value.
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For example, to set a 4 GB heap size, set
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```bash
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-Xms4g
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-Xmx4g
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```
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See <https://www.elastic.co/guide/en/elasticsearch/reference/current/important-settings.html#heap-size-settings>
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for more information.
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:::
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```bash
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sudo systemctl daemon-reload
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sudo systemctl enable elasticsearch.service
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sudo systemctl enable kibana.service
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sudo systemctl start elasticsearch.service
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sudo systemctl start kibana.service
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```
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As of Elasticsearch 8.7, activate secure mode (xpack.security.*.ssl)
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```bash
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sudo vim /etc/elasticsearch/elasticsearch.yml
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```
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Add the following configuration
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```text
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# Enable security features
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xpack.security.enabled: true
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xpack.security.enrollment.enabled: true
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# Enable encryption for HTTP API client connections, such as Kibana, Logstash, and Agents
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xpack.security.http.ssl:
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enabled: true
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keystore.path: certs/http.p12
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# Enable encryption and mutual authentication between cluster nodes
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xpack.security.transport.ssl:
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enabled: true
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verification_mode: certificate
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keystore.path: certs/transport.p12
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truststore.path: certs/transport.p12
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```
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```bash
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sudo systemctl restart elasticsearch
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```
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To create a self-signed certificate, run:
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```bash
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openssl req -x509 -nodes -days 365 -newkey rsa:4096 -keyout kibana.key -out kibana.crt
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```
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Or, to create a Certificate Signing Request (CSR) for a CA, run:
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```bash
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openssl req -newkey rsa:4096-nodes -keyout kibana.key -out kibana.csr
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```
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Fill in the prompts. Watch out for Common Name (e.g. server FQDN or YOUR
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domain name), which is the IP address or domain name that you will use to access Kibana. it is the most important field.
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If you generated a CSR, remove the CSR after you have your certs
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```bash
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rm -f kibana.csr
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```
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Move the keys into place and secure them:
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```bash
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sudo mv kibana.* /etc/kibana
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sudo chmod 660 /etc/kibana/kibana.key
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```
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Activate the HTTPS server in Kibana
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```bash
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sudo vim /etc/kibana/kibana.yml
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```
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Add the following configuration
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```text
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server.host: "SERVER_IP"
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server.publicBaseUrl: "https://SERVER_IP"
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server.ssl.enabled: true
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server.ssl.certificate: /etc/kibana/kibana.crt
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server.ssl.key: /etc/kibana/kibana.key
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```
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:::{note}
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For more security, you can configure Kibana to use a local network connection
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to elasticsearch :
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```text
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elasticsearch.hosts: ['https://SERVER_IP:9200']
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```
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=>
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```text
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elasticsearch.hosts: ['https://127.0.0.1:9200']
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```
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:::
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```bash
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sudo systemctl restart kibana
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```
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Enroll Kibana in Elasticsearch
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```bash
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sudo /usr/share/elasticsearch/bin/elasticsearch-create-enrollment-token -s kibana
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```
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Then access to your web server at `https://SERVER_IP:5601`, accept the self-signed
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certificate and paste the token in the "Enrollment token" field.
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```bash
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sudo /usr/share/kibana/bin/kibana-verification-code
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```
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Then put the verification code to your web browser.
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End Kibana configuration
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```bash
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sudo /usr/share/elasticsearch/bin/elasticsearch-setup-passwords interactive
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sudo /usr/share/kibana/bin/kibana-encryption-keys generate
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sudo vim /etc/kibana/kibana.yml
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```
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Add previously generated encryption keys
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```text
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xpack.encryptedSavedObjects.encryptionKey: xxxx...xxxx
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xpack.reporting.encryptionKey: xxxx...xxxx
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xpack.security.encryptionKey: xxxx...xxxx
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```
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```bash
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sudo systemctl restart kibana
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sudo systemctl restart elasticsearch
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```
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Now that Elasticsearch is up and running, use `parsedmarc` to send data to
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it.
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Download (right-click the link and click save as) [export.ndjson].
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Connect to kibana using the "elastic" user and the password you previously provide
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on the console ("End Kibana configuration" part).
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Import `export.ndjson` the Saved Objects tab of the Stack management
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page of Kibana. (Hamburger menu -> "Management" -> "Stack Management" ->
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"Kibana" -> "Saved Objects")
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It will give you the option to overwrite existing saved dashboards or
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visualizations, which could be used to restore them if you or someone else
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breaks them, as there are no permissions/access controls in Kibana without
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the commercial [X-Pack].
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```{image} _static/screenshots/saved-objects.png
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:align: center
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:alt: A screenshot of setting the Saved Objects Stack management UI in Kibana
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:target: _static/screenshots/saved-objects.png
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```
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```{image} _static/screenshots/confirm-overwrite.png
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:align: center
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:alt: A screenshot of the overwrite conformation prompt
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:target: _static/screenshots/confirm-overwrite.png
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```
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## Upgrading Kibana index patterns
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`parsedmarc` 5.0.0 makes some changes to the way data is indexed in
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Elasticsearch. if you are upgrading from a previous release of
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`parsedmarc`, you need to complete the following steps to replace the
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Kibana index patterns with versions that match the upgraded indexes:
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1. Login in to Kibana, and click on Management
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2. Under Kibana, click on Saved Objects
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3. Check the checkboxes for the `dmarc_aggregate` and `dmarc_failure`
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index patterns
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4. Click Delete
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5. Click Delete on the conformation message
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6. Download (right-click the link and click save as)
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the latest version of [export.ndjson]
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7. Import `export.ndjson` by clicking Import from the Kibana
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Saved Objects page
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## Backfilling the combined DKIM/SPF result fields
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As of the version fixing [#169](https://github.com/domainaware/parsedmarc/issues/169),
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aggregate documents include `dkim_results_combined` and `spf_results_combined` —
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scalar string arrays that keep each auth result's selector/scope, domain, and
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result paired, which the dashboards' alignment-detail tables aggregate on.
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Reports saved by older versions lack these fields and will not appear in
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those tables.
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parsedmarc now backfills this automatically. On startup, it runs a cheap
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count query against each configured aggregate index pattern to check for
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documents that have DKIM or SPF results but are missing the corresponding
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combined field. If any are found, it submits the backfill as a background
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`_update_by_query` task (`wait_for_completion=false`), so startup is never
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blocked on it; progress is logged, including the task ID. The check itself
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is idempotent — once an index is fully backfilled, later startups see a
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count of 0 and log nothing further — and it works the same way on
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OpenSearch. Any error talking to the cluster (for example, no indexes yet
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on a fresh install) is logged as a warning and retried on the next startup,
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rather than aborting parsedmarc.
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If you upgrade the dashboards without pointing the new parsedmarc version
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at the cluster, or you'd rather control when the write load happens, you
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can still run the backfill manually. It is idempotent (documents that
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already have the fields are skipped), so it is safe to re-run. It works
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identically on OpenSearch; just adjust the URL and credentials. The query
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matches only documents that have at least one DKIM or SPF auth result and
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lack the corresponding combined field; documents with no auth results are
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skipped, because an `exists` query cannot see an empty array, and for
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search purposes an empty `dkim_results_combined` is identical to an
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absent one. Each result is matched on either its `domain` or its `result`
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subfield as defense in depth: an empty string indexes no text tokens and
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is invisible to `exists`, and the storage shape of every historical
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parsedmarc version can't be audited, so matching either subfield ensures
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no backfillable document is skipped.
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```bash
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curl -X POST "http://localhost:9200/dmarc_aggregate*/_update_by_query?conflicts=proceed&wait_for_completion=false" \
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-H "Content-Type: application/json" -d '
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{
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"query": {
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"bool": {
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"minimum_should_match": 1,
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"should": [
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{
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"bool": {
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"must": [
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{
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"bool": {
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"minimum_should_match": 1,
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"should": [
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{"exists": {"field": "dkim_results.domain"}},
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{"exists": {"field": "dkim_results.result"}}
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]
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}
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}
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],
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"must_not": [{"exists": {"field": "dkim_results_combined"}}]
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}
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},
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{
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"bool": {
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"must": [
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{
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"bool": {
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"minimum_should_match": 1,
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"should": [
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{"exists": {"field": "spf_results.domain"}},
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{"exists": {"field": "spf_results.result"}}
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]
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}
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}
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],
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"must_not": [{"exists": {"field": "spf_results_combined"}}]
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}
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}
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]
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}
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},
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"script": {
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"lang": "painless",
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"source": "List dk = new ArrayList(); def dr = ctx._source.dkim_results; if (dr != null) { if (!(dr instanceof List)) { dr = [dr]; } for (e in dr) { if (e == null) { continue; } def sel = e.selector != null ? e.selector : \"none\"; def dom = e.domain != null ? e.domain : \"none\"; def res = e.result != null ? e.result : \"none\"; dk.add(sel + \" / \" + dom + \" / \" + res); } } ctx._source.dkim_results_combined = dk; List sp = new ArrayList(); def sr = ctx._source.spf_results; if (sr != null) { if (!(sr instanceof List)) { sr = [sr]; } for (e in sr) { if (e == null) { continue; } def sc = e.scope != null ? e.scope : \"mfrom\"; def dom = e.domain != null ? e.domain : \"none\"; def res = e.result != null ? e.result : (e.results != null ? e.results : \"none\"); sp.add(sc + \" / \" + dom + \" / \" + res); } } ctx._source.spf_results_combined = sp;"
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}
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}'
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```
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`wait_for_completion=false` returns a task ID — check progress with
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`GET _tasks/<task id>`. Adjust the index pattern if you use a custom
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`index_prefix`/`index_suffix`. After backfilling, re-import the updated
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dashboards ndjson (the index pattern saved object changed too) per the
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import instructions above.
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SMTP TLS documents have the same class of defect one level deeper:
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`policies` is an object array, and each policy's `failure_details` is an
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object array inside it. SMTP TLS documents now also carry
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`policies_combined` and `failure_details_combined`, backfilled
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automatically at startup the same way, and the equivalent manual command
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is:
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```bash
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curl -X POST "http://localhost:9200/smtp_tls*/_update_by_query?conflicts=proceed&wait_for_completion=false" \
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-H "Content-Type: application/json" -d '
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{
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"query": {
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"bool": {
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"minimum_should_match": 1,
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"should": [
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{
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"bool": {
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"must": [
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{
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"bool": {
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"minimum_should_match": 1,
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"should": [
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{"exists": {"field": "policies.policy_domain"}},
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{"exists": {"field": "policies.policy_type"}}
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]
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}
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}
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],
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"must_not": [{"exists": {"field": "policies_combined"}}]
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}
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},
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{
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"bool": {
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"must": [
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{
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"bool": {
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"minimum_should_match": 1,
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"should": [
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{"exists": {"field": "policies.failure_details.result_type"}},
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{"exists": {"field": "policies.failure_details.sending_mta_ip"}}
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]
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}
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}
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],
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"must_not": [{"exists": {"field": "failure_details_combined"}}]
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}
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}
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]
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}
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},
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"script": {
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"lang": "painless",
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"source": "List pols = new ArrayList(); List dets = new ArrayList(); def ps = ctx._source.policies; if (ps != null) { if (!(ps instanceof List)) { ps = [ps]; } for (p in ps) { if (p == null) { continue; } def dom = p.policy_domain != null ? p.policy_domain : \"none\"; def typ = p.policy_type != null ? p.policy_type : \"none\"; pols.add(dom + \" / \" + typ); def fds = p.failure_details; if (fds != null) { if (!(fds instanceof List)) { fds = [fds]; } for (f in fds) { if (f == null) { continue; } def rt = f.result_type != null ? f.result_type : \"none\"; def smi = f.sending_mta_ip != null ? f.sending_mta_ip : \"none\"; def ri = f.receiving_ip != null ? f.receiving_ip : \"none\"; def rmh = f.receiving_mx_hostname != null ? f.receiving_mx_hostname : \"none\"; dets.add(dom + \" / \" + typ + \" / \" + rt + \" / \" + smi + \" / \" + ri + \" / \" + rmh); } } } } ctx._source.policies_combined = pols; ctx._source.failure_details_combined = dets;"
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}
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}'
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```
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It works identically on OpenSearch; just adjust the URL and credentials, same
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as the aggregate command above.
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## Records retention
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Starting in version 5.0.0, `parsedmarc` stores data in a separate
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index for each day to make it easy to comply with records
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retention regulations such as GDPR. For more information,
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check out the Elastic guide to [managing time-based indexes efficiently](https://www.elastic.co/blog/managing-time-based-indices-efficiently).
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[elasticsearch]: https://www.elastic.co/guide/en/elasticsearch/reference/current/rpm.html
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[export.ndjson]: https://raw.githubusercontent.com/domainaware/parsedmarc/master/dashboards/opensearch/opensearch_dashboards.ndjson
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[kibana]: https://www.elastic.co/guide/en/kibana/current/rpm.html
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[x-pack]: https://www.elastic.co/products/x-pack
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