Security ML Integrations
ElasticOfficialCreated by elastic
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- Workflow
- Cloud and DevOps
- Apache-2.0
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AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill provides a structured, multi-step workflow for installing, verifying, and troubleshooting Elastic security ML integration packages, including beaconing, data exfiltration, DGA, lateral movement, privileged access, and living-off-the-land detection. It manages the entire lifecycle, from pre-flight environment checks and Fleet package installation to configuring component templates, ingest pipelines, transforms, data views, ML anomaly detection jobs, and detection rules. The skill ensures safe operations by requiring user confirmation before applying any changes and by performing state validation to prevent configuration conflicts.
What it does
- Performs pre-flight checks for license, permissions, and ML capacity.
- Installs and manages Fleet security ML integration packages.
- Configures shared component templates and ingest pipelines without overwriting existing data.
- Manages transform lifecycle, including resetting and starting jobs.
- Deploys ML anomaly detection jobs and enables associated detection rules.
- Provides status reporting and documentation retrieval for installed packages.
When to use it
- When you need to install a new security ML integration package.
- When you need to verify the installation status or configuration of an existing package.
- When troubleshooting issues with ML jobs, transforms, or detection rules related to these packages.
- When you need to ensure all required assets like data views and pipelines are correctly set up.
Advantages
- Reduces manual effort by automating complex, multi-step deployment procedures.
- Prevents configuration errors through pre-flight state validation.
- Protects existing infrastructure by merging rather than overwriting shared templates and pipelines.
- Ensures operational safety by requiring explicit user confirmation before any write operations.
Usage examples
- “Install PAD”
- The agent gathers the current state of the PAD package, checks ML capacity, identifies required template merges, and presents a plan for installation, including transform and data view setup, before requesting confirmation to proceed.
- “Is beaconing installed?”
- The agent queries the Fleet package manager for the beaconing package status and reports the title, version, and current installation status without modifying any system settings.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/elastic/security-ml-integrations/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip security-ml-integrations.zip -d .agents/skills
Documentation by elastic
Security ML Integration Package Management
Install, check, or troubleshoot a security ML package. Supported packages: beaconing (Network Beaconing
Identification), ded (Data Exfiltration Detection), dga (Domain Generation Algorithm Detection), lmd (Lateral
Movement Detection), pad (Privileged Access Detection), problemchild (Living off the Land Attack Detection).
<!-- begin-partial: preamble -->
Environment Configuration
This skill executes Elasticsearch operations through the elastic CLI. If the
elastic CLI is not installed, tell the user what it is needed for. Do
not guess credentials, call the HTTP API directly, or attempt other workarounds.
This skill references operations in HTTP-shorthand form (e.g., GET /, GET /_cat/indices, GET /{index}/_mapping,
GET /{index}/_settings/index.mode, POST /_query). The Operations table at the end of this document
maps each shorthand to the equivalent elastic CLI command — always use the CLI rather than calling the HTTP API
directly.
<!-- end-partial: preamble -->
Package source patterns, shared template fields, and ingest-pipeline wiring live in package capabilities.
Process
Classify the request. Status, README, or install. Status and README stay read-only — do not install, start transforms, deploy jobs, or enable rules. After identifying the package, branch: status uses
GET kbn:/api/fleet/epm/packages/{package}only (title, version, status); README addsGET kbn:/api/fleet/epm/packages/{package}/{version}/docs/README.mdand returns that document; install continues.Identify the package. Map the user's words to one of the six package names above. If the name is ambiguous, ask before calling any API. Load that package's row from package capabilities — omit fields that are empty for that package.
Gather environment state before any mutation. Install only.
GET /_licensefirst — continue only forplatinum,enterprise,trial, or Serverless. IfGET /_ml/inforeturns 403, report missingmanage_mland stop. Then collect:Package:
GET kbn:/api/fleet/epm/packages/{package}for name, title, version, andstatus.Source data:
POST /{source_patterns}/_searchwithsize: 0andtrack_total_hits: true. If every pattern has zero hits, warn that jobs will not produce useful anomalies.Shared template (DGA, PAD, ProblemChild only):
GET /_component_template/{name}. Exists → plan a merge of the fields in the reference. 404 → plan a create with only those fields.Shared pipeline (DGA, PAD, ProblemChild only):
GET /_ingest/pipeline/{name}. Exists → plan to append a processor. 404 → plan a single-processor pipeline.Transforms:
GET /_transform/{pattern}(skip if the package has no transform pattern). Record eachid,dest.index, and the.allalias (dest.aliaseswheremove_on_creationis false).Data views:
GET kbn:/api/data_viewsand check whether the package's data-view pattern already exists.ML capacity:
GET /_ml/info(total memory) andGET /_ml/anomaly_detectors/_all/_stats(sum memory of opened jobs).GET kbn:/internal/ml/modules/get_module/{module_id}for job count and per-job memory. If jobs do not fit, say so and suggest prioritizing job groups — do not deploy anyway without the user accepting the risk.Rules:
GET kbn:/api/detection_engine/rules/prepackaged/_statusandPOST kbn:/internal/detection_engine/prebuilt_rules/installation/_reviewfiltered by the package detection tag.
Present a plan and wait for confirmation. Show package identity and status, source-data hits (warn if all zero), template/pipeline merge-or-create, transform count and states, data-view presence, ML memory fit, and rule count. Do not call any write API until the user confirms. If they decline, stop.
Install the Fleet package, then apply shared mappings. After confirmation:
POST kbn:/api/fleet/epm/packages/{package}to install assets (transforms may be deferred until started).If the package uses a component template:
PUT /_component_template/{name}with the merged or new body. ThenPOST /{data_stream}/_rolloveron the rollover target so new indices pick up mappings.If the package uses an ingest pipeline:
PUT /_ingest/pipeline/{name}with appended or new processors. Use the installed package version in the versioned pipeline name.
Skip template, pipeline, and rollover when the package row has no values for them (beaconing, ded, lmd).
Start transforms and create destination aliases. Skip this block (except
.ml-anomalies-shared) when the package has no transform pattern. Fleet's first checkpoint often skips.allaliases. After install,GET /_transform/{pattern}again if IDs were missing. Reset only if the transform is new, never started, failed, or the user asked to rebuild:POST /_transform/{id}/_stop,POST /_transform/{id}/_reset,POST /_transform/{id}/_updatewith the existing description,POST /_transform/{id}/_start,POST /_transform/{id}/_schedule_now. If alreadystartedwithcheckpointing.last.checkpoint >= 1, skip reset; restamp via the existing description and ensure.allaliases exist. ThenPOST /_aliasesto add the.allalias (and.latestif the dest defines it) ondest.index. If a data-view pattern is missing,POST kbn:/api/data_views/data_view. Also ensure a hidden.ml-anomalies-shareddata view exists (POST kbn:/api/data_views/data_view) so package dashboards resolve.Confirm the first transform checkpoint before ML. If the package row has no transform pattern, skip this step and continue to jobs. Otherwise call
GET /_transform/{pattern}/_stats. Proceed only when each transform isstartedandcheckpointing.last.checkpoint >= 1; do not usedocuments_processedas a substitute. Zero documents with a completed checkpoint is acceptable when source patterns are empty — destination aliases still let datafeeds start. Otherwise tell the user transforms must finish processing and wait for confirmation before the next step. Never set up the ML module against missing dest indices.Deploy ML jobs, then detection rules. After transforms are confirmed (or skipped):
POST kbn:/internal/ml/modules/setup/{module_id}withstartDatafeed: trueandindexPatternNameset to the package data-view pattern, or source patterns when that cell is empty. Do not put spaces after commas inindexPatternName— the setup API splits on commas without trimming. Correct:logs-*,ml_okta_multiple_user_sessions_pad.all,ml_windows_privilege_type_pad.all.Initialize the detection engine if needed (
POST kbn:/api/detection_engine/index), install the prebuilt rules package (POST kbn:/api/fleet/epm/packages/security_detection_engine), review the package-tagged rules, then callPOST kbn:/internal/detection_engine/prebuilt_rules/installation/_performwith{"mode":"SPECIFIC_RULES","rules":[{"rule_id":"<rule_id>","version":<version>}]}(one entry per reviewed rule). Enable the package's ML rules withPOST kbn:/api/detection_engine/rules/_bulk_action(disablethenenableon immutable ML rules tagged with the package detection tag so API keys are stamped with the calling user).
Report created versus skipped. Package version and asset count; template/pipeline/rollover created, updated, or skipped; transforms started; data views created or already present; ML jobs and datafeeds started (and any that failed, with the mapping or index reason); rules installed and enabled.
Examples
Install PAD
User: "Install PAD"
Gather state for
pad. Package not installed, zero source hits,logs-endpoint.events.process@customalready has ProblemChild fields, no@custompipeline, two stopped transforms, 15 jobs fit in available memory, tagged rules available.Present the plan: warn about empty source data; merge
process.command_line_entropy; create the PAD pipeline processor; start both transforms; create the PAD data view. Wait for confirm.After confirm:
POST kbn:/api/fleet/epm/packages/pad, merge-and-PUTthe shared template,PUTthe pipeline, restamp via existing description (reset only if transforms are new or stopped),POST /_aliasesfor each.allalias.GET /_transform/*pad*/_stats. If checkpoint 1 is done (even with 0 docs), continue; otherwise wait for the user.POST kbn:/internal/ml/modules/setup/pad-mlwith a no-spaceindexPatternName, then install and enable rules taggedUse Case: Privileged Access Detection.Report each section as created, updated, or skipped.
Install beaconing (no template or pipeline)
User: "Set up beaconing"
Gather state. Omit template, pipeline, and rollover — the beaconing row has none.
Present a shorter plan (package, one transform, data view, jobs, rules). Wait for confirm.
Install the package, start the transform, create
ml_beaconing*if missing, confirm checkpoint, set upbeaconing-ml, enable rules taggedUse Case: Network Beaconing Identification.
Status only
User: "Is beaconing installed?"
GET kbn:/api/fleet/epm/packages/beaconingonly.Report title, version, and status. A README request also fetches and returns the docs README. Do not install or start anything.
Guidelines
Gather environment state before every install. Do not skip the pre-flight reads.
Stay read-only on status and README questions.
Wait for explicit confirmation before any write. Check license before the Fleet POST.
Pause after transforms until
checkpointing.last.checkpoint >= 1(0 docs is acceptable when source patterns are empty). Skip transform and package data-view steps when those capability cells are empty.Never overwrite shared
@customtemplates or pipelines. PAD and ProblemChild sharelogs-endpoint.events.process@custom— merge fields and append processors.Put no spaces after commas in ML
indexPatternName.Cite Fleet package APIs as
kbn:/api/fleet/.... Do not use afleet:prefix.Restamp a Fleet transform by setting
--descriptionto the existing text, then start. Do not use--body '{}'.On serverless,
GET /_ml/infomay return 410. Continue with opened-job stats fromGET /_ml/anomaly_detectors/_all/_stats; do not abort the install.
Operations
| HTTP API (shorthand) | elastic CLI command |
|---|---|
GET kbn:/api/fleet/epm/packages/{package} | elastic kb elastic-package-manager-epm get-fleet-epm-packages-pkgname --pkg-name '{package}' |
GET kbn:/api/fleet/epm/packages/{package}/{version}/docs/README.md | CLI gap — package-file fetch 404s on registry paths; keep this shorthand as the contract |
POST kbn:/api/fleet/epm/packages/{package} | elastic kb elastic-package-manager-epm post-fleet-epm-packages-pkgname --pkg-name '{package}' |
POST /{source_patterns}/_search | elastic es count --index '{source_patterns}' --allow-no-indices true --ignore-unavailable true |
GET /_component_template/{name} | elastic es cluster get-component-template --name '{name}' |
PUT /_component_template/{name} | elastic es cluster put-component-template --name '{name}' --template '{json}' |
GET /_ingest/pipeline/{name} | elastic es ingest get-pipeline --id '{name}' |
PUT /_ingest/pipeline/{name} | elastic es ingest put-pipeline --id '{name}' --input-file '{path}' |
POST /{data_stream}/_rollover | elastic es indices rollover --alias '{data_stream}' |
GET /_transform/{pattern} | elastic es transform get-transform --transform-id '{pattern}' |
GET /_transform/{pattern}/_stats | elastic es transform get-transform-stats --transform-id '{pattern}' |
POST /_transform/{id}/_stop | elastic es transform stop-transform --transform-id '{id}' --force true --wait-for-completion true |
POST /_transform/{id}/_reset | elastic es transform reset-transform --transform-id '{id}' --force true |
POST /_transform/{id}/_update | elastic es transform update-transform --transform-id '{id}' --description '{existing}' |
POST /_transform/{id}/_start | elastic es transform start-transform --transform-id '{id}' |
POST /_transform/{id}/_schedule_now | elastic es transform schedule-now-transform --transform-id '{id}' |
POST /_aliases | elastic es indices update-aliases --actions '{json}' |
GET kbn:/api/data_views | elastic kb data-views get-all-data-views-default |
POST kbn:/api/data_views/data_view | elastic kb data-views create-data-view-default --data-view '{json}' |
GET /_license | elastic es license get |
GET /_ml/info | elastic es ml info |
GET /_ml/anomaly_detectors/_all/_stats | elastic es ml get-job-stats --job-id '_all' |
GET kbn:/internal/ml/modules/get_module/{module_id} | CLI gap — ML module get is an internal Kibana API; keep this shorthand as the contract |
POST kbn:/internal/ml/modules/setup/{module_id} | CLI gap — ML module setup is an internal Kibana API; keep this shorthand as the contract |
GET kbn:/api/detection_engine/rules/prepackaged/_status | CLI gap — no generated prepackaged-status command; keep this shorthand as the contract |
POST kbn:/api/detection_engine/index | CLI gap — no generated detection-engine index command; keep this shorthand as the contract |
POST kbn:/api/fleet/epm/packages/security_detection_engine | elastic kb elastic-package-manager-epm post-fleet-epm-packages-pkgname --pkg-name 'security_detection_engine' |
POST kbn:/internal/detection_engine/prebuilt_rules/installation/_review | CLI gap — prebuilt-rule review is an internal Kibana API; keep this shorthand as the contract |
POST kbn:/internal/detection_engine/prebuilt_rules/installation/_perform | CLI gap — prebuilt-rule install is an internal Kibana API; keep this shorthand as the contract |
POST kbn:/api/detection_engine/rules/_bulk_action | CLI gap — generated perform-rules-bulk-action accepts only edit; keep this shorthand for disable/enable |
Internal ML-module APIs, prebuilt-rules _review/_perform, detection-engine index, and rules disable/enable have no
usable generated CLI commands yet. Keep the HTTP shorthand as the contract; do not add skill-owned scripts as a
workaround. Generated Fleet EPM get/install commands exist — use those instead of the shorthand.
Files
- ATTRIBUTION.mdAdded by AutoGineer967 B
- LICENSELicence file added by AutoGineer11.1 KiB
- SKILL.md17.5 KiB
- references/README.md1.6 KiB
- references/package-capabilities.md5.7 KiB
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Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Needs an API key
The author says: Requires Kibana 9.4+ with Fleet, ML, and Security; a Platinum, Enterprise, or trial license (or Serverless); manage_ml; and the elastic CLI ≥ 0.5.
Security
No issues found by our static scan· No issues found
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Created by
- elastic
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- Source
- elastic/agent-skills · skills/security/ml-integrations · commit 09d879d
- Licence
- Apache License 2.0 (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
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