Detection Rule Management

Create new detection rules for emerging threats and coverage gaps, and tune existing rules to reduce false positives. All operations use the Kibana Detection Engine API via

rule-manager.js

Execution rules

Start executing tools immediately — do not read SKILL.md, browse the workspace, or list files first.
Report tool output faithfully. Copy rule IDs, names, alert counts, exception IDs, and error messages exactly as returned by the API. Do not abbreviate rule UUIDs, invent rule names, or round alert counts.
When a tool returns an error (rule not found, API failure), report the exact error — do not guess at alternatives.

Prerequisites

Install dependencies before first use from the

skills/security

directory:

bash

cd skills/security && npm install

Set the required environment variables (or add them to a

.env

file in the workspace root):

bash

export ELASTICSEARCH_URL="https://your-cluster.es.cloud.example.com:443"
export ELASTICSEARCH_API_KEY="your-api-key"
export KIBANA_URL="https://your-cluster.kb.cloud.example.com:443"
export KIBANA_API_KEY="your-kibana-api-key"

Common multi-step workflows

Task	Tools to call (in order)
Tune noisy SIEM rule	`rule_manager` find/noisy-rules → `run_query` (investigate FPs) → `rule_manager` patch or add-exception
Add endpoint behavior exception	`fetch_endpoint_rule` (get rule definition from GitHub) → `add_endpoint_exception` (scoped to rule.id)
Create new detection rule	`run_query` (test query against data) → `rule_manager` create
Investigate rule alert volume	`rule_manager` get → `run_query` (query alerts index)

For endpoint behavior rules, always fetch the rule definition first to understand query logic and existing exclusions before adding an exception. For SIEM rules, always investigate alert patterns with

run_query

before tuning.

Critical: For endpoint behavior rules, always use

fetch_endpoint_rule

(not

shell

or direct script calls) to get the rule definition, then use

add_endpoint_exception

to add the exception. These are dedicated tools — do not invoke the underlying scripts manually.

Workflow: Tune a rule for false positives

Steps 1–2: Identify noisy rules and analyze false positives

Find noisy rules with

noisy-rules

find

, then get the rule definition and investigate alerts:

bash

node skills/security/detection-rule-management/scripts/rule-manager.js noisy-rules --days 7 --top 20
node skills/security/detection-rule-management/scripts/rule-manager.js find --filter "alert.attributes.name:*Suspicious*" --brief
node skills/security/detection-rule-management/scripts/rule-manager.js get --id <rule_uuid>
node skills/security/alert-triage/scripts/run-query.js "kibana.alert.rule.name:\"<rule_name>\"" --index ".alerts-security.alerts-*" --days 7 --full

Look for patterns: same process/user/host → exception candidate; broad pattern → tighten query; legitimate software → exception; too broad → rewrite or adjust threshold.

Step 3: Choose a tuning strategy

In order of preference:

Add exception — Best for specific known-good processes, users, or hosts. Does not modify the rule query. Use when the rule is correct in general but fires on known-legitimate activity.
Tighten the query — Patch the rule's query to exclude the FP pattern. Best when the false positives stem from the query being too broad.
Adjust threshold / alert suppression — For threshold rules, increase the threshold value. For any rule type, enable alert suppression to reduce duplicate alerts on the same entity.
Reduce risk score / severity — Downgrade the rule's priority if it generates many low-value alerts but still has some detection value.
Disable the rule — Last resort. Only if the rule provides no value or is completely redundant with another rule.

Steps 4–5: Apply tuning, verify, and document

Add exception (single/multi-condition, wildcard via

matches

bash

node skills/security/detection-rule-management/scripts/rule-manager.js add-exception \
  --rule-uuid <rule_uuid> \
  --entries "process.executable:is:C:\\Program Files\\SCCM\\CcmExec.exe" "process.parent.name:is:CcmExec.exe" \
  --name "Exclude SCCM" --comment "FP: SCCM deployment" --tags "tuning:fp" "source:soc" --yes

Patch query, threshold, severity, or disable:

bash

node skills/security/detection-rule-management/scripts/rule-manager.js patch --id <rule_uuid> --query "process.name:powershell.exe AND NOT process.parent.name:CcmExec.exe" --yes
node skills/security/detection-rule-management/scripts/rule-manager.js patch --id <rule_uuid> --max-signals 50 --yes
node skills/security/detection-rule-management/scripts/rule-manager.js patch --id <rule_uuid> --severity low --risk-score 21 --yes
node skills/security/detection-rule-management/scripts/rule-manager.js disable --id <rule_uuid> --yes

Write operations (

patch

enable

disable

delete

add-exception

bulk-action

) prompt for confirmation by default. Pass

--yes

to skip the prompt (required when called by an agent).

Verify with

rule-manager.js get --id <rule_uuid>

. Update triage cases via the

case-management

skill.

Workflow: Create new detection rule

Steps 1–2: Define the threat, data sources, and fields

Specify MITRE ATT&CK technique(s), required data sources (Endpoint, Network, Cloud), and malicious vs legitimate behavior. Common indexes:

logs-endpoint.events.process-*

logs-endpoint.events.network-*

.alerts-security.alerts-*

logs-windows.*

logs-aws.*

. Key fields:

process.name

process.command_line

process.parent.name

destination.ip

winlog.event_id

event.action

. Verify data with

run-query.js

bash

node skills/security/alert-triage/scripts/run-query.js "process.name:certutil.exe" --index "logs-endpoint.events.process-*" --days 30 --size 5

Step 3: Write and test the query

Rule types:

query

(KQL field matching),

eql

(event sequences),

esql

(aggregations),

threshold

(volume-based),

threat_match

(IOC correlation),

new_terms

(first-seen). Test against Elasticsearch before creating:

bash

node skills/security/alert-triage/scripts/run-query.js "process.name:certutil.exe AND process.command_line:(*urlcache* OR *decode*)" \
  --index "logs-endpoint.events.process-*" --days 30

For EQL, use

--query-file

to avoid shell escaping issues.

Validate query syntax before creating or patching a rule. The

validate-query

command catches common errors locally — escaped backslashes, mismatched parentheses, unbalanced quotes, and duplicate boolean operators:

bash

node skills/security/detection-rule-management/scripts/rule-manager.js validate-query \
  --query "process.name:taskkill.exe AND process.command_line:(*chrome.exe* OR *msedge.exe*)" --language kuery

The

create

and

patch

commands also run validation automatically and reject invalid queries. Pass

--skip-validation

only if you are certain the query is correct despite triggering a check.

Common KQL syntax mistakes:

Escaped forward-slashes — KQL wildcards use plain text. Write
```
*/IM chrome.exe*
```
, not
```
*\/IM chrome.exe*
```
.
Mismatched parentheses — every
```
(
```
must have a matching
```
)
```
.
Unbalanced quotes — every
```
"
```
must be paired.
Duplicate operators —
```
AND AND
```
or
```
OR OR
```
is always an error.

Step 4: Create the rule

bash

node skills/security/detection-rule-management/scripts/rule-manager.js create \
  --name "Certutil URL Download or Decode" \
  --description "Detects certutil.exe used to download files or decode Base64 payloads, a common LOLBin technique." \
  --type query \
  --query "process.name:certutil.exe AND process.command_line:(*urlcache* OR *decode*)" \
  --index "logs-endpoint.events.process-*" \
  --severity medium --risk-score 47 \
  --tags "OS:Windows" "Tactic:Defense Evasion" "Tactic:Command and Control" \
  --false-positives "IT administrators using certutil for legitimate certificate operations" \
  --references "https://attack.mitre.org/techniques/T1140/" \
  --interval 5m --disabled

For complex rules (EQL sequences, MITRE mappings, alert suppression), use

create --from-file rule_definition.json

and

--threat-file

. See references/detection-api-reference.md for schema.

Step 5: Monitor and iterate

Monitor alert volume with

noisy-rules --days 3 --top 10

and tune false positives as needed.

Workflow: Endpoint behavior rules tuning

Tune Elastic Endpoint behavior rules by adding Endpoint exceptions scoped to specific rules. Endpoint exceptions live in Security → Exceptions → Endpoint Security Exception List, not under individual SIEM rules.

Key principles: Always fetch the rule definition from protections-artifacts first. Always scope exceptions to the rule (

rule.id

rule.name

). Use full paths over process names. Run the mandatory entity cross-check (Step 4b) before any exception. Simulate impact (Step 5b) and aim for ≥60% noise reduction.

Scripts:

fetch-endpoint-rule-from-github.js

(get rule TOML by id),

add-endpoint-exception.js

(add to Endpoint Exception List; rule.id/rule.name required),

check-exclusion-best-practices.js

For the full step-by-step workflow (Steps 1–6), queries, and simulation templates, see references/endpoint-behavior-tuning-workflow.md. For exclusion best practices, see references/endpoint-rule-exclusion-best-practices.md.

Tool reference

rule-manager.js

All commands are run from the workspace root. All output is JSON unless noted.

Command	Description
`find`	Search/list rules with optional KQL filter
`get`	Get a rule by `--id` or `--rule-id`
`create`	Create a rule (inline flags or `--from-file` )
`patch`	Patch specific fields on a rule
`enable`	Enable a rule
`disable`	Disable a rule
`delete`	Delete a rule
`export`	Export rules as NDJSON
`bulk-action`	Bulk enable/disable/delete/duplicate/edit
`add-exception`	Add an exception item to a rule
`list-exceptions`	List items on an exception list
`create-shared-list`	Create a shared exception list
`noisy-rules`	Find noisiest rules by alert volume
`validate-query`	Check query syntax before create/patch

Endpoint behavior tuning:

fetch-endpoint-rule-from-github.js

(get rule TOML by id),

add-endpoint-exception.js

(add to Endpoint Exception List; rule.id/rule.name required),

check-exclusion-best-practices.js

Exception entry format

Pass entries as

field:operator:value

. Operators:

is

is_not

is_one_of

is_not_one_of

exists

does_not_exist

matches

does_not_match

. Example:

process.name:is:svchost.exe

file.path:matches:C:\\Program Files\\*

Additional resources

For full API schema details, see references/detection-api-reference.md
For endpoint behavior tuning: references/endpoint-exceptions-guide.md, references/endpoint-rule-exclusion-best-practices.md
For alert investigation during tuning, use the
```
alert-triage
```
skill
For documenting tuning actions in cases, use the
```
case-management
```
skill

Examples

"Find the noisiest detection rules from the last 7 days and help me tune one"
"Add an exception to exclude SCCM from the suspicious PowerShell rule"
"Create a new detection rule for certutil URL download or decode"

Guidelines

Report only tool output. When summarizing results, quote or paraphrase only what the tools returned. Do not invent IDs, hostnames, IPs, scores, process trees, or other details not present in the tool response.
Preserve identifiers from the request. If the user provides specific hostnames, agent IDs, case IDs, or other values, use those exact values in tool calls and responses — do not substitute different identifiers.
Confirm actions concisely. After executing a tool, confirm what was done using the tool's return data. Do not fabricate internal IDs, metadata, or status details unless they appear in the tool response.
Distinguish facts from inference. If you draw conclusions beyond what the tools returned (e.g., suggesting a MITRE technique based on observed behavior), clearly label those as your assessment rather than presenting them as tool output.
Start executing tools immediately. Do not read SKILL.md, browse directories, or list files before acting.
Report tool output verbatim. Copy rule IDs, names, alert counts, and error messages exactly as returned. Do not abbreviate UUIDs or round numbers.

Production use

All write operations (
```
create
```
,
```
patch
```
,
```
enable
```
,
```
disable
```
,
```
delete
```
,
```
add-exception
```
,
```
bulk-action
```
,
```
add-endpoint-exception
```
) prompt for confirmation. Pass
```
--yes
```
or
```
-y
```
to skip when called by an agent.
Endpoint exceptions suppress detections globally. Always scope exceptions to a specific rule using
```
rule.id
```
or
```
rule.name
```
in the entries. A broad, unscoped exception can silently reduce detection coverage.
Verify environment variables point to the intended cluster before running any script.
Use
```
--dry-run
```
with
```
bulk-action
```
to preview impact before executing bulk changes.

Environment variables

Variable	Required	Description
`ELASTICSEARCH_URL`	Yes	Elasticsearch URL (for noisy-rules aggregation)
`ELASTICSEARCH_API_KEY`	Yes	Elasticsearch API key
`KIBANA_URL`	Yes	Kibana URL (for rules API)
`KIBANA_API_KEY`	Yes	Kibana API key

security-detection-rule-management

NPX Install

Tags

SKILL.md Content

Detection Rule Management

Execution rules

Prerequisites

Common multi-step workflows

Workflow: Tune a rule for false positives

Steps 1–2: Identify noisy rules and analyze false positives

Step 3: Choose a tuning strategy

Steps 4–5: Apply tuning, verify, and document

Workflow: Create new detection rule

Steps 1–2: Define the threat, data sources, and fields

Step 3: Write and test the query

Step 4: Create the rule

Step 5: Monitor and iterate

Workflow: Endpoint behavior rules tuning

Tool reference

rule-manager.js

Exception entry format

Additional resources

Examples

Guidelines

Production use

Environment variables