Detection rules › Splunk

Risk Rule for Dev Sec Ops by Repository

Status
production
Severity
informational
Group by
All_Risk.annotations.mitre_attack.mitre_tactic, All_Risk.risk_object, All_Risk.risk_object_type
Author
Bhavin Patel
Source
github.com/splunk/security_content

The following analytic identifies high-risk activities within repositories by correlating repository data with risk scores. It leverages findings and intermediate findings created by detections from the Dev Sec Ops analytic stories, summing risk scores and capturing source and user information. The detection focuses on high-risk scores above 100 and sources with more than three occurrences. This activity is significant as it highlights repositories frequently targeted by threats, providing insights into potential vulnerabilities. If confirmed malicious, attackers could exploit these repositories, leading to data breaches or infrastructure compromise.

MITRE ATT&CK coverage

Rule body splunk

name: Risk Rule for Dev Sec Ops by Repository
id: 161bc0ca-4651-4c13-9c27-27770660cf67
version: 12
creation_date: '2023-11-16'
modification_date: '2026-05-13'
author: Bhavin Patel
status: production
type: Correlation
description: The following analytic identifies high-risk activities within repositories by correlating repository data with risk scores. It leverages findings and intermediate findings created by detections from the Dev Sec Ops analytic stories, summing risk scores and capturing source and user information. The detection focuses on high-risk scores above 100 and sources with more than three occurrences. This activity is significant as it highlights repositories frequently targeted by threats, providing insights into potential vulnerabilities. If confirmed malicious, attackers could exploit these repositories, leading to data breaches or infrastructure compromise.
data_source: []
search: |-
    | tstats `security_content_summariesonly` min(_time) as firstTime max(_time) as lastTime sum(All_Risk.calculated_risk_score) as sum_risk_score, values(All_Risk.annotations.mitre_attack.mitre_tactic) as annotations.mitre_attack.mitre_tactic, values(All_Risk.annotations.mitre_attack.mitre_technique_id) as annotations.mitre_attack.mitre_technique_id, dc(All_Risk.annotations.mitre_attack.mitre_technique_id) as mitre_technique_id_count values(source) as source, dc(source) as source_count FROM datamodel=Risk.All_Risk
      WHERE All_Risk.analyticstories="Dev Sec Ops" All_Risk.risk_object_type = "other"
      BY All_Risk.risk_object All_Risk.risk_object_type All_Risk.annotations.mitre_attack.mitre_tactic
    | `drop_dm_object_name(All_Risk)`
    | `security_content_ctime(firstTime)`
    | `security_content_ctime(lastTime)`
    | where source_count > 3 and sum_risk_score > 100
    | `risk_rule_for_dev_sec_ops_by_repository_filter`
how_to_implement: Ensure that all relevant detections in the Dev Sec Ops analytic stories are enabled and are configured to create findings or intermediate findings in Enterprise Security.
known_false_positives: No false positives have been identified at this time.
references: []
drilldown_searches:
    - name: View the detection results for - "$risk_object$"
      search: '%original_detection_search% | search  risk_object = "$risk_object$"'
      earliest_offset: $info_min_time$
      latest_offset: $info_max_time$
    - name: View risk events for the last 7 days for - "$risk_object$"
      search: '| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$risk_object$") | stats count min(_time) as firstTime max(_time) as lastTime values(search_name) as "Search Name" values(risk_message) as "Risk Message" values(analyticstories) as "Analytic Stories" values(annotations._all) as "Annotations" values(annotations.mitre_attack.mitre_tactic) as "ATT&CK Tactics" by normalized_risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`'
      earliest_offset: 7d
      latest_offset: "0"
finding:
    title: Risk Threshold Exceeded for $risk_object$
    entity:
        field: risk_object
        type: other
        score: 0
analytic_story:
    - Dev Sec Ops
asset_type: Amazon Elastic Container Registry
mitre_attack_id:
    - T1204.003
product:
    - Splunk Enterprise
    - Splunk Enterprise Security
    - Splunk Cloud
category: cloud
security_domain: threat
tests:
    - name: True Positive Test
      attack_data:
        - data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1204.003/risk_dataset/aws_ecr_risk_dataset.log
          source: aws_ecr_risk_dataset.log
          sourcetype: stash
      test_type: unit

Stages and Predicates

Stage 1: tstats

| tstats `security_content_summariesonly` min(_time) as firstTime max(_time) as lastTime sum(All_Risk.calculated_risk_score) as sum_risk_score, values(All_Risk.annotations.mitre_attack.mitre_tactic) as annotations.mitre_attack.mitre_tactic, values(All_Risk.annotations.mitre_attack.mitre_technique_id) as annotations.mitre_attack.mitre_technique_id, dc(All_Risk.annotations.mitre_attack.mitre_technique_id) as mitre_technique_id_count values(source) as source, dc(source) as source_count FROM datamodel=Risk.All_Risk
  WHERE All_Risk.analyticstories="Dev Sec Ops" All_Risk.risk_object_type = "other"
  BY All_Risk.risk_object All_Risk.risk_object_type All_Risk.annotations.mitre_attack.mitre_tactic

Stage 2: search

| `drop_dm_object_name(All_Risk)`

Stage 3: search

| `security_content_ctime(firstTime)`

Stage 4: search

| `security_content_ctime(lastTime)`

Stage 5: where

| where source_count > 3 and sum_risk_score > 100

Stage 6: search

| `risk_rule_for_dev_sec_ops_by_repository_filter`

Indicators

Each row is a field, operator, and value that the rule matches. The corpus column counts how many other rules in the catalog look for the same combination: high numbers point to widely-used, community-vetted indicators. Blank or 1 shows that the indicator is specific to this rule.