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Description

The following analytic identifies high-risk activities within repositories by correlating repository data with risk scores. It leverages risk events 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.

  • Type: Correlation
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Risk
  • Last Updated: 2024-05-24
  • Author: Bhavin Patel
  • ID: 161bc0ca-4651-4c13-9c27-27770660cf67

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1204.003 Malicious Image Execution
T1204 User Execution Execution
Kill Chain Phase
  • Installation
NIST
  • DE.AE
CIS20
  • CIS 10
CVE 


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| 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`

Macros

The SPL above uses the following Macros:

:information_source: risk_rule_for_dev_sec_ops_by_repository_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Required fields

List of fields required to use this analytic.

  • _time

How To Implement

Ensure that all relevant detections in the Dev Sec Ops analytic stories are enabled and are configured to create risk events in Enterprise Security.

Known False Positives

Unknown

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
70.0 70 100 Correlation triggered for repository $risk_object$

:information_source: The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

Reference

Test Dataset

Replay any dataset to Splunk Enterprise by using our replay.py tool or the UI. Alternatively you can replay a dataset into a Splunk Attack Range

source | version: 2