Incident Score: Analysis & Impact (SPOMITSPL1767777752)
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Rankiteo Score Impact Analysis
Key Highlights From The Incident Analysis
- Timeline of Splunk's Vulnerability and lateral movement inside company's environment.
- Overview of affected data sets, including SSNs and PHI, and why they materially increase incident severity.
- How Rankiteo’s incident engine converts technical details into a normalized incident score.
- How this cyber incident impacts Splunk Rankiteo cyber scoring and cyber rating.
- Rankiteo’s MITRE ATT&CK correlation analysis for this incident, with associated confidence level.
Full Incident Analysis Transcript
In this Rankiteo incident briefing, we review the Splunk breach identified under incident ID SPOMITSPL1767777752.
The analysis begins with a detailed overview of Splunk's information like the linkedin page: https://www.linkedin.com/company/splunk, the number of followers: 772636, the industry type: Software Development and the number of employees: 9686 employees
After the initial compromise, the video explains how Rankiteo's incident engine converts technical details into a normalized incident score. The incident score before the incident was 787 and after the incident was 782 with a difference of -5 which is could be a good indicator of the severity and impact of the incident.
In the next step of the video, we will analyze in more details the incident and the impact it had on Splunk and their customers.
Spotipy (Spotify Web API Python Library) recently reported "GitHub Repositories Vulnerable to Hijacking via Insecure pull_request_target Workflows", a noteworthy cybersecurity incident.
Sysdig researchers warned that developers and maintainers could leave their GitHub repositories open to hijacking due to inadequately secured workflows, specifically the misuse of the pull_request_target trigger event in GitHub Actions.
The disruption is felt across the environment, affecting GitHub repositories with misconfigured workflows, and exposing Repository secrets (e.g., GITHUB_TOKEN), potentially other sensitive data.
In response, moved swiftly to contain the threat with measures like Flaws were fixed by the respective maintainers (Spotify, Mitre, Splunk), and began remediation that includes Correcting misconfigured GitHub Actions workflows to prevent secret exfiltration.
The case underscores how Ongoing (additional findings to be disclosed after remediation), teams are taking away lessons such as Maintainers must fully understand the security implications of GitHub Actions workflows, particularly pull_request_target, and use them with caution. Misconfigurations can lead to severe security risks, including repository takeover, and recommending next steps like Audit GitHub Actions workflows for insecure use of pull_request_target, Limit GITHUB_TOKEN permissions to the minimum required and Use pull_request_target only when absolutely necessary and with proper safeguards.
Finally, we try to match the incident with the MITRE ATT&CK framework to see if there is any correlation between the incident and the MITRE ATT&CK framework.
The MITRE ATT&CK framework is a knowledge base of techniques and sub-techniques that are used to describe the tactics and procedures of cyber adversaries. It is a powerful tool for understanding the threat landscape and for developing effective defense strategies.
MITRE ATT&CK® Correlation Analysis
Rankiteo's analysis has identified several MITRE ATT&CK tactics and techniques associated with this incident, each with varying levels of confidence based on available evidence. Under the Initial Access tactic, the analysis identified Supply Chain Compromise: Compromise Software Dependencies and Development Tools (T1195.001) with high confidence (90%), supported by evidence indicating misconfigured GitHub Actions workflows (pull_request_target) exploited and Trusted Relationship (T1199) with moderate to high confidence (80%), supported by evidence indicating attackers hijack projects via insecure workflows in trusted repositories. Under the Execution tactic, the analysis identified Serverless Execution (T1648) with moderate to high confidence (80%), supported by evidence indicating malicious code executed via GitHub Actions workflows (pull_request_target) and User Execution: Malicious File (T1204.002) with moderate to high confidence (70%), supported by evidence indicating attackers inject malicious code into untrusted pull requests. Under the Privilege Escalation tactic, the analysis identified Abuse Elevation Control Mechanism: Setuid and Setgid (T1548.001) with moderate confidence (60%), supported by evidence indicating gITHUB_TOKEN with write permissions accessed via misconfigured workflows and Valid Accounts (T1078) with high confidence (90%), supported by evidence indicating gITHUB_TOKEN exploited for elevated privileges in repositories. Under the Credential Access tactic, the analysis identified Unsecured Credentials: Credentials In Files (T1552.001) with high confidence (90%), supported by evidence indicating repository secrets (e.g., GITHUB_TOKEN) exfiltrated via workflows and Credentials from Password Stores (T1555) with moderate to high confidence (70%), supported by evidence indicating secrets accessed via misconfigured pull_request_target workflows. Under the Lateral Movement tactic, the analysis identified Use Alternate Authentication Material: Application Access Token (T1550.001) with moderate to high confidence (80%), supported by evidence indicating gITHUB_TOKEN used to move laterally within repositories. Under the Collection tactic, the analysis identified Data from Code Repositories (T1213.003) with high confidence (90%), supported by evidence indicating repository secrets and sensitive data collected via workflows. Under the Exfiltration tactic, the analysis identified Transfer Data to Cloud Account (T1537) with moderate to high confidence (80%), supported by evidence indicating secrets exfiltrated in proof-of-concept attacks and Exfiltration Over C2 Channel (T1041) with moderate to high confidence (70%), supported by evidence indicating attackers could exfiltrate secrets via malicious workflows. Under the Impact tactic, the analysis identified Data Destruction (T1485) with moderate confidence (50%), supported by evidence indicating potential unauthorized code modifications in main branch and Network Denial of Service (T1498) with lower confidence (40%), supported by evidence indicating repository takeover could disrupt development operations. Under the Defense Evasion tactic, the analysis identified Hide Artifacts: Hidden Window (T1564.003) with moderate confidence (60%), supported by evidence indicating malicious code executed via legitimate GitHub Actions workflows and Valid Accounts (T1078) with moderate to high confidence (80%), supported by evidence indicating gITHUB_TOKEN used to evade detection in workflows. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.
Sources & References
- Splunk Rankiteo Cyber Incident Details: https://www.rankiteo.com/company/splunk/incident/SPOMITSPL1767777752
- Splunk CyberSecurity Rating page: https://www.rankiteo.com/company/splunk
- Splunk Rankiteo Cyber Incident Blog Article: https://blog.rankiteo.com/spomitspl1767777752-vulnerability-june-2025/
- Splunk CyberSecurity Score History: https://www.rankiteo.com/company/splunk/history
- Splunk CyberSecurity Incident Source: https://devclass.com/2025/06/18/misconfigured-github-actions-could-leave-repos-and-secrets-exposed-sysdig-finds/
- Rankiteo A.I CyberSecurity Rating methodology: https://www.rankiteo.com/Images/rankiteo_algo.pdf
- Rankiteo TPRM Scoring methodology: https://static.rankiteo.com/model/rankiteo_tprm_methodology.pdf