Incident Score: Analysis & Impact (BERLIT1774384560)
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Rankiteo Score Impact Analysis
Key Highlights From The Incident Analysis
- Timeline of LiteLLM's Cyber Attack 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 LiteLLM 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 LiteLLM breach identified under incident ID BERLIT1774384560.
The analysis begins with a detailed overview of LiteLLM's information like the linkedin page: https://www.linkedin.com/company/litellm, the number of followers: 8480, the industry type: Software Development and the number of employees: 7 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 628 and after the incident was 607 with a difference of -21 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 LiteLLM and their customers.
LiteLLM recently reported "Malicious Code Injection in LiteLLM Leads to PyPI Removal", a noteworthy cybersecurity incident.
Two versions of LiteLLM (v1.82.7 and v1.82.8), an open-source interface for accessing multiple large language models, were removed from the Python Package Index (PyPI) after a supply chain attack inserted credential-stealing malware into the package.
The disruption is felt across the environment, affecting LiteLLM package (v1.82.7, v1.82.8) and Trivy (v0.69.4, v0.69.5, v0.69.6), and exposing Credentials (PYPI_PUBLISH token).
In response, moved swiftly to contain the threat with measures like PyPI package removal and Token revocation, and began remediation that includes Rotating all PyPI publishing tokens, Evaluating JWT-based trusted publishing and Migrating to a new PyPI account, and stakeholders are being briefed through Security advisory issued by PyPA.
The case underscores how Ongoing, and recommending next steps like Rotate all secrets accessible to affected environments, Use JWT-based trusted publishing for PyPI and Pin commits in CI/CD pipelines instead of version tags, with advisories going out to stakeholders covering PyPA security advisory warning users to rotate credentials.
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 supply chain attack inserted credential-stealing malware into the package and Trusted Relationship (T1199) with moderate to high confidence (80%), supported by evidence indicating exploited a misconfiguration in Trivy, used in LiteLLM’s CI/CD pipeline. Under the Execution tactic, the analysis identified Serverless Execution (T1648) with moderate to high confidence (70%), supported by evidence indicating malicious code executed undetected in CI/CD pipeline via version tags. Under the Credential Access tactic, the analysis identified Steal Application Access Token (T1528) with high confidence (95%), supported by evidence indicating stole a privileged access token from Trivy’s GitHub Actions environment and Unsecured Credentials: Credentials In Files (T1552.001) with high confidence (90%), supported by evidence indicating pYPI_PUBLISH token stored as an .env variable in GitHub repository. Under the Persistence tactic, the analysis identified Compromise Client Software Binary (T1554) with moderate to high confidence (80%), supported by evidence indicating published malicious versions of Trivy and LiteLLM on PyPI/DockerHub. Under the Defense Evasion tactic, the analysis identified Masquerading: Match Legitimate Name or Location (T1036.005) with moderate to high confidence (85%), supported by evidence indicating modified existing version tags in GitHub Action scripts to inject malware and Subvert Trust Controls: Code Signing (T1553.002) with moderate to high confidence (70%), supported by evidence indicating used stolen PYPI_PUBLISH token to bypass 2FA and push compromised versions. Under the Collection tactic, the analysis identified Data from Code Repositories (T1213.003) with moderate to high confidence (80%), supported by evidence indicating stole PYPI_PUBLISH token from GitHub repository .env variable. Under the Exfiltration tactic, the analysis identified Transfer Data to Cloud Account (T1537) with moderate to high confidence (70%), supported by evidence indicating credential-stealing malware implies exfiltration of stolen tokens. Under the Impact tactic, the analysis identified Defacement: Internal Defacement (T1491.001) with moderate confidence (60%), supported by evidence indicating spam attack on GitHub vulnerability report to obscure updates and Service Stop (T1489) with moderate to high confidence (70%), supported by evidence indicating liteLLM versions removed from PyPI due to compromise. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.
Sources & References
- LiteLLM Rankiteo Cyber Incident Details: https://www.rankiteo.com/company/litellm/incident/BERLIT1774384560
- LiteLLM CyberSecurity Rating page: https://www.rankiteo.com/company/litellm
- LiteLLM Rankiteo Cyber Incident Blog Article: https://blog.rankiteo.com/berlit1774384560-litellm-berri-ai-cyber-attack-march-2026/
- LiteLLM CyberSecurity Score History: https://www.rankiteo.com/company/litellm/history
- LiteLLM CyberSecurity Incident Source: https://www.theregister.com/2026/03/24/trivy_compromise_litellm/
- 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