Incident Score: Analysis & Impact (LIT1777472744)
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Rankiteo Score Impact Analysis
Key Highlights From The Incident Analysis
- Timeline of LiteLLM'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 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 LIT1777472744.
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 308 and after the incident was 303 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 LiteLLM and their customers.
On 20 April 2024, LiteLLM disclosed SQL Injection issues under the banner "Critical SQL Injection Flaw in LiteLLM Exploited Within Days of Disclosure".
A critical SQL injection vulnerability (CVE-2026-42208, CVSS 9.3) in the open-source AI gateway LiteLLM was exploited just 36 hours after public disclosure, allowing attackers to access sensitive database tables.
The disruption is felt across the environment, affecting LiteLLM AI gateway, and exposing API keys, provider credentials, environment variable configurations.
In response, moved swiftly to contain the threat with measures like Patch released (version 1.83.7), recommendation to disable error logs, and began remediation that includes Update to patched version 1.83.7, and stakeholders are being briefed through Public advisory on April 20, user notifications.
The case underscores how Completed, teams are taking away lessons such as Automated exploitation can occur rapidly after vulnerability disclosure; proper input sanitization is critical for API security, and recommending next steps like Update to patched versions immediately, disable error logs if unable to patch, monitor for unauthorized database access, with advisories going out to stakeholders covering Users urged to update to version 1.83.7 or disable error logs.
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 Exploit Public-Facing Application (T1190) with high confidence (90%), supported by evidence indicating critical SQL injection flaw in LiteLLM exploited within days of disclosure. Under the Execution tactic, the analysis identified Exploitation for Client Execution (T1203) with moderate to high confidence (80%), supported by evidence indicating unauthenticated API requests with malicious Authorization headers. Under the Credential Access tactic, the analysis identified Unsecured Credentials: Credentials In Files (T1552.001) with high confidence (90%), supported by evidence indicating aPI keys, provider credentials, and environment variable configurations exposed and Credentials from Password Stores (T1555) with moderate to high confidence (80%), supported by evidence indicating access to proxy’s database via error-handling paths. Under the Discovery tactic, the analysis identified System Information Discovery (T1082) with moderate to high confidence (80%), supported by evidence indicating attackers used column-count discovery techniques to enumerate database schema and Network Service Discovery (T1046) with moderate to high confidence (70%), supported by evidence indicating automated exploitation attempts targeting PostgreSQL tables. Under the Defense Evasion tactic, the analysis identified Impair Defenses: Disable or Modify Tools (T1562.001) with moderate confidence (60%), supported by evidence indicating recommendation to disable error logs to mitigate risk and Direct Volume Access (T1006) with moderate to high confidence (70%), supported by evidence indicating bypassing authentication entirely via error-handling paths. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with moderate confidence (50%), supported by evidence indicating no confirmed data compromise, but credentials were exposed. 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/LIT1777472744
- LiteLLM CyberSecurity Rating page: https://www.rankiteo.com/company/litellm
- LiteLLM Rankiteo Cyber Incident Blog Article: https://blog.rankiteo.com/lit1777472744-litellm-vulnerability-april-2026/
- LiteLLM CyberSecurity Score History: https://www.rankiteo.com/company/litellm/history
- LiteLLM CyberSecurity Incident Source: https://www.securityweek.com/fresh-litellm-vulnerability-exploited-shortly-after-disclosure/
- 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