Incident Score: Analysis & Impact (OLL1769784240)
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Rankiteo Score Impact Analysis
Key Highlights From The Incident Analysis
- Timeline of Ollama'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 Ollama 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 Ollama breach identified under incident ID OLL1769784240.
The analysis begins with a detailed overview of Ollama's information like the linkedin page: https://www.linkedin.com/company/ollama, the number of followers: 146140, the industry type: Technology, Information and Internet and the number of employees: 45 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 767 and after the incident was 750 with a difference of -17 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 Ollama and their customers.
Ollama AI Servers recently reported "Global Network of 175,000 Exposed Ollama AI Servers Raises Remote Code Execution Risks", a noteworthy cybersecurity incident.
Researchers have uncovered a vast, unmanaged network of 175,000 publicly exposed Ollama AI servers across 130 countries, posing severe remote code execution (RCE) risks.
The disruption is felt across the environment, affecting 175,000 publicly exposed Ollama AI servers, and exposing Sensitive data extraction via prompt injection attacks.
Formal response steps have not been shared publicly yet.
The case underscores how teams are taking away lessons such as The decentralized nature of these deployments, particularly on home networks, complicates attribution and incident response. Security teams often lack legal or contractual access to mitigate threats. The findings underscore the need for authentication, monitoring, and network controls equivalent to those applied to traditional externally facing infrastructure, and recommending next steps like Implement authentication for Ollama AI servers, Enhance monitoring and network controls and Apply security governance equivalent to traditional infrastructure.
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%), with evidence including 175,000 publicly exposed Ollama AI servers, and vulnerability exploited such as publicly exposed Ollama AI servers without authentication and External Remote Services (T1133) with moderate to high confidence (80%), with evidence including exposed Ollama AI servers across 130 countries, and unauthenticated access to compute power. Under the Execution tactic, the analysis identified Exploitation for Client Execution (T1203) with high confidence (90%), with evidence including remote code execution (RCE) risks, and tool-calling capabilities enabling code execution and Command and Scripting Interpreter (T1059) with moderate to high confidence (80%), supported by evidence indicating aPI access and external system interactions via tool-enabled models. Under the Credential Access tactic, the analysis identified Brute Force: Password Guessing (T1110.001) with moderate confidence (50%), supported by evidence indicating unauthenticated access to exposed servers. Under the Collection tactic, the analysis identified Automated Collection (T1119) with moderate to high confidence (70%), supported by evidence indicating prompt injection attacks to extract sensitive data and Data from Information Repositories (T1213) with moderate to high confidence (70%), supported by evidence indicating tool-enabled models enabling data extraction. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with moderate to high confidence (80%), supported by evidence indicating data exfiltration possible via tool-enabled models and Automated Exfiltration (T1020) with moderate to high confidence (70%), supported by evidence indicating sensitive data extraction via prompt injection attacks. Under the Impact tactic, the analysis identified Resource Hijacking (T1496) with high confidence (90%), supported by evidence indicating unauthenticated access to compute power for malicious activities like spam and Network Denial of Service (T1498) with moderate confidence (60%), supported by evidence indicating potential unauthorized use of compute power for disinformation. Under the Defense Evasion tactic, the analysis identified Impair Defenses: Disable or Modify Tools (T1562.001) with moderate to high confidence (70%), supported by evidence indicating decentralized deployments on home networks complicate attribution and Valid Accounts (T1078) with moderate confidence (50%), supported by evidence indicating unauthenticated access implies lack of account controls. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.
Sources & References
- Ollama Rankiteo Cyber Incident Details: https://www.rankiteo.com/company/ollama/incident/OLL1769784240
- Ollama CyberSecurity Rating page: https://www.rankiteo.com/company/ollama
- Ollama Rankiteo Cyber Incident Blog Article: https://blog.rankiteo.com/oll1769784240-ollama-vulnerability-april-2025/
- Ollama CyberSecurity Score History: https://www.rankiteo.com/company/ollama/history
- Ollama CyberSecurity Incident Source: https://cyberpress.org/175k-exposed-ollama-hosts-allow-remote-code-execution/
- 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