Incident Score: Analysis & Impact (MCK1788385186)
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Rankiteo Score Impact Analysis
Key Highlights From The Incident Analysis
- Timeline of McKesson'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 McKesson 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 McKesson breach identified under incident ID MCK1788385186.
The analysis begins with a detailed overview of McKesson's information like the linkedin page: https://www.linkedin.com/company/mckesson, the number of followers: 611876, the industry type: Hospitals and Health Care and the number of employees: 25352 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 833 and after the incident was 816 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 McKesson and their customers.
McKesson recently reported "McKesson Confirms Data Theft in Cyberattack Targeting Third-Party Cloud Applications", a noteworthy cybersecurity incident.
McKesson, a major U.S.
The disruption is felt across the environment, affecting Third-party cloud applications, and exposing Yes.
Formal response steps have not been shared publicly yet.
The case underscores how Ongoing (no evidence of ongoing unauthorized activity, but full scope not independently verified), teams are taking away lessons such as The incident underscores the risks posed by healthcare intermediaries and the stealthy nature of account takeovers, which can extract data without immediate disruption. It highlights vulnerabilities in healthcare’s reliance on interconnected third-party platforms and the difficulty in detecting anomalous activity when attackers use legitimate 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 Phishing: Voice Phishing (T1566.004) with high confidence (90%), supported by evidence indicating adversaries use social engineering, including voice phishing and Valid Accounts (T1078) with high confidence (95%), supported by evidence indicating exploit legitimate credentials to move undetected through systems. Under the Credential Access tactic, the analysis identified Brute Force: Password Guessing (T1110.001) with moderate confidence (50%), supported by evidence indicating compromise employee accounts (implied via social engineering) and Credentials from Password Stores (T1555) with moderate confidence (60%), supported by evidence indicating accessing sensitive data tied to the compromised user’s permissions. Under the Lateral Movement tactic, the analysis identified Remote Services: Cloud Services (T1021.007) with moderate to high confidence (80%), supported by evidence indicating unauthorized access to third-party cloud applications and Valid Accounts (T1078) with high confidence (90%), supported by evidence indicating attackers exploit legitimate credentials to move undetected. Under the Collection tactic, the analysis identified Data from Cloud Storage (T1213.003) with high confidence (90%), supported by evidence indicating data theft in cyberattack involving third-party cloud applications and Data from Local System (T1005) with moderate to high confidence (70%), supported by evidence indicating accessing sensitive data tied to the compromised user’s permissions. Under the Exfiltration tactic, the analysis identified Transfer Data to Cloud Account (T1537) with moderate to high confidence (80%), supported by evidence indicating data theft in cyberattack involving third-party cloud applications and Exfiltration Over C2 Channel (T1041) with moderate to high confidence (70%), supported by evidence indicating resulting in data theft (claimed by ShinyHunters). Under the Defense Evasion tactic, the analysis identified Valid Accounts (T1078) with high confidence (90%), supported by evidence indicating attackers exploit legitimate credentials to move undetected and Hide Artifacts: Email Hiding Rules (T1564.008) with moderate confidence (50%), supported by evidence indicating such activity often appears normal, making detection difficult. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.
Sources & References
- McKesson Rankiteo Cyber Incident Details: https://www.rankiteo.com/company/mckesson/incident/MCK1788385186
- McKesson CyberSecurity Rating page: https://www.rankiteo.com/company/mckesson
- McKesson Rankiteo Cyber Incident Blog Article: https://blog.rankiteo.com/mck1788385186-mckesson-cyber-attack-january-2025/
- McKesson CyberSecurity Score History: https://www.rankiteo.com/company/mckesson/history
- McKesson CyberSecurity Incident Source: https://www.healthcaredive.com/news/mckesson-confirms-data-theft-cyberattack-involving-third-party-apps/829435/
- 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