Incident Score: Analysis & Impact (AST1774045431)
The details regarding individual company incidents & reports gives you full view from every side.
Rankiteo Score Impact Analysis
Key Highlights From The Incident Analysis
- Timeline of AstraZeneca's Breach 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 AstraZeneca 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 AstraZeneca breach identified under incident ID AST1774045431.
The analysis begins with a detailed overview of AstraZeneca's information like the linkedin page: https://www.linkedin.com/company/astrazeneca, the number of followers: 3722569, the industry type: Pharmaceutical Manufacturing and the number of employees: 78683 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 812 and after the incident was 783 with a difference of -29 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 AstraZeneca and their customers.
AstraZeneca recently reported "LAPSUS$ Claims AstraZeneca Data Breach, Leaks 3GB of Sensitive Internal Data", a noteworthy cybersecurity incident.
The threat actor group LAPSUS$ has claimed responsibility for a data breach targeting AstraZeneca, allegedly yielding 3GB of internal data including source code, cloud infrastructure configurations, employee records, and access credentials.
The disruption is felt across the environment, affecting GitHub Enterprise, Cloud infrastructure (AWS, Azure) and Internal databases, and exposing 3GB of internal data.
Formal response steps have not been shared publicly yet.
The case underscores how Unverified (AstraZeneca has not confirmed the breach).
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 Valid Accounts (T1078) with moderate to high confidence (80%), with evidence including access credentials allegedly stolen, and gitHub usernames, roles (including Owner privileges) and Exploit Public-Facing Application (T1190) with moderate confidence (50%), supported by evidence indicating cloud infrastructure configurations (AWS, Azure) compromised. Under the Credential Access tactic, the analysis identified Steal Application Access Token (T1528) with moderate to high confidence (70%), supported by evidence indicating private keys, vault data allegedly stolen and OS Credential Dumping (T1003) with moderate confidence (60%), supported by evidence indicating access credentials allegedly stolen. Under the Discovery tactic, the analysis identified Account Discovery (T1087) with high confidence (90%), supported by evidence indicating gitHub Enterprise User Data such as employee names, GitHub usernames, roles, File and Directory Discovery (T1083) with moderate to high confidence (70%), supported by evidence indicating source code (Java, Angular, Python) allegedly stolen, and Cloud Infrastructure Discovery (T1580) with moderate to high confidence (80%), supported by evidence indicating cloud infrastructure configurations (AWS, Azure, Terraform) allegedly stolen. Under the Collection tactic, the analysis identified Data from Local System (T1005) with moderate to high confidence (80%), supported by evidence indicating 3GB of internal data including source code, employee records and Data from Information Repositories (T1213) with high confidence (90%), supported by evidence indicating gitHub Enterprise User Data such as employee names, roles, 2FA status. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with moderate to high confidence (80%), supported by evidence indicating 3GB of data allegedly stolen and shared in .tar.gz format and Exfiltration Over Web Service (T1567) with moderate to high confidence (70%), supported by evidence indicating data being sold on hacker forums. Under the Impact tactic, the analysis identified Data Encrypted for Impact (T1486) with lower confidence (30%), supported by evidence indicating no direct evidence of encryption, but data sold for financial gain. Under the Defense Evasion tactic, the analysis identified Hide Artifacts (T1564) with moderate confidence (60%), supported by evidence indicating data shared in .tar.gz format to obscure contents. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.
Sources & References
- AstraZeneca Rankiteo Cyber Incident Details: https://www.rankiteo.com/company/astrazeneca/incident/AST1774045431
- AstraZeneca CyberSecurity Rating page: https://www.rankiteo.com/company/astrazeneca
- AstraZeneca Rankiteo Cyber Incident Blog Article: https://blog.rankiteo.com/ast1774045431-astrazeneca-breach-march-2026/
- AstraZeneca CyberSecurity Score History: https://www.rankiteo.com/company/astrazeneca/history
- AstraZeneca CyberSecurity Incident Source: https://hackread.com/hacker-group-lapsus-astrazeneca-data-breach/
- 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