Rankiteo Logo
Rankiteo
Leader in Cyber Underwriting
Loading...
NEWRankiteo Cyber Underwriting Desktop - Score, price, and bind from your desktop
WindowsmacOSLinux
Download
Analyze » UK Biobank » UK-1777184662

Incident Score: Analysis & Impact (UK-1777184662)

The details regarding individual company incidents & reports gives you full view from every side.

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-62
Company Score Before Incident753 / 1000
Company Score After Incident691 / 1000
INCIDENT NUMBERUK-1777184662
Type of Cyber IncidentBreach
ATTACK VECTORUnauthorized data sale by vetted researchers
DATA EXPOSEDAnonymized participant data (genetic, health,...
INCIDENT DATE31/12/2023
STATUSpublished

Key Highlights From The Incident Analysis

  • Timeline of UK Biobank'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 UK Biobank 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 UK Biobank breach identified under incident ID UK-1777184662.

The analysis begins with a detailed overview of UK Biobank's information like the linkedin page: https://www.linkedin.com/company/uk-biobank, the number of followers: 25895, the industry type: Research Services and the number of employees: 275 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 753 and after the incident was 691 with a difference of -62 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 UK Biobank and their customers.

UK Biobank recently reported "UK Biobank Data Security Breach", a noteworthy cybersecurity incident.

UK Biobank faced a significant data security incident after researchers linked to three Chinese academic institutions attempted to sell anonymized participant data online.

The disruption is felt across the environment, and exposing Anonymized participant data (genetic, health, and lifestyle data).

In response, teams activated the incident response plan, moved swiftly to contain the threat with measures like Banned the institutions, enlisted diplomatic support to remove listings, and began remediation that includes Tightened data access protocols, automated monitoring for unauthorized data exposure.

The case underscores how teams are taking away lessons such as Balancing scientific progress with data protection is challenging; 'rogue researcher' misuse is an underaddressed threat; legacy open-access models pose vulnerabilities, and recommending next steps like Restrict data access to cloud-based analysis, enhance automated monitoring, and address 'rogue researcher' risks.

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 high confidence (90%), supported by evidence indicating vetted researchers listing datasets on Alibaba-owned e-commerce platforms. Under the Exfiltration tactic, the analysis identified Transfer Data to Cloud Account (T1537) with moderate to high confidence (80%), supported by evidence indicating researchers attempted to sell anonymized participant data online and Exfiltration Over C2 Channel (T1041) with moderate to high confidence (70%), supported by evidence indicating data breach involving genetic, health, and lifestyle data from 500,000+ volunteers. Under the Credential Access tactic, the analysis identified Unsecured Credentials: Credentials In Files (T1552.001) with moderate confidence (60%), supported by evidence indicating inadvertent exposure of raw data through published code on platforms like GitHub. Under the Collection tactic, the analysis identified Data from Information Repositories (T1213) with high confidence (90%), supported by evidence indicating uK Biobank holds nearly 40 petabytes of genetic, health, and lifestyle data. Under the Defense Evasion tactic, the analysis identified Hide Artifacts: Hidden Files and Directories (T1564.001) with moderate confidence (50%), supported by evidence indicating anonymized participant data listed for sale online. Under the Impact tactic, the analysis identified Defacement: Internal Defacement (T1491.001) with lower confidence (40%), supported by evidence indicating brand reputation impact such as risks in medical research collaboration and Data Manipulation: Stored Data Manipulation (T1565.001) with lower confidence (30%), supported by evidence indicating re-identification risk of anonymized datasets. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.

Initial Access
Valid Accounts (90%)
Exfiltration
Transfer Data to Cloud Account (80%)
Exfiltration Over C2 Channel (70%)
Credential Access
Unsecured Credentials: Credentials In Files (60%)
Collection
Data from Information Repositories (90%)
Defense Evasion
Hide Artifacts: Hidden Files and Directories (50%)
Impact
Defacement: Internal Defacement (40%)
Data Manipulation: Stored Data Manipulation (30%)

Sources & References