Incident Score: Analysis & Impact (N26REV1776860884)
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 Revolut'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 Revolut 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 Revolut breach identified under incident ID N26REV1776860884.
The analysis begins with a detailed overview of Revolut's information like the linkedin page: https://www.linkedin.com/company/revolut, the number of followers: 1698237, the industry type: Financial Services and the number of employees: 15697 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 764 and after the incident was 725 with a difference of -39 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 Revolut and their customers.
Revolut recently reported "French Freelancer Fintech Accounts Exploited for Large-Scale Money Laundering", a noteworthy cybersecurity incident.
Cybercriminals are increasingly hijacking French freelancer fintech accounts to launder stolen funds at high speed, often moving money within minutes before banks or victims detect the fraud.
The disruption is felt across the environment, affecting Fintech platforms (Revolut, Wise, N26), Payment rails (SEPA), and exposing French personal data, Freelancer account credentials, plus an estimated financial loss of €2.5 billion (2024 EEA credit transfer fraud).
Formal response steps have not been shared publicly yet.
The case underscores how teams are taking away lessons such as Fintech platforms must monitor freelancer accounts as part of broader fraud networks, not just individual users. Detection requires linking signals across the full account lifecycle, including infrastructure, subnet continuity, and cross-account connections, and recommending next steps like Enhance KYC processes, implement continuous monitoring of account behavior, and improve cross-platform fraud detection to identify industrial-scale mule account operations.
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 (T1566) with high confidence (90%), supported by evidence indicating phishing sites and fake financial services (e.g., bogus mortgage portals) and Valid Accounts (T1078) with high confidence (90%), with evidence including hijacking French freelancer fintech accounts, and verified freelancer accounts transferred to fraud rings. Under the Resource Development tactic, the analysis identified Acquire Infrastructure: Domains (T1583.001) with moderate to high confidence (80%), supported by evidence indicating phishing sites and fake financial services (e.g., bogus mortgage portals), Acquire Infrastructure: Web Services (T1583.006) with moderate to high confidence (70%), supported by evidence indicating sIM modem farms to generate French IP addresses and phone numbers, and Obtain Capabilities: Tool (T1588.002) with moderate to high confidence (80%), supported by evidence indicating sIM modem farms used to rotate connections and evade detection. Under the Credential Access tactic, the analysis identified Compromise Accounts (T1586) with high confidence (90%), supported by evidence indicating identity Harvesting such as Phishing sites collect real French personal data and Brute Force (T1110) with moderate confidence (50%), supported by evidence indicating accounts are transferred to fraud rings via mobile apps. Under the Defense Evasion tactic, the analysis identified Valid Accounts (T1078) with high confidence (90%), supported by evidence indicating accounts appear compliant to fintech platforms after social engineering KYC, Modify Authentication Process (T1556) with moderate to high confidence (70%), supported by evidence indicating victims tricked into completing verification (social engineering KYC), and Proxy (T1090) with moderate to high confidence (80%), supported by evidence indicating sIM modem farms to rotate French IP addresses and phone numbers. Under the Collection tactic, the analysis identified Gather Victim Identity Information (T1589) with high confidence (90%), supported by evidence indicating identity Harvesting such as Phishing sites collect real French personal data and Data from Information Repositories (T1213) with moderate to high confidence (70%), supported by evidence indicating french personal data, Freelancer account credentials compromised. Under the Command and Control tactic, the analysis identified Proxy (T1090) with moderate to high confidence (80%), supported by evidence indicating sIM modem farms to rotate connections and evade detection. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with moderate to high confidence (80%), supported by evidence indicating stolen funds moved within minutes before detection and Exfiltration Over Web Service (T1567) with moderate to high confidence (70%), supported by evidence indicating cross-border transfers under guise of legitimate business activity. Under the Impact tactic, the analysis identified Resource Hijacking (T1496) with high confidence (90%), supported by evidence indicating hijacking French freelancer fintech accounts for money laundering and Financial Theft (T1657) with high confidence (90%), supported by evidence indicating €2.5 billion credit transfer fraud in EEA (2024). These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.
Sources & References
- Revolut Rankiteo Cyber Incident Details: https://www.rankiteo.com/company/revolut/incident/N26REV1776860884
- Revolut CyberSecurity Rating page: https://www.rankiteo.com/company/revolut
- Revolut Rankiteo Cyber Incident Blog Article: https://blog.rankiteo.com/n26rev1776860884-n26-revolut-cyber-attack-january-2024/
- Revolut CyberSecurity Score History: https://www.rankiteo.com/company/revolut/history
- Revolut CyberSecurity Incident Source: https://gbhackers.com/french-fintech-accounts/
- 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