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Analyze » INTERPOL » INT1774362377

Incident Score: Analysis & Impact (INT1774362377)

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

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-210
Company Score Before Incident753 / 1000
Company Score After Incident543 / 1000
INCIDENT NUMBERINT1774362377
Type of Cyber IncidentRansomware
ATTACK VECTORExploited vulnerabilities in computer networks
DATA EXPOSEDVictims' data encrypted and exfiltrated
INCIDENT DATE31/10/2025
STATUSResolved (sentencing completed)

Key Highlights From The Incident Analysis

  • Timeline of INTERPOL's Ransomware 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 INTERPOL 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 INTERPOL breach identified under incident ID INT1774362377.

The analysis begins with a detailed overview of INTERPOL's information like the linkedin page: https://www.linkedin.com/company/interpol, the number of followers: 534650, the industry type: Law Enforcement and the number of employees: 2214 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 543 with a difference of -210 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 INTERPOL and their customers.

A newly reported cybersecurity incident, "Russian Cybercriminal Sentenced for Enabling $24M in Ransomware Attacks", has drawn attention.

Aleksei Volkov, a Russian national, was sentenced to 81 months in U.S.

The disruption is felt across the environment, and exposing Victims' data encrypted and exfiltrated, plus an estimated financial loss of $9 million (actual losses), $24 million (intended damages).

Formal response steps have not been shared publicly yet.

The case underscores how Resolved (sentencing completed).

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%), supported by evidence indicating exploited vulnerabilities in computer networks and External Remote Services (T1133) with moderate to high confidence (70%), supported by evidence indicating gained unauthorized access to computer networks. Under the Persistence tactic, the analysis identified Valid Accounts (T1078) with moderate confidence (60%), supported by evidence indicating sold access to ransomware groups (implied persistence). Under the Privilege Escalation tactic, the analysis identified Exploitation for Privilege Escalation (T1068) with moderate to high confidence (70%), supported by evidence indicating exploited vulnerabilities in computer networks. Under the Defense Evasion tactic, the analysis identified Obfuscated Files or Information (T1027) with moderate confidence (50%), supported by evidence indicating deployed malware to encrypt victims’ data. Under the Credential Access tactic, the analysis identified Adversary-in-the-Middle (T1557) with moderate confidence (60%), supported by evidence indicating initial access broker facilitating unauthorized access. Under the Lateral Movement tactic, the analysis identified Exploitation of Remote Services (T1210) with moderate to high confidence (80%), supported by evidence indicating exploited vulnerabilities in computer networks. Under the Impact tactic, the analysis identified Data Encrypted for Impact (T1486) with high confidence (95%), supported by evidence indicating deployed malware to encrypt victims’ data and Inhibit System Recovery (T1490) with moderate to high confidence (70%), supported by evidence indicating disrupt operations via ransomware. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with moderate to high confidence (80%), supported by evidence indicating stolen data published on leak sites. Under the Command and Control tactic, the analysis identified Application Layer Protocol (T1071) with moderate confidence (60%), supported by evidence indicating ransomware groups deployed malware (implied C2). Under the Collection tactic, the analysis identified Data from Local System (T1005) with moderate to high confidence (80%), supported by evidence indicating data exfiltration and encryption. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.

Initial Access
Exploit Public-Facing Application (90%)
External Remote Services (70%)
Persistence
Valid Accounts (60%)
Privilege Escalation
Exploitation for Privilege Escalation (70%)
Defense Evasion
Obfuscated Files or Information (50%)
Credential Access
Adversary-in-the-Middle (60%)
Lateral Movement
Exploitation of Remote Services (80%)
Impact
Data Encrypted for Impact (95%)
Inhibit System Recovery (70%)
Exfiltration
Exfiltration Over C2 Channel (80%)
Command and Control
Application Layer Protocol (60%)
Collection
Data from Local System (80%)

Sources & References