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Analyze » Alfa-Bank » ALFMIN1768300194

Incident Score: Analysis & Impact (ALFMIN1768300194)

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

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-24
Company Score Before Incident840 / 1000
Company Score After Incident816 / 1000
INCIDENT NUMBERALFMIN1768300194
Type of Cyber IncidentBreach
ATTACK VECTORInsider Abuse, Corrupt Officials, Dark Web Marketplaces
DATA EXPOSEDPassports, Metadata, Personal Identifiable Information,...
INCIDENT DATE12/01/2026
STATUSOngoing

Key Highlights From The Incident Analysis

  • Timeline of Alfa-Bank'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 Alfa-Bank 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 Alfa-Bank breach identified under incident ID ALFMIN1768300194.

The analysis begins with a detailed overview of Alfa-Bank's information like the linkedin page: https://www.linkedin.com/company/alfa-bank, the number of followers: 0, the industry type: Banking and the number of employees: 5410 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 840 and after the incident was 816 with a difference of -24 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 Alfa-Bank and their customers.

Solaris Platform recently reported "Crackdown on Probiv Market in Russia", a noteworthy cybersecurity incident.

Russia's crackdown on the probiv market, an illegal network trading leaked personal data, following increased fraud risks and national security concerns.

The disruption is felt across the environment, and exposing Passports, Metadata and Personal Identifiable Information.

In response, moved swiftly to contain the threat with measures like Arrest of key brokers (Kirill Mironov and Mikhail Seifetdinov) and Legal crackdown on data brokers.

The case underscores how Ongoing, teams are taking away lessons such as Data integrity is critical to national security. Insider abuse and lack of access controls can turn personal data into a weapon for fraud, espionage, and targeted operations, and recommending next steps like Strengthen access controls, Monitor insider threats and Enhance regulatory oversight of data markets, with advisories going out to stakeholders covering Government and financial institutions should reassess data security measures due to heightened risks from leaked data.

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%), with evidence including corrupt Officials, bank Workers, and mironov worked for a federal agency and Trusted Relationship (T1199) with moderate to high confidence (80%), with evidence including probiv market served as unofficial tool for police, and deeply embedded in law enforcement. Under the Credential Access tactic, the analysis identified Credentials In Files (T1552.005) with moderate to high confidence (80%), supported by evidence indicating passports ($10 in some cases), metadata traded in probiv market and Credentials from Password Stores (T1555) with moderate to high confidence (70%), with evidence including bank Client Data exposed, and fSB Kordon-2023 database leaked. Under the Collection tactic, the analysis identified Data from Information Repositories (T1213) with high confidence (90%), with evidence including fSB Kordon-2023 database (9 years of border crossings), and alfa Bank client database and Data from Local System (T1005) with moderate to high confidence (80%), with evidence including personal Identifiable Information compromised, and banking Data exposed. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with moderate to high confidence (80%), with evidence including data exfiltration such as Yes, and data sold on dark web and Exfiltration Over Web Service (T1567) with moderate to high confidence (70%), supported by evidence indicating dark Web Marketplaces listed as attack vector. Under the Defense Evasion tactic, the analysis identified Valid Accounts: Local Accounts (T1078.003) with high confidence (90%), with evidence including insider Threat, and corrupt Officials used legitimate access and Hide Artifacts: Hidden Users (T1564.002) with moderate to high confidence (70%), supported by evidence indicating probiv market operated in shadowy network for a decade. Under the Impact tactic, the analysis identified Data Destruction (T1485) with moderate confidence (60%), supported by evidence indicating data Corruption listed as vulnerability exploited and Data Manipulation: Stored Data Manipulation (T1565.001) with moderate to high confidence (70%), with evidence including fraud enabled by leaked data, and targeted killings enabled. 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%)
Trusted Relationship (80%)
Credential Access
Credentials In Files (80%)
Credentials from Password Stores (70%)
Collection
Data from Information Repositories (90%)
Data from Local System (80%)
Exfiltration
Exfiltration Over C2 Channel (80%)
Exfiltration Over Web Service (70%)
Defense Evasion
Valid Accounts: Local Accounts (90%)
Hide Artifacts: Hidden Users (70%)
Impact
Data Destruction (60%)
Data Manipulation: Stored Data Manipulation (70%)