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Analyze » Commerzbank AG » COM1786740728

Incident Score: Analysis & Impact (COM1786740728)

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

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-20
Company Score Before Incident814 / 1000
Company Score After Incident794 / 1000
INCIDENT NUMBERCOM1786740728
Type of Cyber IncidentCyber Attack
ATTACK VECTORVulnerability in a payment provider
DATA EXPOSEDNA
INCIDENT DATE31/10/2023
STATUSOngoing (arrests made, prosecutions expected)

Key Highlights From The Incident Analysis

  • Timeline of Commerzbank AG'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 Commerzbank AG 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 Commerzbank AG breach identified under incident ID COM1786740728.

The analysis begins with a detailed overview of Commerzbank AG's information like the linkedin page: https://www.linkedin.com/company/commerzbank-ag, the number of followers: 186248, the industry type: Banking and the number of employees: 12820 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 814 and after the incident was 794 with a difference of -20 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 Commerzbank AG and their customers.

Commerzbank recently reported "German-Brazilian Cyber Heist Leads to Multiple Arrests in €30 Million Bank Fraud", a noteworthy cybersecurity incident.

German and Brazilian authorities have arrested seven suspects in connection with a late-2023 cyber heist that siphoned an estimated €30 million ($34.7 million) from German bank accounts.

The disruption is felt across the environment, affecting Online banking systems, plus an estimated financial loss of €30 million ($34.7 million).

In response, and stakeholders are being briefed through Bank assured customers they would not bear financial losses.

The case underscores how Ongoing (arrests made, prosecutions expected), with advisories going out to stakeholders covering Commerzbank assured customers they would not bear financial losses.

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 exploiting a vulnerability in a payment provider. Under the Credential Access tactic, the analysis identified Input Capture: Web Portal Capture (T1056.003) with moderate to high confidence (70%), supported by evidence indicating unauthorized withdrawals from German online banking users and Modify Authentication Process: Multi-Factor Authentication (T1556.003) with moderate confidence (60%), supported by evidence indicating cloned payment cards used for unauthorized withdrawals. Under the Lateral Movement tactic, the analysis identified Valid Accounts (T1078) with moderate to high confidence (80%), supported by evidence indicating unauthorized withdrawals from German online banking users. Under the Collection tactic, the analysis identified Data from Local System (T1005) with moderate to high confidence (70%), supported by evidence indicating payment card information compromised. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with moderate to high confidence (80%), supported by evidence indicating stolen funds laundered through networks in Brazil and Europe. Under the Impact tactic, the analysis identified Data Encrypted for Impact (T1486) with lower confidence (30%), supported by evidence indicating cloned payment cards used (implies data manipulation) and Financial Theft (T1657) with high confidence (90%), supported by evidence indicating €30 million siphoned from German bank accounts. Under the Defense Evasion tactic, the analysis identified Masquerading (T1036) with moderate to high confidence (70%), supported by evidence indicating cloned payment cards used for unauthorized transactions. 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%)
Credential Access
Input Capture: Web Portal Capture (70%)
Modify Authentication Process: Multi-Factor Authentication (60%)
Lateral Movement
Valid Accounts (80%)
Collection
Data from Local System (70%)
Exfiltration
Exfiltration Over C2 Channel (80%)
Impact
Data Encrypted for Impact (30%)
Financial Theft (90%)
Defense Evasion
Masquerading (70%)

Sources & References