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Analyze » IBM » IBMPON1785321521

Incident Score: Analysis & Impact (IBMPON1785321521)

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

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-13
Company Score Before Incident708 / 1000
Company Score After Incident695 / 1000
Company LinkView IBM Profile
INCIDENT NUMBERIBMPON1785321521
Type of Cyber IncidentCyber Attack
ATTACK VECTORdeepfake impersonation, AI-driven malware, compromised APIs, applications, or plug-ins, cloud misconfigurations
DATA EXPOSEDTrue
INCIDENT DATE28/02/2025
STATUSpublished

Key Highlights From The Incident Analysis

  • Timeline of IBM'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 IBM 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 IBM breach identified under incident ID IBMPON1785321521.

The analysis begins with a detailed overview of IBM's information like the linkedin page: https://www.linkedin.com/company/ibm, the number of followers: 19659540, the industry type: IT Services and IT Consulting and the number of employees: 336062 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 708 and after the incident was 695 with a difference of -13 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 IBM and their customers.

A newly reported cybersecurity incident, "AI-Enabled Breaches Surge, Costing Organizations $6 Million on Average in 2026", has drawn attention.

A new IBM study reveals that one in four malicious data breaches in 2026 were AI-enabled, marking a 56% increase from the previous year.

The disruption is felt across the environment, affecting AI models, applications and cloud systems, and exposing True, plus an estimated financial loss of $6 million (average for AI-related breaches).

In response, and began remediation that includes AI-driven security tools and automation in security operations.

The case underscores how teams are taking away lessons such as The growing imbalance between attack costs and breach expenses is reshaping cyber risk, emphasizing the need for faster remediation, runtime identity security, and integrated vulnerability management to match attackers’ speed, and recommending next steps like Adopt AI-driven security tools, Increase security spending and Use automation in security 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 Exploit Public-Facing Application (T1190) with moderate to high confidence (80%), supported by evidence indicating compromised APIs, applications, or plug-ins (27%), Phishing: Spearphishing Attachment (T1566.001) with moderate to high confidence (70%), supported by evidence indicating deepfake impersonation and AI-driven malware, and Trusted Relationship (T1199) with moderate confidence (60%), supported by evidence indicating aI-driven attacks targeting financial services and energy sectors. Under the Execution tactic, the analysis identified User Execution: Malicious File (T1204.002) with moderate to high confidence (70%), supported by evidence indicating aI-driven malware accelerating breach economics and Command and Scripting Interpreter: Visual Basic (T1059.005) with moderate confidence (50%), supported by evidence indicating aI-driven malware automating attacks. Under the Persistence tactic, the analysis identified Server Software Component: Web Shell (T1505.003) with moderate confidence (60%), supported by evidence indicating compromised APIs, applications, or plug-ins (27%). Under the Privilege Escalation tactic, the analysis identified Exploitation for Privilege Escalation (T1068) with moderate to high confidence (70%), supported by evidence indicating cloud misconfigurations (27%) enabling AI-driven attacks. Under the Defense Evasion tactic, the analysis identified Obfuscated Files or Information (T1027) with moderate to high confidence (80%), supported by evidence indicating aI-driven malware making attacks faster and cheaper and Impair Defenses: Disable or Modify Tools (T1562.001) with moderate confidence (60%), supported by evidence indicating only 18% of organizations use AI-driven agents for vulnerability management. Under the Credential Access tactic, the analysis identified Modify Authentication Process: Domain Controller Authentication (T1556.001) with moderate to high confidence (70%), supported by evidence indicating deepfake impersonation enabling credential theft and Brute Force: Password Spraying (T1110.003) with moderate confidence (60%), supported by evidence indicating aI-driven attacks automating credential exploitation. Under the Discovery tactic, the analysis identified Account Discovery: Domain Account (T1087.002) with moderate to high confidence (70%), supported by evidence indicating aI-driven attacks targeting employee data (35%) and Network Service Discovery (T1046) with moderate confidence (60%), supported by evidence indicating aI-driven malware exploiting cloud misconfigurations. Under the Collection tactic, the analysis identified Data from Local System (T1005) with moderate to high confidence (80%), supported by evidence indicating employee data (35%), intellectual property (31%) compromised and Data from Information Repositories: Sharepoint (T1213.002) with moderate to high confidence (70%), supported by evidence indicating aI-driven attacks targeting brand reputation (41%). Under the Command and Control tactic, the analysis identified Application Layer Protocol: Web Protocols (T1071.001) with moderate to high confidence (70%), supported by evidence indicating aI-driven malware automating attacks via APIs. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with high confidence (90%), supported by evidence indicating data exfiltration confirmed in AI-enabled breaches and Exfiltration Over Web Service: Exfiltration to Cloud Storage (T1567.002) with moderate to high confidence (70%), supported by evidence indicating cloud misconfigurations (27%) enabling data exfiltration. Under the Impact tactic, the analysis identified Data Encrypted for Impact (T1486) with moderate to high confidence (80%), supported by evidence indicating ransomware attacks (39%) with data encryption and Defacement: Internal Defacement (T1491.001) with moderate confidence (60%), supported by evidence indicating brand reputation exploitation (41%). 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 (80%)
Phishing: Spearphishing Attachment (70%)
Trusted Relationship (60%)
Execution
User Execution: Malicious File (70%)
Command and Scripting Interpreter: Visual Basic (50%)
Persistence
Server Software Component: Web Shell (60%)
Privilege Escalation
Exploitation for Privilege Escalation (70%)
Defense Evasion
Obfuscated Files or Information (80%)
Impair Defenses: Disable or Modify Tools (60%)
Credential Access
Modify Authentication Process: Domain Controller Authentication (70%)
Brute Force: Password Spraying (60%)
Discovery
Account Discovery: Domain Account (70%)
Network Service Discovery (60%)
Collection
Data from Local System (80%)
Data from Information Repositories: Sharepoint (70%)
Command and Control
Application Layer Protocol: Web Protocols (70%)
Exfiltration
Exfiltration Over C2 Channel (90%)
Exfiltration Over Web Service: Exfiltration to Cloud Storage (70%)
Impact
Data Encrypted for Impact (80%)
Defacement: Internal Defacement (60%)