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Analyze » JPMorganChase » CITJPM1776832106

Incident Score: Analysis & Impact (CITJPM1776832106)

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

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-29
Company Score Before Incident811 / 1000
Company Score After Incident782 / 1000
INCIDENT NUMBERCITJPM1776832106
Type of Cyber IncidentBreach
ATTACK VECTORhacking, malware, social_engineering, third-party_vulnerabilities, API_exploits
DATA EXPOSEDpersonal_data (54%), internal_organizational_data (35%), credentials...
INCIDENT DATE31/12/2024
STATUSpublished

Key Highlights From The Incident Analysis

  • Timeline of JPMorganChase'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 JPMorganChase 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 JPMorganChase breach identified under incident ID CITJPM1776832106.

The analysis begins with a detailed overview of JPMorganChase's information like the linkedin page: https://www.linkedin.com/company/jpmorganchase, the number of followers: 7067454, the industry type: Financial Services and the number of employees: 224255 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 811 and after the incident was 782 with a difference of -29 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 JPMorganChase and their customers.

JPMorgan Chase recently reported "Cyber Threats in Finance: 2025’s Rising Risks and Evolving Attack Tactics", a noteworthy cybersecurity incident.

In 2025, financially motivated cyberattacks dominated the financial sector, driving 90% of breaches targeting banks, insurers, and payment processors.

The disruption is felt across the environment, affecting banks, insurers and payment_processors, and exposing personal_data (54%), internal_organizational_data (35%) and credentials (22%), plus an estimated financial loss of $5.56 million (average per incident).

Formal response steps have not been shared publicly yet.

Overall, the incident is a reminder of why proactive monitoring and strong governance matter.

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 vulnerable file transfer solutions, managed service platforms, and APIs served as common entry points, Supply Chain Compromise: Compromise Software Supply Chain (T1195.002) with high confidence (90%), supported by evidence indicating supply chain compromises played a role in 30% of financial sector breaches, Phishing: Spearphishing Attachment (T1566.001) with moderate to high confidence (70%), supported by evidence indicating generative AI amplified social engineering, producing contextually accurate phishing emails, and Phishing: Spearphishing via Service (T1566.003) with moderate to high confidence (70%), supported by evidence indicating social engineering (25%) as primary vector; deepfake impersonations used. Under the Execution tactic, the analysis identified User Execution: Malicious File (T1204.002) with moderate to high confidence (80%), supported by evidence indicating malware (37%) as primary attack vector; adaptive malware evaded signature-based detection and Command and Scripting Interpreter: Visual Basic (T1059.005) with moderate confidence (60%), supported by evidence indicating aI-driven attack tools likely automated malicious script execution. Under the Persistence tactic, the analysis identified Valid Accounts (T1078) with high confidence (90%), supported by evidence indicating attackers leveraged stolen credentials for persistent network access (22% of cases) and Create Account: Cloud Account (T1136.003) with moderate to high confidence (70%), supported by evidence indicating shadow AI adoption (20% of AI-related breaches) lacked adequate access controls. Under the Privilege Escalation tactic, the analysis identified Valid Accounts (T1078) with moderate to high confidence (80%), supported by evidence indicating stolen credentials (22%) used for persistent access and likely privilege escalation and Exploitation for Privilege Escalation (T1068) with moderate to high confidence (70%), supported by evidence indicating zero-day vulnerabilities exploited by state-aligned APT actors. Under the Defense Evasion tactic, the analysis identified Obfuscated Files or Information (T1027) with high confidence (90%), supported by evidence indicating adaptive malware dynamically altered behavior to evade signature-based detection, Impair Defenses: Disable or Modify Tools (T1562.001) with moderate confidence (60%), supported by evidence indicating aI-driven attack tools likely disabled security controls, and Valid Accounts (T1078) with moderate to high confidence (80%), supported by evidence indicating stolen credentials used to blend in with legitimate activity. Under the Credential Access tactic, the analysis identified Credentials from Password Stores (T1555) with moderate to high confidence (80%), supported by evidence indicating credentials (22%) compromised; used for fraud and resale, Brute Force: Password Guessing (T1110.001) with moderate confidence (60%), supported by evidence indicating aI-powered scanning tools enabled faster reconnaissance, and Adversary-in-the-Middle (T1557) with moderate to high confidence (70%), supported by evidence indicating third-party wallet infrastructure exploited for $1.5B theft. Under the Discovery tactic, the analysis identified Account Discovery: Domain Account (T1087.002) with moderate to high confidence (70%), supported by evidence indicating aI-powered scanning tools enabled faster reconnaissance and Network Service Discovery (T1046) with moderate to high confidence (70%), supported by evidence indicating machine learning-powered scanning tools used for reconnaissance. Under the Collection tactic, the analysis identified Data from Local System (T1005) with high confidence (90%), supported by evidence indicating personal data (54%) and internal organizational data (35%) compromised and Data from Information Repositories: Sharepoint (T1213.002) with moderate to high confidence (70%), supported by evidence indicating third-party file transfer solutions exploited as entry points. Under the Command and Control tactic, the analysis identified Application Layer Protocol: Web Protocols (T1071.001) with moderate to high confidence (80%), supported by evidence indicating aPI exploits and third-party vulnerabilities used for C2 and Ingress Tool Transfer (T1105) with moderate to high confidence (70%), supported by evidence indicating adaptive malware likely downloaded additional tools dynamically. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with high confidence (90%), supported by evidence indicating ransomware shifted to data exfiltration; data breach impacted major banks and Exfiltration Over Web Service: Exfiltration to Cloud Storage (T1567.002) with moderate to high confidence (70%), supported by evidence indicating third-party providers and APIs used as exfiltration vectors. Under the Impact tactic, the analysis identified Data Encrypted for Impact (T1486) with moderate confidence (60%), supported by evidence indicating ransomware (36% of incidents) sometimes included data encryption, Defacement: Internal Defacement (T1491.001) with moderate confidence (50%), supported by evidence indicating hacktivist DDoS campaigns targeted banks during geopolitical tensions, and Data Manipulation: Transmitted Data Manipulation (T1565.002) with moderate to high confidence (70%), supported by evidence indicating fraud-as-a-service and deepfake impersonations used for financial fraud. 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%)
Supply Chain Compromise: Compromise Software Supply Chain (90%)
Phishing: Spearphishing Attachment (70%)
Phishing: Spearphishing via Service (70%)
Execution
User Execution: Malicious File (80%)
Command and Scripting Interpreter: Visual Basic (60%)
Persistence
Valid Accounts (90%)
Create Account: Cloud Account (70%)
Privilege Escalation
Valid Accounts (80%)
Exploitation for Privilege Escalation (70%)
Defense Evasion
Obfuscated Files or Information (90%)
Impair Defenses: Disable or Modify Tools (60%)
Valid Accounts (80%)
Credential Access
Credentials from Password Stores (80%)
Brute Force: Password Guessing (60%)
Adversary-in-the-Middle (70%)
Discovery
Account Discovery: Domain Account (70%)
Network Service Discovery (70%)
Collection
Data from Local System (90%)
Data from Information Repositories: Sharepoint (70%)
Command and Control
Application Layer Protocol: Web Protocols (80%)
Ingress Tool Transfer (70%)
Exfiltration
Exfiltration Over C2 Channel (90%)
Exfiltration Over Web Service: Exfiltration to Cloud Storage (70%)
Impact
Data Encrypted for Impact (60%)
Defacement: Internal Defacement (50%)
Data Manipulation: Transmitted Data Manipulation (70%)

Sources & References