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Analyze » Federal Bureau of Investigation (FBI) » FBI1775659096

Incident Score: Analysis & Impact (FBI1775659096)

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

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-102
Company Score Before Incident390 / 1000
Company Score After Incident288 / 1000
INCIDENT NUMBERFBI1775659096
Type of Cyber IncidentCyber Attack
ATTACK VECTORAI-driven tactics, deepfake voices, cloned identities, fabricated video content, phishing
DATA EXPOSEDNA
INCIDENT DATE31/12/2024
STATUSpublished

Key Highlights From The Incident Analysis

  • Timeline of Federal Bureau of Investigation (FBI)'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 Federal Bureau of Investigation (FBI) 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 Federal Bureau of Investigation (FBI) breach identified under incident ID FBI1775659096.

The analysis begins with a detailed overview of Federal Bureau of Investigation (FBI)'s information like the linkedin page: https://www.linkedin.com/company/fbi, the number of followers: 936451, the industry type: Law Enforcement and the number of employees: 10118 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 390 and after the incident was 288 with a difference of -102 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 Federal Bureau of Investigation (FBI) and their customers.

A newly reported cybersecurity incident, "AI-Driven Cybercrime Losses Hit Record $20.87 Billion in 2025, FBI Reports", has drawn attention.

Cybercrime losses surged to an unprecedented $20.87 billion in 2025, with artificial intelligence playing an increasingly central role in fraud schemes, according to the FBI’s Internet Crime Complaint Center (IC3) report.

The disruption is felt across the environment, plus an estimated financial loss of $20.87 billion.

Formal response steps have not been shared publicly yet.

The case underscores how teams are taking away lessons such as AI is increasingly used by criminal networks to enhance the scale and sophistication of attacks, including deepfake voices, cloned identities, and fabricated video content. Cyber-enabled fraud crimes leveraging technology dominate the landscape, with investment fraud causing the greatest financial damage.

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 Phishing (T1566) with high confidence (90%), supported by evidence indicating phishing remained the most reported offense, Phishing: Spearphishing via Service (T1566.003) with moderate to high confidence (80%), supported by evidence indicating business email compromise (BEC) contributed heavily to losses, and Content Injection (T1659) with moderate to high confidence (70%), supported by evidence indicating deepfake voices, cloned identities, and fabricated video content. Under the Execution tactic, the analysis identified User Execution (T1204) with moderate to high confidence (80%), supported by evidence indicating aI-driven tactics...used in BEC, romance scams, employment fraud and User Execution: Malicious Link (T1204.001) with moderate to high confidence (70%), supported by evidence indicating phishing remained the most reported offense. Under the Credential Access tactic, the analysis identified Modify Authentication Process (T1556) with moderate to high confidence (70%), supported by evidence indicating cloned identities...used to deceive victims into compromising personal accounts and Brute Force (T1110) with moderate confidence (60%), supported by evidence indicating aI-driven tactics enhance scale and sophistication of attacks. Under the Defense Evasion tactic, the analysis identified Masquerading (T1036) with high confidence (90%), supported by evidence indicating government impersonation scams surged 128% and Use Alternate Authentication Material: Application Access Token (T1550.001) with moderate to high confidence (70%), supported by evidence indicating aI-generated messages impersonating officials. Under the Collection tactic, the analysis identified Data from Information Repositories (T1213) with moderate to high confidence (80%), supported by evidence indicating investment fraud caused the greatest financial damage ($8.6B) and Data from Cloud Storage (T1530) with moderate confidence (60%), supported by evidence indicating digitally enabled fraud dominated the landscape. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with moderate to high confidence (70%), supported by evidence indicating cybercrime losses surged to $20.87B and Exfiltration Over Alternative Protocol (T1048) with moderate confidence (60%), supported by evidence indicating aI-powered fraud accounted for 22,364 complaints. Under the Impact tactic, the analysis identified Data Encrypted for Impact (T1486) with moderate confidence (50%), supported by evidence indicating ransomware accounted for 75% of reported technical attacks and Defacement (T1491) with lower confidence (40%), supported by evidence indicating fabricated video content used in scams. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.

Initial Access
Phishing (90%)
Phishing: Spearphishing via Service (80%)
Content Injection (70%)
Execution
User Execution (80%)
User Execution: Malicious Link (70%)
Credential Access
Modify Authentication Process (70%)
Brute Force (60%)
Defense Evasion
Masquerading (90%)
Use Alternate Authentication Material: Application Access Token (70%)
Collection
Data from Information Repositories (80%)
Data from Cloud Storage (60%)
Exfiltration
Exfiltration Over C2 Channel (70%)
Exfiltration Over Alternative Protocol (60%)
Impact
Data Encrypted for Impact (50%)
Defacement (40%)

Sources & References