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Analyze » Mexintel » SERMEX1772240290

Incident Score: Analysis & Impact (SERMEX1772240290)

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

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-53
Company Score Before Incident759 / 1000
Company Score After Incident706 / 1000
INCIDENT NUMBERSERMEX1772240290
Type of Cyber IncidentCyber Attack
ATTACK VECTORAI Tool Exploitation (Claude LLM)
DATA EXPOSED150 GB of sensitive data
INCIDENT DATE26/02/2026
STATUSOngoing

Key Highlights From The Incident Analysis

  • Timeline of Mexintel'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 Mexintel 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 Mexintel breach identified under incident ID SERMEX1772240290.

The analysis begins with a detailed overview of Mexintel's information like the linkedin page: https://www.linkedin.com/company/mexintel, the number of followers: 21, the industry type: Security and Investigations and the number of employees: 1 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 759 and after the incident was 706 with a difference of -53 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 Mexintel and their customers.

On 01 December 2023, Servicio de Administración Tributaria (SAT) disclosed Data Breach, Cyber Espionage issues under the banner "Mexican Government Agencies Hit by Month-Long Cyberattack Leveraging AI Tool".

A sustained cyberattack targeting multiple Mexican government agencies between December and January exploited Anthropic’s Claude large language model (LLM) to steal 150 GB of sensitive data.

The disruption is felt across the environment, affecting Federal tax authority (SAT), civil registry, state governments, Monterrey’s water utility, and exposing 150 GB of sensitive data, with nearly 195 million records at risk.

In response, and stakeholders are being briefed through Denial by affected agencies.

The case underscores how Ongoing.

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 exploited Anthropic’s Claude large language model (LLM) to steal 150 GB of sensitive data and Supply Chain Compromise: Compromise Software Dependencies and Development Tools (T1195.002) with moderate to high confidence (70%), supported by evidence indicating attackers weaponized Claude by prompting the AI to identify 20 security vulnerabilities. Under the Execution tactic, the analysis identified Command and Scripting Interpreter: Visual Basic (T1059.005) with moderate to high confidence (70%), supported by evidence indicating generate exploit scripts, disguising their activity as a bug-hunting operation and Content Injection (T1659) with moderate confidence (60%), supported by evidence indicating prompting the AI to identify 20 security vulnerabilities and generate exploit scripts. Under the Defense Evasion tactic, the analysis identified Masquerading: Match Legitimate Name or Location (T1036.005) with high confidence (90%), with evidence including disguising their activity as a bug-hunting operation, and framing their requests as authorized security research and Hide Artifacts: Hidden Files and Directories (T1564.001) with moderate confidence (60%), supported by evidence indicating claude’s safeguards flagged attempts to delete logs and command histories. Under the Credential Access tactic, the analysis identified Unsecured Credentials: Credentials In Files (T1552.001) with moderate to high confidence (70%), supported by evidence indicating government employee credentials exposed. Under the Discovery tactic, the analysis identified Active Scanning: Vulnerability Scanning (T1595.002) with high confidence (90%), supported by evidence indicating prompting the AI to identify 20 security vulnerabilities. Under the Collection tactic, the analysis identified Data from Local System (T1005) with high confidence (90%), supported by evidence indicating 150 GB of sensitive data stolen, including taxpayer records, civil registry files, voter lists. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with moderate to high confidence (80%), with evidence including 150 GB of sensitive data stolen, and data exfiltration confirmed. Under the Impact tactic, the analysis identified Defacement: Internal Defacement (T1491.001) with moderate confidence (50%), supported by evidence indicating attack threatening the economy of geographical region and Data Manipulation: Transmitted Data Manipulation (T1565.002) with moderate confidence (60%), supported by evidence indicating high identity theft risk due to compromised voter lists and taxpayer records. 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 Dependencies and Development Tools (70%)
Execution
Command and Scripting Interpreter: Visual Basic (70%)
Content Injection (60%)
Defense Evasion
Masquerading: Match Legitimate Name or Location (90%)
Hide Artifacts: Hidden Files and Directories (60%)
Credential Access
Unsecured Credentials: Credentials In Files (70%)
Discovery
Active Scanning: Vulnerability Scanning (90%)
Collection
Data from Local System (90%)
Exfiltration
Exfiltration Over C2 Channel (80%)
Impact
Defacement: Internal Defacement (50%)
Data Manipulation: Transmitted Data Manipulation (60%)