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Analyze » CountryMax Stores » ELFTEMCOUGRUAMASAMLYF1777580773

Incident Score: Analysis & Impact (ELFTEMCOUGRUAMASAMLYF1777580773)

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

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-61
Company Score Before Incident770 / 1000
Company Score After Incident709 / 1000
INCIDENT NUMBERELFTEMCOUGRUAMASAMLYF1777580773
Type of Cyber IncidentCyber Attack
ATTACK VECTORMisconfigured Server
DATA EXPOSED345,000 credit cards (145,000 active)
INCIDENT DATE15/04/2026
STATUSOngoing

Key Highlights From The Incident Analysis

  • Timeline of CountryMax Stores'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 CountryMax Stores 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 CountryMax Stores breach identified under incident ID ELFTEMCOUGRUAMASAMLYF1777580773.

The analysis begins with a detailed overview of CountryMax Stores's information like the linkedin page: https://www.linkedin.com/company/countrymax-stores, the number of followers: 672, the industry type: Retail and the number of employees: 139 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 770 and after the incident was 709 with a difference of -61 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 CountryMax Stores and their customers.

On 16 April 2024, Jerry’s Store disclosed Data Breach issues under the banner "AI Coding Error Exposes Massive Stolen Credit Card Database".

Cybersecurity researchers uncovered a misconfigured server linked to Jerry’s Store, a dark web carding marketplace, due to an AI-assisted coding mistake.

The disruption is felt across the environment, affecting Jerry’s Store dark web marketplace server, and exposing 345,000 credit cards (145,000 active), with nearly 345,000 records at risk, plus an estimated financial loss of $2.6 million (potential dark web value).

Formal response steps have not been shared publicly yet.

The case underscores how Ongoing, teams are taking away lessons such as AI-assisted development tools like Cursor can inadvertently facilitate criminal activity due to lack of safety guardrails. Misconfigurations in AI-generated code can lead to significant data exposures, and recommending next steps like AI tool developers should implement stricter safety guardrails to prevent misuse. Organizations should audit AI-generated code for security vulnerabilities and enforce secure coding practices.

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 misconfigured server linked to Jerry’s Store...exposing the server to public access. Under the Credential Access tactic, the analysis identified Modify Authentication Process: Hybrid Identity (T1556.003) with moderate to high confidence (70%), supported by evidence indicating hackers verify stolen credit cards...confirming a card’s validity and Adversary-in-the-Middle (T1557) with moderate confidence (60%), supported by evidence indicating small transactions on major platforms...to test stolen cards. Under the Collection tactic, the analysis identified Data from Local System (T1005) with high confidence (90%), supported by evidence indicating exposed data included card numbers, security codes, cardholder names, home addresses and Data from Information Repositories (T1213) with moderate to high confidence (80%), supported by evidence indicating entire database including 345,000 credit cards...exposed via misconfigured server. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with moderate to high confidence (70%), supported by evidence indicating data potentially worth $2.6 million...increasing its dark web value and Exfiltration Over Web Service (T1567) with moderate confidence (60%), supported by evidence indicating server hosted in Germany via bulletproof hosting provider to evade detection. Under the Defense Evasion tactic, the analysis identified Hide Artifacts: Hidden Window (T1564.003) with moderate to high confidence (70%), supported by evidence indicating bulletproof hosting provider to evade detection and Masquerading (T1036) with moderate confidence (60%), supported by evidence indicating aI-assisted coding mistake...Cursor generated unauthenticated open web directory. Under the Impact tactic, the analysis identified Resource Hijacking (T1496) with moderate to high confidence (80%), supported by evidence indicating small transactions on major platforms...to test stolen cards and Data Manipulation: Stored Data Manipulation (T1565.001) with moderate to high confidence (70%), supported by evidence indicating hackers verify stolen credit cards...confirming a card’s validity. 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%)
Credential Access
Modify Authentication Process: Hybrid Identity (70%)
Adversary-in-the-Middle (60%)
Collection
Data from Local System (90%)
Data from Information Repositories (80%)
Exfiltration
Exfiltration Over C2 Channel (70%)
Exfiltration Over Web Service (60%)
Defense Evasion
Hide Artifacts: Hidden Window (70%)
Masquerading (60%)
Impact
Resource Hijacking (80%)
Data Manipulation: Stored Data Manipulation (70%)