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Analyze » MEJ : Mouvement Eucharistique des Jeunes » MEJ1785018222

Incident Score: Analysis & Impact (MEJ1785018222)

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

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-93
Company Score Before Incident761 / 1000
Company Score After Incident668 / 1000
INCIDENT NUMBERMEJ1785018222
Type of Cyber IncidentBreach
ATTACK VECTORAPI Misconfiguration
DATA EXPOSED720,000 user records
INCIDENT DATE31/12/2025
STATUSResolved

Key Highlights From The Incident Analysis

  • Timeline of MEJ : Mouvement Eucharistique des Jeunes'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 MEJ : Mouvement Eucharistique des Jeunes 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 MEJ : Mouvement Eucharistique des Jeunes breach identified under incident ID MEJ1785018222.

The analysis begins with a detailed overview of MEJ : Mouvement Eucharistique des Jeunes's information like the linkedin page: https://www.linkedin.com/company/mej, the number of followers: 311, the industry type: Civic and Social Organizations and the number of employees: 13 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 761 and after the incident was 668 with a difference of -93 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 MEJ : Mouvement Eucharistique des Jeunes and their customers.

Pope’s Worldwide Prayer Network recently reported "Vatican-Linked Prayer App Exposed 720,000 Users’ Data Due to Zero Security", a noteworthy cybersecurity incident.

Security researcher BobDaHacker uncovered critical vulnerabilities in *Click To Pray*, the official prayer app of the Pope’s Worldwide Prayer Network, exposing sensitive user data.

The disruption is felt across the environment, affecting Click To Pray app API, and exposing 720,000 user records, with nearly 720,000 records at risk.

In response, moved swiftly to contain the threat with measures like Vulnerabilities patched after public disclosure, and began remediation that includes API security improvements (rate limiting, encryption of sensitive data), and stakeholders are being briefed through No initial response to researcher; public disclosure via Dark Reading.

The case underscores how Resolved, teams are taking away lessons such as The incident highlights the risks of overlooked security in niche applications, especially those targeting vulnerable populations like older, less tech-savvy users. Basic security measures (e.g., rate limiting, encryption) are critical even for non-commercial apps, and recommending next steps like Implement rate limiting on APIs to prevent automated data harvesting, Encrypt sensitive data (e.g., validation_hash) to prevent plaintext exposure and Establish a clear vulnerability disclosure process to respond to security researchers promptly.

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 high confidence (90%), supported by evidence indicating app’s API lacked basic security measures, allowing unrestricted access. Under the Credential Access tactic, the analysis identified Unsecured Credentials: Credentials In Files (T1552.001) with moderate to high confidence (80%), supported by evidence indicating validation_hash was also stored in plaintext. Under the Collection tactic, the analysis identified Automated Collection (T1119) with high confidence (90%), supported by evidence indicating no rate limiting on the API, attackers could automate data harvesting and Data from Local System (T1005) with moderate to high confidence (80%), supported by evidence indicating exposing sensitive user data including names, email addresses, and birthdates. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with moderate to high confidence (70%), supported by evidence indicating retrieving details from all 720,000 accounts and Automated Exfiltration (T1020) with moderate to high confidence (80%), supported by evidence indicating no rate limiting on the API, attackers could automate data harvesting. Under the Impact tactic, the analysis identified Endpoint Denial of Service: Application or System Exploitation (T1499.004) with moderate confidence (50%), supported by evidence indicating aPI lacked basic security measures, allowing unrestricted access and Data Manipulation: Stored Data Manipulation (T1565.001) with lower confidence (40%), supported by evidence indicating validation_hash stored in plaintext, enabling account verification via email. 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 (90%)
Credential Access
Unsecured Credentials: Credentials In Files (80%)
Collection
Automated Collection (90%)
Data from Local System (80%)
Exfiltration
Exfiltration Over C2 Channel (70%)
Automated Exfiltration (80%)
Impact
Endpoint Denial of Service: Application or System Exploitation (50%)
Data Manipulation: Stored Data Manipulation (40%)

Sources & References