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Analyze » MongoDB » MON1772720630

Incident Score: Analysis & Impact (MON1772720630)

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

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-4
Company Score Before Incident457 / 1000
Company Score After Incident453 / 1000
INCIDENT NUMBERMON1772720630
Type of Cyber IncidentVulnerability
ATTACK VECTORNetwork
DATA EXPOSEDNA
INCIDENT DATE04/03/2026
STATUSpublished

Key Highlights From The Incident Analysis

  • Timeline of MongoDB's Vulnerability 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 MongoDB 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 MongoDB breach identified under incident ID MON1772720630.

The analysis begins with a detailed overview of MongoDB's information like the linkedin page: https://www.linkedin.com/company/mongodbinc, the number of followers: 925601, the industry type: Software Development and the number of employees: 8042 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 457 and after the incident was 453 with a difference of -4 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 MongoDB and their customers.

MongoDB recently reported "Critical MongoDB Vulnerability (CVE-2026-25611) Enables Server Crashes via Low-Bandwidth Attacks", a noteworthy cybersecurity incident.

A high-severity vulnerability (CVE-2026-25611, CVSS 7.5) has been identified in MongoDB, allowing unauthenticated attackers to crash exposed servers with minimal effort.

The disruption is felt across the environment, affecting MongoDB servers with compression enabled.

In response, and began remediation that includes Monitor for official patches and mitigation guidance.

The case underscores how and recommending next steps like Monitor for official patches and mitigation guidance from MongoDB.

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%), with evidence including vulnerability (CVE-2026-25611) has been identified in MongoDB, and internet-exposed instances. Under the Impact tactic, the analysis identified Endpoint Denial of Service (T1499) with high confidence (100%), with evidence including exploiting the vulnerability...triggers a server crash, denial of Service (DoS), and disrupting operations for affected deployments and Service Exhaustion Flood (T1499.002) with moderate to high confidence (80%), supported by evidence indicating sending a small 47KB zlib-compressed packet while falsely declaring an uncompressed size of 48MB. Under the Resource Development tactic, the analysis identified Obtain Capabilities: Vulnerabilities (T1588.006) with high confidence (90%), supported by evidence indicating high-severity vulnerability (CVE-2026-25611, CVSS 7.5) has been identified. 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%)
Impact
Endpoint Denial of Service (100%)
Service Exhaustion Flood (80%)
Resource Development
Obtain Capabilities: Vulnerabilities (90%)

Sources & References