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Analyze » The Apache Software Foundation » THE1769425022

Incident Score: Analysis & Impact (THE1769425022)

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

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-5
Company Score Before Incident757 / 1000
Company Score After Incident752 / 1000
INCIDENT NUMBERTHE1769425022
Type of Cyber IncidentVulnerability
ATTACK VECTORManipulation of untrusted input in URI parser
DATA EXPOSEDPotential data loss
INCIDENT DATE31/12/2024
STATUSpublished

Key Highlights From The Incident Analysis

  • Timeline of The Apache Software Foundation'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 The Apache Software Foundation 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 The Apache Software Foundation breach identified under incident ID THE1769425022.

The analysis begins with a detailed overview of The Apache Software Foundation's information like the linkedin page: https://www.linkedin.com/company/the-apache-software-foundation, the number of followers: 79547, the industry type: Software Development and the number of employees: 2368 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 757 and after the incident was 752 with a difference of -5 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 The Apache Software Foundation and their customers.

Organizations using Apache Hadoop for big data operations recently reported "Critical Vulnerability in Apache Hadoop HDFS Native Client Exposes Systems to Crashes and Data Corruption", a noteworthy cybersecurity incident.

A critical vulnerability in Apache Hadoop’s HDFS native client, tracked as CVE-2025-27821, has been disclosed, posing risks of system crashes, memory corruption, and data loss in production environments.

The disruption is felt across the environment, affecting Apache Hadoop HDFS native client, and exposing Potential data loss.

In response, moved swiftly to contain the threat with measures like Conduct an immediate version audit of Hadoop deployments, Monitor HDFS logs for suspicious URI patterns and Implement network-level access controls to restrict HDFS client connections to trusted sources, and began remediation that includes Upgrade to Hadoop version 3.4.2 or later.

The case underscores how teams are taking away lessons such as Importance of timely updates in distributed storage frameworks, particularly in mission-critical big data infrastructure, and recommending next steps like Upgrade to Hadoop version 3.4.2 or later, Conduct an immediate version audit of Hadoop deployments and Monitor HDFS logs for suspicious URI patterns.

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 vulnerability in Apache Hadoop’s HDFS native client (CVE-2025-27821). Under the Execution tactic, the analysis identified Exploitation for Client Execution (T1203) with moderate to high confidence (70%), supported by evidence indicating out-of-bounds write issue in the URI parser component of the HDFS native client. Under the Impact tactic, the analysis identified Endpoint Denial of Service (T1499) with high confidence (90%), supported by evidence indicating denial-of-service (DoS) conditions, complete system unavailability, Network Denial of Service (T1498) with moderate to high confidence (80%), supported by evidence indicating system crashes, memory corruption, and data loss in production environments, and Data Manipulation: Stored Data Manipulation (T1565.001) with moderate to high confidence (70%), supported by evidence indicating memory corruption, potential data loss in vulnerable HDFS clusters. Under the Defense Evasion tactic, the analysis identified Exploitation for Defense Evasion (T1211) with moderate confidence (60%), supported by evidence indicating manipulate untrusted input and overwrite memory beyond allocated boundaries. 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%)
Execution
Exploitation for Client Execution (70%)
Impact
Endpoint Denial of Service (90%)
Network Denial of Service (80%)
Data Manipulation: Stored Data Manipulation (70%)
Defense Evasion
Exploitation for Defense Evasion (60%)

Sources & References