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Analyze » The Apache Software Foundation » TP-HIKFOXGOOREVARITHEOPECIS1770645410

Incident Score: Analysis & Impact (TP-HIKFOXGOOREVARITHEOPECIS1770645410)

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

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-19
Company Score Before Incident620 / 1000
Company Score After Incident601 / 1000
INCIDENT NUMBERTP-HIKFOXGOOREVARITHEOPECIS1770645410
Type of Cyber IncidentCyber Attack
ATTACK VECTORMalicious AI Extensions, Compromised Software Updates, Exposed APIs, Phishing via Messaging Apps, Typosquatting, Ethereum Smart Contracts, Insecure Direct Object Reference (IDOR)
DATA EXPOSEDAI Agent Configurations, User Data...
INCIDENT DATE31/10/2025
STATUSOngoing

Key Highlights From The Incident Analysis

  • Timeline of The Apache Software Foundation'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 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 TP-HIKFOXGOOREVARITHEOPECIS1770645410.

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 620 and after the incident was 601 with a difference of -19 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.

OpenClaw recently reported "Cybersecurity Roundup: Trust Abuse, AI Risks, and Supply Chain Attacks Dominate Threat Landscape", a noteworthy cybersecurity incident.

This week’s cybersecurity developments highlight attackers exploiting trusted systems, AI platforms, software updates, messaging apps, and open-source ecosystems to bypass security controls.

The disruption is felt across the environment, affecting OpenClaw AI Framework, Notepad++ and Docker AI Assistant, and exposing AI Agent Configurations, User Data on MoltBook and Credentials.

In response, moved swiftly to contain the threat with measures like Starlink Terminal Verification System (Ukraine), Docker Patch (MCP Gateway RCE) and Notepad++ Update Verification Fix, and began remediation that includes OpenClaw Gateway Scanning, AI Backdoor Scanner (Microsoft) and Enhanced Monitoring for Exposed OpenClaw Instances.

The case underscores how Ongoing, teams are taking away lessons such as Attackers are increasingly exploiting trust in ecosystems (AI, software updates, messaging apps) rather than relying on traditional malware. Organizations must monitor integrations, verify updates, and secure AI deployments to mitigate risks from state-sponsored actors and cybercriminals, and recommending next steps like Scan AI extensions for malware (e.g., VirusTotal integration), Verify software updates and supply chain integrity and Secure AI deployments with encryption-at-rest and containerization.

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 Supply Chain Compromise (T1195) with high confidence (90%), with evidence including sophisticated supply chain attack targeted Notepad++, and winGUp updater redirected to malicious servers, Compromise Software Supply Chain (T1195.002) with high confidence (90%), with evidence including notepad++ WinGUp update verification flaw exploited, and docker AI assistant RCE via malicious image metadata, Phishing (T1566) with moderate to high confidence (80%), with evidence including state-sponsored phishing attacks via Signal, and exploiting PIN and device-linking features, Exploit Public-Facing Application (T1190) with moderate to high confidence (80%), with evidence including exposed OpenClaw gateways (port 18789) targeted, and 21,639 exposed OpenClaw instances identified, and Drive-by Compromise (T1189) with moderate to high confidence (70%), with evidence including malicious components in OpenClaw ClawHub marketplace, and typosquatted claw packages on npm and PyPI. Under the Execution tactic, the analysis identified Exploitation for Client Execution (T1203) with moderate to high confidence (80%), with evidence including docker MCP Gateway RCE via malicious instructions, and notepad++ WinGUp update verification flaw, Command and Scripting Interpreter (T1059) with moderate to high confidence (70%), with evidence including shadowHS fileless Linux framework runs in memory, and modules for command execution, and User Execution (T1204) with moderate confidence (60%), with evidence including malicious AI extensions in OpenClaw, and typosquatted packages on npm/PyPI. Under the Persistence tactic, the analysis identified Server Software Component: Web Shell (T1505.003) with moderate to high confidence (70%), supported by evidence indicating attackers bypassed OpenClaw AI layers to target WebSocket API and Create or Modify System Process (T1543) with moderate confidence (60%), with evidence including shadowHS fileless framework runs in memory, and prioritizes stealth and long-term control. Under the Privilege Escalation tactic, the analysis identified Exploitation for Privilege Escalation (T1068) with moderate to high confidence (70%), with evidence including shadowHS includes privilege escalation modules, and openClaw authentication bypasses and Abuse Elevation Control Mechanism (T1548) with moderate confidence (60%), with evidence including signal PIN/device-linking features hijacked, and openClaw outdated trust model. Under the Defense Evasion tactic, the analysis identified Obfuscated Files or Information (T1027) with moderate to high confidence (80%), with evidence including shadowHS fileless framework runs entirely in memory, and etherHiding uses Ethereum smart contracts for C2, Impair Defenses: Disable or Modify Tools (T1562.001) with moderate to high confidence (70%), with evidence including shadowHS includes defensive tooling enumeration, and aggressive evasion tactics, Masquerading (T1036) with moderate to high confidence (70%), with evidence including typosquatted claw packages on npm/PyPI, and malicious AI extensions in ClawHub, and Hijack Execution Flow: DLL Side-Loading (T1574.002) with moderate confidence (60%), with evidence including etherHiding malware uses COM hijacking, and targets Windows systems. Under the Credential Access tactic, the analysis identified Credentials from Password Stores (T1555) with moderate to high confidence (70%), with evidence including shadowHS includes credential access modules, and openClaw authentication bypasses and Brute Force (T1110) with moderate confidence (60%), with evidence including signal account hijacking via PIN/device-linking, and openClaw exposed gateways. Under the Discovery tactic, the analysis identified Account Discovery (T1087) with moderate to high confidence (70%), with evidence including shadowHS includes system profiling, and targets high-value officials via Signal, File and Directory Discovery (T1083) with moderate confidence (60%), supported by evidence indicating shadowHS fileless framework enumerates defensive tools, and Network Service Scanning (T1046) with moderate to high confidence (80%), with evidence including active scanning of exposed OpenClaw gateways (port 18789), and 21,639 exposed instances identified. Under the Lateral Movement tactic, the analysis identified Exploitation of Remote Services (T1210) with moderate to high confidence (70%), with evidence including shadowHS includes lateral movement modules, and openClaw WebSocket API targeted and Remote Services (T1021) with moderate confidence (60%), with evidence including openClaw gateways exploited for command execution, and docker AI assistant RCE. Under the Collection tactic, the analysis identified Data from Local System (T1005) with moderate to high confidence (80%), with evidence including aI agent configurations compromised, and user data on MoltBook at risk, Automated Collection (T1119) with moderate to high confidence (70%), with evidence including moltBook AI agents interact without human oversight, and 506 prompt injection attacks identified, and Data from Information Repositories (T1213) with moderate confidence (60%), with evidence including spree IDOR flaws exposed user address data, and pII and payment info compromised. Under the Command and Control tactic, the analysis identified Application Layer Protocol (T1071) with moderate to high confidence (80%), with evidence including openClaw WebSocket API targeted for C2, and etherHiding uses Ethereum smart contracts, Ingress Tool Transfer (T1105) with moderate to high confidence (70%), with evidence including malicious AI extensions fetched from ClawHub, and typosquatted packages on npm/PyPI, and Proxy (T1090) with moderate confidence (60%), with evidence including etherHiding complicates C2 takedowns via blockchain, and shadowHS uses stealthy C2. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with moderate to high confidence (80%), with evidence including data exfiltration via OpenClaw and ShadowHS, and iNC Ransomware exfiltrated victim data and Exfiltration Over Web Service (T1567) with moderate to high confidence (70%), with evidence including aI agent data exfiltration risks, and moltBook unregulated cryptocurrency activity. Under the Impact tactic, the analysis identified Network Denial of Service (T1498) with high confidence (90%), with evidence including 31.4 Tbps DDoS attack by AISURU/Kimwolf botnet, and dDoS attacks surged 121% in 2025, Data Encrypted for Impact (T1486) with moderate to high confidence (80%), with evidence including iNC Ransomware encrypted victim data, and data exfiltration confirmed, and Data Manipulation (T1565) with moderate to high confidence (70%), with evidence including moltBook AI agents manipulated for social engineering, and prompt injection attacks. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.

Initial Access
Supply Chain Compromise (90%)
Compromise Software Supply Chain (90%)
Phishing (80%)
Exploit Public-Facing Application (80%)
Drive-by Compromise (70%)
Execution
Exploitation for Client Execution (80%)
Command and Scripting Interpreter (70%)
User Execution (60%)
Persistence
Server Software Component: Web Shell (70%)
Create or Modify System Process (60%)
Privilege Escalation
Exploitation for Privilege Escalation (70%)
Abuse Elevation Control Mechanism (60%)
Defense Evasion
Obfuscated Files or Information (80%)
Impair Defenses: Disable or Modify Tools (70%)
Masquerading (70%)
Hijack Execution Flow: DLL Side-Loading (60%)
Credential Access
Credentials from Password Stores (70%)
Brute Force (60%)
Discovery
Account Discovery (70%)
File and Directory Discovery (60%)
Network Service Scanning (80%)
Lateral Movement
Exploitation of Remote Services (70%)
Remote Services (60%)
Collection
Data from Local System (80%)
Automated Collection (70%)
Data from Information Repositories (60%)
Command and Control
Application Layer Protocol (80%)
Ingress Tool Transfer (70%)
Proxy (60%)
Exfiltration
Exfiltration Over C2 Channel (80%)
Exfiltration Over Web Service (70%)
Impact
Network Denial of Service (90%)
Data Encrypted for Impact (80%)
Data Manipulation (70%)

Sources & References