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Analyze » OpenClaw » 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-28
Company Score Before Incident802 / 1000
Company Score After Incident774 / 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 OpenClaw'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 OpenClaw 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 OpenClaw breach identified under incident ID TP-HIKFOXGOOREVARITHEOPECIS1770645410.

The analysis begins with a detailed overview of OpenClaw's information like the linkedin page: https://www.linkedin.com/company/openclaw, the number of followers: 0, the industry type: Technology, Information and Internet and the number of employees: 2 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 802 and after the incident was 774 with a difference of -28 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 OpenClaw 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%), supported by evidence indicating sophisticated supply chain attack targeted Notepad++ between June and December 2025, Compromise Software Supply Chain (T1195.002) with high confidence (90%), supported by evidence indicating threat actors redirected its WinGUp updater to malicious servers, Exploit Public-Facing Application (T1190) with moderate to high confidence (80%), supported by evidence indicating exposed OpenClaw gateways (port 18789) targeted for authentication bypasses, Phishing (T1566) with moderate to high confidence (80%), supported by evidence indicating state-sponsored phishing attacks via Signal exploiting PIN and device-linking features, and Trusted Relationship (T1199) with moderate to high confidence (70%), supported by evidence indicating attackers exploiting trusted systems, AI platforms, and open-source ecosystems. Under the Execution tactic, the analysis identified Exploitation for Client Execution (T1203) with moderate to high confidence (80%), supported by evidence indicating docker AI assistant vulnerable to RCE via DockerDash MCP Gateway, Command and Scripting Interpreter (T1059) with moderate to high confidence (70%), supported by evidence indicating malicious instructions in Docker image metadata executed without validation, and User Execution (T1204) with moderate confidence (60%), supported by evidence indicating malicious components in OpenClaw ClawHub marketplace. 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 bypassing AI layers to target WebSocket API directly and Create or Modify System Process (T1543) with moderate confidence (60%), supported by evidence indicating shadowHS fileless Linux post-exploitation framework runs entirely in memory. Under the Privilege Escalation tactic, the analysis identified Exploitation for Privilege Escalation (T1068) with moderate to high confidence (70%), supported by evidence indicating shadowHS includes modules for privilege escalation and Abuse Elevation Control Mechanism (T1548) with moderate confidence (60%), supported by evidence indicating openClaw AI agents with broad permissions and user-controlled configurations. Under the Defense Evasion tactic, the analysis identified Obfuscated Files or Information (T1027) with moderate to high confidence (80%), supported by evidence indicating shadowHS fileless Linux framework runs entirely in memory, Impair Defenses: Disable or Modify Tools (T1562.001) with moderate to high confidence (70%), supported by evidence indicating shadowHS includes aggressive defensive tooling enumeration, Masquerading (T1036) with moderate to high confidence (70%), supported by evidence indicating typosquatted claw packages on npm and PyPI, and Hijack Execution Flow: DLL Side-Loading (T1574.002) with moderate confidence (60%), supported by evidence indicating malicious npm packages using COM hijacking. Under the Credential Access tactic, the analysis identified Credentials from Password Stores (T1555) with moderate to high confidence (70%), supported by evidence indicating shadowHS includes modules for credential access, Brute Force (T1110) with moderate confidence (60%), supported by evidence indicating attackers reused stolen credentials to maintain control of Notepad++ update servers, and Adversary-in-the-Middle (T1557) with moderate confidence (50%), supported by evidence indicating signal phishing attacks exploiting device-linking features. Under the Discovery tactic, the analysis identified Account Discovery (T1087) with moderate to high confidence (70%), supported by evidence indicating shadowHS includes modules for lateral movement and system profiling, File and Directory Discovery (T1083) with moderate confidence (60%), supported by evidence indicating shadowHS framework includes data exfiltration modules, and Network Service Discovery (T1046) with moderate confidence (60%), supported by evidence indicating active scanning of exposed OpenClaw gateways (port 18789). Under the Lateral Movement tactic, the analysis identified Exploitation of Remote Services (T1210) with moderate to high confidence (70%), supported by evidence indicating shadowHS includes modules for lateral movement and Lateral Tool Transfer (T1570) with moderate confidence (60%), supported by evidence indicating fileless Linux framework designed for long-term control. Under the Collection tactic, the analysis identified Data from Local System (T1005) with moderate to high confidence (80%), supported by evidence indicating aI agent configurations, user data, and PII compromised, Automated Collection (T1119) with moderate to high confidence (70%), supported by evidence indicating moltBook AI agents interact without human oversight, and Data from Information Repositories (T1213) with moderate confidence (60%), supported by evidence indicating iDOR flaws in Spree allowed unauthorized access to user address data. Under the Command and Control tactic, the analysis identified Application Layer Protocol (T1071) with moderate to high confidence (80%), supported by evidence indicating etherHiding leverages Ethereum smart contracts to fetch C2 servers, Ingress Tool Transfer (T1105) with moderate to high confidence (70%), supported by evidence indicating malicious npm packages using system profiling and sandbox evasion, and Proxy (T1090) with moderate confidence (60%), supported by evidence indicating botnet operations discussed on Exploit.in for OpenClaw. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with high confidence (90%), supported by evidence indicating data exfiltration confirmed in OpenClaw, ShadowHS, and INC Ransomware incidents, Exfiltration Over Web Service (T1567) with moderate to high confidence (70%), supported by evidence indicating aI agents with persistent memory and data exfiltration risks, and Exfiltration Over Alternative Protocol (T1048) with moderate confidence (60%), supported by evidence indicating shadowHS framework includes data exfiltration modules. Under the Impact tactic, the analysis identified Network Denial of Service (T1498) with high confidence (90%), supported by evidence indicating 31.4 Tbps DDoS attack by AISURU/Kimwolf botnet in November 2025, Data Encrypted for Impact (T1486) with moderate to high confidence (80%), supported by evidence indicating iNC Ransomware data encryption confirmed, Data Manipulation (T1565) with moderate to high confidence (70%), supported by evidence indicating prompt injection attacks and social engineering exploits on MoltBook, and Data Destruction (T1485) with moderate confidence (50%), supported by evidence indicating malware infection risks in supply chain 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%)
Exploit Public-Facing Application (80%)
Phishing (80%)
Trusted Relationship (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%)
Adversary-in-the-Middle (50%)
Discovery
Account Discovery (70%)
File and Directory Discovery (60%)
Network Service Discovery (60%)
Lateral Movement
Exploitation of Remote Services (70%)
Lateral Tool Transfer (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 (90%)
Exfiltration Over Web Service (70%)
Exfiltration Over Alternative Protocol (60%)
Impact
Network Denial of Service (90%)
Data Encrypted for Impact (80%)
Data Manipulation (70%)
Data Destruction (50%)