Incident Score: Analysis & Impact (TP-HIKFOXGOOREVARITHEOPECIS1770645410)
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Rankiteo Score Impact Analysis
Key Highlights From The Incident Analysis
- Timeline of Foxit'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 Foxit 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 Foxit breach identified under incident ID TP-HIKFOXGOOREVARITHEOPECIS1770645410.
The analysis begins with a detailed overview of Foxit's information like the linkedin page: https://www.linkedin.com/company/foxit-corporation, the number of followers: 52049, the industry type: Software Development and the number of employees: 559 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 733 and after the incident was 713 with a difference of -20 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 Foxit 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%), supported by evidence indicating notepad++ WinGUp update verification flaw exploited, Phishing (T1566) with moderate to high confidence (80%), supported by evidence indicating state-sponsored phishing attacks via Signal app, Exploit Public-Facing Application (T1190) with moderate to high confidence (80%), supported by evidence indicating exposed OpenClaw gateways (port 18789) targeted, and Drive-by Compromise (T1189) with moderate to high confidence (70%), supported by evidence indicating malicious components in OpenClaw ClawHub marketplace. 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 RCE via DockerDash MCP Gateway, Command and Scripting Interpreter (T1059) with moderate to high confidence (70%), supported by evidence indicating shadowHS Linux post-exploitation framework runs in memory, and User Execution (T1204) with moderate to high confidence (70%), supported by evidence indicating malicious AI extensions in OpenClaw executed by users. Under the Persistence tactic, the analysis identified Web Shell (T1505.003) with moderate confidence (60%), supported by evidence indicating openClaw WebSocket API targeted for command execution and Create or Modify System Process (T1543) with moderate to high confidence (70%), supported by evidence indicating shadowHS framework includes persistence modules. 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 privilege escalation modules and Abuse Elevation Control Mechanism (T1548) with moderate confidence (60%), supported by evidence indicating openClaw AI agents with broad permissions exploited. 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, Disable or Modify Tools (T1562.001) with moderate to high confidence (70%), supported by evidence indicating shadowHS performs defensive tooling enumeration, Masquerading (T1036) with moderate to high confidence (80%), 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 etherHiding malware uses 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 credential access modules and Brute Force (T1110) with moderate confidence (60%), supported by evidence indicating signal PIN and device-linking features exploited. Under the Discovery tactic, the analysis identified Account Discovery (T1087) with moderate to high confidence (70%), supported by evidence indicating shadowHS performs system profiling and File and Directory Discovery (T1083) with moderate to high confidence (70%), supported by evidence indicating shadowHS framework includes discovery modules. 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 lateral movement modules. 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 and user data compromised and Automated Collection (T1119) with moderate to high confidence (70%), supported by evidence indicating moltBook AI agents interact without human oversight. Under the Command and Control tactic, the analysis identified Application Layer Protocol (T1071) with moderate to high confidence (80%), supported by evidence indicating etherHiding uses Ethereum smart contracts for C2 and Ingress Tool Transfer (T1105) with moderate to high confidence (70%), supported by evidence indicating shadowHS framework transfers tools post-exploitation. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with high confidence (90%), supported by evidence indicating data exfiltration via OpenClaw, ShadowHS, INC Ransomware and Exfiltration Over Alternative Protocol (T1048) with moderate to high confidence (70%), supported by evidence indicating aI agent data exfiltration risks via MoltBook. 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, Data Encrypted for Impact (T1486) with moderate to high confidence (80%), supported by evidence indicating iNC Ransomware data encryption, and Data Manipulation (T1565) with moderate to high confidence (70%), supported by evidence indicating prompt injection attacks on MoltBook AI agents. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.
Sources & References
- Foxit Rankiteo Cyber Incident Details: https://www.rankiteo.com/company/foxit-corporation/incident/TP-HIKFOXGOOREVARITHEOPECIS1770645410
- Foxit CyberSecurity Rating page: https://www.rankiteo.com/company/foxit-corporation
- Foxit Rankiteo Cyber Incident Blog Article: https://blog.rankiteo.com/tp-hikfoxgoorevaritheopecis1770645410-openclaw-notepad-hikvision-apache-syncope-foxit-tp-link-cisco-google-chrome-arista-ng-firewall-cyber-attack-november-2025/
- Foxit CyberSecurity Score History: https://www.rankiteo.com/company/foxit-corporation/history
- Foxit CyberSecurity Incident Source: https://thehackernews.com/2026/02/weekly-recap-ai-skill-malware-31tbps.html
- Rankiteo A.I CyberSecurity Rating methodology: https://www.rankiteo.com/Images/rankiteo_algo.pdf
- Rankiteo TPRM Scoring methodology: https://static.rankiteo.com/model/rankiteo_tprm_methodology.pdf