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Analyze » TP-Link » 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-18
Company Score Before Incident706 / 1000
Company Score After Incident688 / 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 TP-Link'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 TP-Link 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 TP-Link breach identified under incident ID TP-HIKFOXGOOREVARITHEOPECIS1770645410.

The analysis begins with a detailed overview of TP-Link's information like the linkedin page: https://www.linkedin.com/company/tp-link-corporation, the number of followers: 61740, the industry type: Computers and Electronics Manufacturing and the number of employees: 8511 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 706 and after the incident was 688 with a difference of -18 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 TP-Link 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 users likely executed compromised updates. Under the Persistence tactic, the analysis identified Web Shell (T1505.003) with moderate to high confidence (70%), supported by evidence indicating attackers bypassed OpenClaw AI layers to target WebSocket API, Create or Modify System Process (T1543) with moderate confidence (60%), supported by evidence indicating shadowHS post-exploitation framework for long-term control, and Event Triggered Execution (T1546) with moderate confidence (50%), supported by evidence indicating cOM hijacking in EtherHiding malware. 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 authentication bypasses in OpenClaw WebSocket API. 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 includes defensive tooling enumeration, Masquerading (T1036) with moderate to high confidence (70%), supported by evidence indicating typosquatted claw packages on npm and PyPI, Code Signing (T1553.002) with moderate confidence (60%), supported by evidence indicating compromised Notepad++ updates via legitimate domains, and Exploitation for Defense Evasion (T1211) with moderate confidence (60%), supported by evidence indicating etherHiding uses Ethereum smart contracts for C2. 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, Brute Force (T1110) with moderate confidence (60%), supported by evidence indicating attackers reused stolen credentials for Notepad++, and Adversary-in-the-Middle (T1557) with moderate confidence (50%), supported by evidence indicating signal phishing exploited 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 system profiling modules, Network Service Scanning (T1046) with moderate to high confidence (70%), supported by evidence indicating active scanning of exposed OpenClaw gateways, and File and Directory Discovery (T1083) with moderate confidence (60%), supported by evidence indicating shadowHS post-exploitation framework for data discovery. 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 and Remote Services (T1021) with moderate confidence (60%), supported by evidence indicating openClaw WebSocket API targeted for command execution. Under the Collection tactic, the analysis identified Data from Local System (T1005) with moderate to high confidence (80%), with evidence including aI agent configurations and user data compromised, and shadowHS data exfiltration modules, 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 spree IDOR flaws allowed unauthorized access to user data. 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%), supported by evidence indicating malicious components in OpenClaw ClawHub marketplace, and Proxy (T1090) with moderate confidence (60%), supported by evidence indicating botnet operations discussed for OpenClaw. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with high confidence (90%), with evidence including data exfiltration via OpenClaw, ShadowHS, INC Ransomware, and aI agent data exfiltration risks and Exfiltration Over Web Service (T1567) with moderate to high confidence (70%), supported by evidence indicating etherHiding uses Ethereum smart contracts for C2. 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, Data Manipulation (T1565) with moderate to high confidence (70%), supported by evidence indicating prompt injection attacks on MoltBook AI agents, 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%)
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
Web Shell (70%)
Create or Modify System Process (60%)
Event Triggered Execution (50%)
Privilege Escalation
Exploitation for Privilege Escalation (70%)
Abuse Elevation Control Mechanism (60%)
Defense Evasion
Obfuscated Files or Information (80%)
Disable or Modify Tools (70%)
Masquerading (70%)
Code Signing (60%)
Exploitation for Defense Evasion (60%)
Credential Access
Credentials from Password Stores (70%)
Brute Force (60%)
Adversary-in-the-Middle (50%)
Discovery
Account Discovery (70%)
Network Service Scanning (70%)
File and Directory Discovery (60%)
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 (90%)
Exfiltration Over Web Service (70%)
Impact
Network Denial of Service (90%)
Data Encrypted for Impact (80%)
Data Manipulation (70%)
Data Destruction (50%)