Incident Score: Analysis & Impact (FORPALGITIVA1782980964)
The details regarding individual company incidents & reports gives you full view from every side.
Rankiteo Score Impact Analysis
Key Highlights From The Incident Analysis
- Timeline of Ivanti'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 Ivanti 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 Ivanti breach identified under incident ID FORPALGITIVA1782980964.
The analysis begins with a detailed overview of Ivanti's information like the linkedin page: https://www.linkedin.com/company/ivanti, the number of followers: 185186, the industry type: Software Development and the number of employees: 3008 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 641 and after the incident was 632 with a difference of -9 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 Ivanti and their customers.
A newly reported cybersecurity incident, "Sophisticated Supply-Chain Attack via GitHub PoCs Targeting Cybersecurity Researchers", has drawn attention.
A coordinated supply-chain campaign exploited GitHub proof-of-concept (PoC) repositories to deploy a stealthy Python-based Remote Access Trojan (RAT) called *ChocoPoC*, targeting vulnerability researchers and penetration testers.
The disruption is felt across the environment, affecting Researchers' development environments, Python-based systems, and exposing Credentials (Chrome, Edge, Brave, Firefox), shell history, system reconnaissance data, files.
In response, and began remediation that includes Removal of malicious Python packages (*skytext*, *frint*, *slogsec*), cleanup of trojanized dependencies (*_distutils_hack*, *.pth* files).
The case underscores how Ongoing, teams are taking away lessons such as Risks of unvetted PoC dependencies, need for isolated testing environments, and rigorous dependency analysis, and recommending next steps like Use isolated environments for testing PoCs, Analyze dependencies rigorously and Monitor for malicious PyPI packages and C2 infrastructure.
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: Compromise Software Dependencies and Development Tools (T1195.002) with high confidence (95%), with evidence including exploited GitHub proof-of-concept (PoC) repositories to deploy a stealthy Python-based RAT, and malicious entries in *requirements.txt* (packages *frint* and *skytext*) and Phishing: Spearphishing Attachment (T1566.001) with moderate to high confidence (80%), supported by evidence indicating tricking victims into installing malicious dependencies under the guise of legitimate exploit development tools. Under the Execution tactic, the analysis identified Command and Scripting Interpreter: Python (T1059.006) with high confidence (90%), supported by evidence indicating malicious Python dependencies (*frint*, *skytext*) execute obfuscated code via *pip install* and User Execution: Malicious File (T1204.002) with moderate to high confidence (85%), supported by evidence indicating researchers run *pip install* on malicious *requirements.txt* entries. Under the Persistence tactic, the analysis identified Hijack Execution Flow: DLL Search Order Hijacking (T1574.001) with moderate to high confidence (80%), supported by evidence indicating trojanized *_distutils_hack* package and malicious *.pth* files in *site-packages* and Event Triggered Execution: Python Module Load (T1546.013) with moderate to high confidence (85%), supported by evidence indicating malicious *.pth* files ensure execution on every Python interpreter startup. Under the Defense Evasion tactic, the analysis identified Obfuscated Files or Information (T1027) with high confidence (90%), supported by evidence indicating obfuscated code with anti-analysis measures, including debugger detection, Virtualization/Sandbox Evasion: System Checks (T1497.001) with moderate to high confidence (85%), supported by evidence indicating malware remains dormant in sandboxes until triggered by specific runtime conditions, and Masquerading: Match Legitimate Name or Location (T1036.005) with moderate to high confidence (80%), supported by evidence indicating seemingly authentic PoC repositories with malicious dependencies. Under the Credential Access tactic, the analysis identified Credentials from Password Stores: Credentials from Web Browsers (T1555.003) with high confidence (90%), supported by evidence indicating credential theft (Chrome, Edge, Brave, Firefox) and Unsecured Credentials: Bash History (T1552.003) with moderate to high confidence (80%), supported by evidence indicating shell history harvesting. Under the Collection tactic, the analysis identified Data from Local System (T1005) with high confidence (90%), supported by evidence indicating file exfiltration, system reconnaissance data collection and Data from Information Repositories: Code Repositories (T1213.003) with moderate to high confidence (70%), supported by evidence indicating targeting vulnerability researchers and penetration testers. Under the Command and Control tactic, the analysis identified Application Layer Protocol: DNS-over-HTTPS (DoH) (T1071.004) with high confidence (90%), supported by evidence indicating dNS-over-HTTPS (DoH) to resolve *api.mapbox.com* to attacker-controlled IP and Web Service: Bidirectional Communication (T1102.002) with moderate to high confidence (85%), supported by evidence indicating mapbox datasets as a covert command-and-control (C2) channel. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with high confidence (90%), supported by evidence indicating data exfiltration via Mapbox C2 channel, Base64-encoded payloads and Exfiltration Over Web Service: Exfiltration to Cloud Storage (T1567.002) with moderate to high confidence (80%), supported by evidence indicating mapbox datasets used for C2 and exfiltration. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.
Sources & References
- Ivanti Rankiteo Cyber Incident Details: https://www.rankiteo.com/company/ivanti/incident/FORPALGITIVA1782980964
- Ivanti CyberSecurity Rating page: https://www.rankiteo.com/company/ivanti
- Ivanti Rankiteo Cyber Incident Blog Article: https://blog.rankiteo.com/forpalgitiva1782980964-ivanti-fortinet-github-palo-alto-networks-vulnerability-october-2025/
- Ivanti CyberSecurity Score History: https://www.rankiteo.com/company/ivanti/history
- Ivanti CyberSecurity Incident Source: https://gbhackers.com/chocopoc-campaign-abuses-github/
- 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