Rankiteo Logo
Rankiteo
Leader in Cyber Underwriting
Loading...
NEWRankiteo Cyber Underwriting Desktop - Score, price, and bind from your desktop
WindowsmacOSLinux
Download
Analyze » PyPI » GITPYP1783002615

Incident Score: Analysis & Impact (GITPYP1783002615)

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

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-14
Company Score Before Incident793 / 1000
Company Score After Incident779 / 1000
Company LinkView PyPI Profile
INCIDENT NUMBERGITPYP1783002615
Type of Cyber IncidentCyber Attack
ATTACK VECTORPoisoned GitHub repositories, Malicious Python packages on PyPI
DATA EXPOSEDExploit code, System information, Browser...
INCIDENT DATE31/12/2022
STATUSpublished

Key Highlights From The Incident Analysis

  • Timeline of PyPI'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 PyPI 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 PyPI breach identified under incident ID GITPYP1783002615.

The analysis begins with a detailed overview of PyPI's information like the linkedin page: https://www.linkedin.com/company/pypi, the number of followers: 0, the industry type: Software Development and the number of employees: 4 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 793 and after the incident was 779 with a difference of -14 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 PyPI and their customers.

A newly reported cybersecurity incident, "ChocoPoC Campaign Targets Security Researchers with Trojanized Exploit Code", has drawn attention.

Security researchers have uncovered *ChocoPoC*, a long-running cyber campaign that weaponizes trusted proof-of-concept (PoC) exploits to deploy a Python-based remote access trojan (RAT) against vulnerability researchers.

The disruption is felt across the environment, affecting Systems of security researchers, and exposing Exploit code, System information and Browser data.

Formal response steps have not been shared publicly yet.

The case underscores how teams are taking away lessons such as The attack exploits the trust within the open-source research community, where disabling security tools during testing makes researchers particularly vulnerable. Highlights the growing threat of supply-chain attacks within the cybersecurity research ecosystem.

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 Supply Chain (T1195.002) with high confidence (95%), supported by evidence indicating poisoned GitHub repositories and malicious Python packages on PyPI and Phishing: Spearphishing Attachment (T1566.001) with moderate to high confidence (80%), supported by evidence indicating trojanized exploit code...appears to be legitimate PoC code. Under the Execution tactic, the analysis identified User Execution: Malicious File (T1204.002) with high confidence (90%), supported by evidence indicating victims who download and execute what appears to be legitimate PoC code and Command and Scripting Interpreter: Python (T1059.006) with high confidence (90%), supported by evidence indicating python-based remote access trojan (RAT)...capable of command execution. 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 compiled native Python extension (*gradient.so*...loaded directly into memory) and Boot or Logon Autostart Execution: Registry Run Keys / Startup Folder (T1547.001) with moderate confidence (60%), supported by evidence indicating multi-stage infection process...further payload delivery. Under the Defense Evasion tactic, the analysis identified Obfuscated Files or Information: Software Packing (T1027.002) with high confidence (90%), supported by evidence indicating compiled native Python extension loaded directly into memory to evade detection, Debugger Evasion (T1622) with moderate to high confidence (85%), supported by evidence indicating anti-debugging checks, scanning for hardware breakpoints and remote debuggers, and Application Layer Protocol: DNS (T1071.004) with moderate to high confidence (80%), supported by evidence indicating dNS-over-HTTPS resolvers (*dns.alidns.com*, *cloudflare-dns.com*). Under the Command and Control tactic, the analysis identified Web Service: One-Way Communication (T1102.003) with high confidence (90%), supported by evidence indicating abuse the legitimate *Mapbox Datasets API* as a C2 channel and Application Layer Protocol: Web Protocols (T1071.001) with moderate to high confidence (85%), supported by evidence indicating blending malicious traffic with normal web requests. Under the Collection tactic, the analysis identified Data from Local System (T1005) with high confidence (90%), supported by evidence indicating steal files, harvest browser data, and gather system information and Input Capture: Keylogging (T1056.001) with moderate confidence (60%), supported by evidence indicating python RAT...capable of data theft. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with high confidence (90%), supported by evidence indicating data theft...abuse the legitimate *Mapbox Datasets API* as a C2 channel and Exfiltration Over Web Service: Exfiltration to Cloud Storage (T1567.002) with moderate to high confidence (70%), supported by evidence indicating dead-drop C2 server...blending malicious traffic with normal web requests. Under the Impact tactic, the analysis identified Resource Hijacking (T1496) with moderate to high confidence (70%), supported by evidence indicating targets vulnerability researchers...access to unpublished exploits. 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: Compromise Software Supply Chain (95%)
Phishing: Spearphishing Attachment (80%)
Execution
User Execution: Malicious File (90%)
Command and Scripting Interpreter: Python (90%)
Persistence
Hijack Execution Flow: DLL Search Order Hijacking (80%)
Boot or Logon Autostart Execution: Registry Run Keys / Startup Folder (60%)
Defense Evasion
Obfuscated Files or Information: Software Packing (90%)
Debugger Evasion (85%)
Application Layer Protocol: DNS (80%)
Command and Control
Web Service: One-Way Communication (90%)
Application Layer Protocol: Web Protocols (85%)
Collection
Data from Local System (90%)
Input Capture: Keylogging (60%)
Exfiltration
Exfiltration Over C2 Channel (90%)
Exfiltration Over Web Service: Exfiltration to Cloud Storage (70%)
Impact
Resource Hijacking (70%)

Sources & References