Rankiteo Logo
Rankiteo
Leader in Cyber Underwriting
Loading...
NEWRankiteo Cyber Underwriting Desktop - Score, price, and bind from your desktop
WindowsmacOSLinux
Download
Analyze » Proofpoint » MOZPHAGITPROGOOGIT1780935989

Incident Score: Analysis & Impact (MOZPHAGITPROGOOGIT1780935989)

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

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-19
Company Score Before Incident704 / 1000
Company Score After Incident685 / 1000
INCIDENT NUMBERMOZPHAGITPROGOOGIT1780935989
Type of Cyber IncidentCyber Attack
ATTACK VECTORMalicious emails with fake job offers and code-review requests, malicious GitHub/GitLab repositories
DATA EXPOSEDBrowser credentials, cryptocurrency wallet data,...
INCIDENT DATE31/03/2026
STATUSOngoing

Key Highlights From The Incident Analysis

  • Timeline of Proofpoint'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 Proofpoint 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 Proofpoint breach identified under incident ID MOZPHAGITPROGOOGIT1780935989.

The analysis begins with a detailed overview of Proofpoint's information like the linkedin page: https://www.linkedin.com/company/proofpoint, the number of followers: 182427, the industry type: Computer and Network Security and the number of employees: 4976 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 704 and after the incident was 685 with a difference of -19 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 Proofpoint and their customers.

A newly reported cybersecurity incident, "North Korean Threat Actor Targets Developers in Large-Scale Phishing Campaign", has drawn attention.

A likely North Korean threat actor conducted a sophisticated phishing campaign targeting nearly 100 organizations primarily in the U.S.

The disruption is felt across the environment, affecting macOS, Linux, Windows systems running VS Code or Cursor, and exposing Browser credentials, cryptocurrency wallet data, saved passwords, cookies, plus an estimated financial loss of Cryptocurrency wallet drainage.

Formal response steps have not been shared publicly yet.

The case underscores how Ongoing.

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 Phishing (T1566) with high confidence (95%), with evidence including sent over 250 malicious emails in April and May 2026, and fake job offers and code-review requests and Phishing: Spearphishing Link (T1566.001) with high confidence (90%), supported by evidence indicating lure victims into cloning malicious GitHub or GitLab repositories. Under the Execution tactic, the analysis identified Command and Scripting Interpreter: JavaScript (T1059.007) with moderate to high confidence (80%), supported by evidence indicating windows ran JavaScript directly in the editor, leaving no disk footprint, User Execution: Malicious File (T1204.002) with moderate to high confidence (85%), supported by evidence indicating exploiting a legitimate editor feature via tasks.json file executed automatically, and Serverless Execution (T1648) with moderate to high confidence (70%), supported by evidence indicating javaScript ran directly in the editor without disk footprint. Under the Persistence tactic, the analysis identified Browser Extensions (T1176) with high confidence (90%), supported by evidence indicating installed a fake Google-themed VS Code extension for persistence and Boot or Logon Autostart Execution: XDG Autostart Entries (T1547.013) with moderate to high confidence (70%), supported by evidence indicating malware relaunched on macOS and Linux whenever the editor reopened. Under the Privilege Escalation tactic, the analysis identified Abuse Elevation Control Mechanism: Sudo and Sudo Caching (T1548.003) with moderate to high confidence (85%), supported by evidence indicating macOS/Linux displayed a fake password prompt to escalate privileges. Under the Defense Evasion tactic, the analysis identified Masquerading (T1036) with high confidence (90%), with evidence including fake Google-themed VS Code extension, and fake password prompt, Indicator Removal: File Deletion (T1070.004) with moderate to high confidence (85%), supported by evidence indicating malware deleted itself after exfiltration to evade detection, and Deobfuscate/Decode Files or Information (T1140) with moderate to high confidence (70%), supported by evidence indicating malware likely obfuscated to bypass security. Under the Credential Access tactic, the analysis identified Credentials from Password Stores (T1555) with high confidence (90%), supported by evidence indicating targeted saved passwords & cookies from Chrome, Brave, Edge, and Firefox, Credentials from Password Stores: Credentials from Web Browsers (T1555.003) with high confidence (90%), supported by evidence indicating dumped keychains on macOS/Linux to extract credentials, and Steal Application Access Token (T1528) with moderate to high confidence (80%), supported by evidence indicating bypassed Chrome’s app-bound encryption to extract data. Under the Collection tactic, the analysis identified Data from Local System (T1005) with high confidence (90%), supported by evidence indicating targeted cryptocurrency wallets and browser credentials and Automated Collection (T1119) with moderate to high confidence (80%), supported by evidence indicating malware systematically collected wallet and credential data. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with high confidence (90%), supported by evidence indicating go-based RAT from Overlord framework for remote access and Exfiltration Over Web Service (T1567) with moderate to high confidence (70%), supported by evidence indicating likely exfiltrated data via C2 infrastructure. Under the Impact tactic, the analysis identified Resource Hijacking (T1496) with moderate to high confidence (80%), supported by evidence indicating cryptocurrency wallet drainage for financial gain. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.

Initial Access
Phishing (95%)
Phishing: Spearphishing Link (90%)
Execution
Command and Scripting Interpreter: JavaScript (80%)
User Execution: Malicious File (85%)
Serverless Execution (70%)
Persistence
Browser Extensions (90%)
Boot or Logon Autostart Execution: XDG Autostart Entries (70%)
Privilege Escalation
Abuse Elevation Control Mechanism: Sudo and Sudo Caching (85%)
Defense Evasion
Masquerading (90%)
Indicator Removal: File Deletion (85%)
Deobfuscate/Decode Files or Information (70%)
Credential Access
Credentials from Password Stores (90%)
Credentials from Password Stores: Credentials from Web Browsers (90%)
Steal Application Access Token (80%)
Collection
Data from Local System (90%)
Automated Collection (80%)
Exfiltration
Exfiltration Over C2 Channel (90%)
Exfiltration Over Web Service (70%)
Impact
Resource Hijacking (80%)