Incident Score: Analysis & Impact (DROROBNPMGIT1773476652)
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 GitHub'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 GitHub 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 GitHub breach identified under incident ID DROROBNPMGIT1773476652.
The analysis begins with a detailed overview of GitHub's information like the linkedin page: https://www.linkedin.com/company/github, the number of followers: 5688458, the industry type: Software Development and the number of employees: 6007 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 482 and after the incident was 468 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 GitHub and their customers.
On 12 March 2026, npm users (Windows) disclosed Infostealer issues under the banner "Sophisticated npm-Based Infostealer Targets Windows Users via Malicious Packages".
JFrog security researchers uncovered a stealthy cyberattack leveraging the npm ecosystem to distribute the Cipher infostealer.
The disruption is felt across the environment, affecting Windows systems with npm package installations, and exposing Discord credentials, 2FA codes, credit card details, browser data (passwords, cookies, autofill, history), cryptocurrency wallet seeds.
In response, moved swiftly to contain the threat with measures like Malicious npm packages and Dropbox links neutralized.
The case underscores how Ongoing, teams are taking away lessons such as Highlights risks of supply-chain attacks in open-source ecosystems; need for vigilance in dependency management, and recommending next steps like Enhanced scrutiny of npm packages, monitoring for pre-install scripts, and improved detection of obfuscated payloads.
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 (T1195.001) with high confidence (95%), supported by evidence indicating malicious npm packages such as bluelite-bot-manager and test-logsmodule-v-zisko and User Execution: Malicious File (T1204.002) with moderate to high confidence (80%), supported by evidence indicating pre-install scripts in npm packages downloaded Windows executable from Dropbox. Under the Execution tactic, the analysis identified Command and Scripting Interpreter: JavaScript (T1059.007) with high confidence (90%), supported by evidence indicating obfuscated JavaScript in 321MB archive, Node.js environment embedded, Command and Scripting Interpreter: Python (T1059.006) with moderate to high confidence (85%), supported by evidence indicating embedded Python script in archive; downloaded Python if not installed, and User Execution: Malicious File (T1204.002) with moderate to high confidence (80%), supported by evidence indicating windows executable acted as dropper for malicious payload. Under the Privilege Escalation tactic, the analysis identified Abuse Elevation Control Mechanism: Bypass User Account Control (T1548.002) with moderate to high confidence (80%), supported by evidence indicating elevate.exe (legitimate tool) repurposed to escalate privileges. Under the Defense Evasion tactic, the analysis identified Obfuscated Files or Information (T1027) with high confidence (95%), supported by evidence indicating 321MB archive contained obfuscated JavaScript; evaded VirusTotal detection, Masquerading: Match Legitimate Name or Location (T1036.005) with high confidence (90%), supported by evidence indicating malware disguised as Roblox script executor named Solara, and Subvert Trust Controls: Install Root Certificate (T1553.004) with lower confidence (30%), supported by evidence indicating no direct evidence, but implied by evasion of webhook protections. Under the Credential Access tactic, the analysis identified Credentials from Password Stores: Credentials from Web Browsers (T1555.003) with high confidence (95%), supported by evidence indicating stole passwords, cookies, autofill data from Chrome, Edge, Brave, Opera, Yandex, Credentials from Password Stores: Windows Credential Manager (T1555.004) with moderate to high confidence (70%), supported by evidence indicating system-wide sweep for sensitive data; likely targeted credential stores, Steal Application Access Token (T1528) with high confidence (90%), supported by evidence indicating captured Discord credentials, 2FA codes, credit card details via forced re-login, and Unsecured Credentials: Credentials In Files (T1552.001) with moderate to high confidence (85%), supported by evidence indicating decrypted Exodus wallet seed files using local libraries. Under the Collection tactic, the analysis identified Data from Local System (T1005) with high confidence (95%), supported by evidence indicating system-wide sweep for browser data, cryptocurrency wallets, Discord credentials and Automated Collection (T1119) with high confidence (90%), supported by evidence indicating malware conducted automated sweep for sensitive data across browsers/wallets. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with high confidence (90%), supported by evidence indicating stolen data transmitted to attackers via C2 server or file-sharing services and Exfiltration Over Web Service: Exfiltration to Cloud Storage (T1567.002) with moderate to high confidence (85%), supported by evidence indicating data compressed into ZIP file; likely exfiltrated via Dropbox/file-sharing. Under the Persistence tactic, the analysis identified Boot or Logon Autostart Execution: Registry Run Keys / Startup Folder (T1547.001) with moderate to high confidence (70%), supported by evidence indicating modified Discord installation files to auto-execute malicious script and Hijack Execution Flow: DLL Side-Loading (T1574.002) with moderate confidence (60%), supported by evidence indicating patched BetterDiscord core files to disable webhook protections. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.
Sources & References
- GitHub Rankiteo Cyber Incident Details: https://www.rankiteo.com/company/github/incident/DROROBNPMGIT1773476652
- GitHub CyberSecurity Rating page: https://www.rankiteo.com/company/github
- GitHub Rankiteo Cyber Incident Blog Article: https://blog.rankiteo.com/drorobnpmgit1773476652-github-npm-dropbox-roblox-cyber-attack-march-2026/
- GitHub CyberSecurity Score History: https://www.rankiteo.com/company/github/history
- GitHub CyberSecurity Incident Source: https://cyberpress.org/malicious-npm-campaign-steal-discord-and-crypto-wallet-data/
- 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