Incident Score: Analysis & Impact (ANT1774964235)
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Rankiteo Score Impact Analysis
Key Highlights From The Incident Analysis
- Timeline of Anthropic's Breach 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 Anthropic 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 Anthropic breach identified under incident ID ANT1774964235.
The analysis begins with a detailed overview of Anthropic's information like the linkedin page: https://www.linkedin.com/company/anthropicresearch, the number of followers: 1898947, the industry type: Research Services and the number of employees: 3717 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 443 and after the incident was 385 with a difference of -58 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 Anthropic and their customers.
On 31 March 2026, Anthropic disclosed Source Code Leak issues under the banner "Anthropic’s Claude Code Source Leak Exposes Proprietary AI Tool Internals Again".
Security researcher Chaofan Shou discovered that Anthropic’s flagship AI coding tool, Claude Code, had its entire source code exposed through a misconfigured source-map file (cli.js.map) included in its npm package.
The disruption is felt across the environment, affecting Claude Code (npm package version 2.1.88), and exposing 1,906 proprietary files (internal APIs, telemetry systems, encryption tools, inter-process communication protocols), with nearly 1,906 files records at risk.
Formal response steps have not been shared publicly yet.
The case underscores how teams are taking away lessons such as Persistent risks in AI tooling distribution and software release practices, particularly for enterprise-grade developer tools.
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 moderate to high confidence (80%), supported by evidence indicating misconfigured source-map file (cli.js.map) included in its npm package. Under the Exfiltration tactic, the analysis identified Transfer Data to Cloud Account (T1537) with high confidence (90%), supported by evidence indicating leaked code was archived on GitHub (1,100+ stars, 1,900+ forks). Under the Collection tactic, the analysis identified Data from Information Repositories (T1213) with moderate to high confidence (80%), supported by evidence indicating 1,906 proprietary files (internal APIs, telemetry systems, encryption tools). Under the Defense Evasion tactic, the analysis identified Code Signing: Code Signing Policy Modification (T1553.006) with moderate confidence (60%), supported by evidence indicating source map referencing unobfuscated TypeScript files hosted in cloud storage. Under the Impact tactic, the analysis identified Defacement: Internal Defacement (T1491.001) with moderate to high confidence (70%), supported by evidence indicating exposed proprietary AI tool internals (internal architecture, security mechanisms). These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.
Sources & References
- Anthropic Rankiteo Cyber Incident Details: https://www.rankiteo.com/company/anthropicresearch/incident/ANT1774964235
- Anthropic CyberSecurity Rating page: https://www.rankiteo.com/company/anthropicresearch
- Anthropic Rankiteo Cyber Incident Blog Article: https://blog.rankiteo.com/ant1774964235-anthropic-breach-march-2026/
- Anthropic CyberSecurity Score History: https://www.rankiteo.com/company/anthropicresearch/history
- Anthropic CyberSecurity Incident Source: https://www.ndtv.com/science/anthropics-ai-coding-tool-leaks-its-own-source-code-for-the-second-time-in-a-year-11291517
- 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