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Analyze » Kimi (Moonshot AI) » DEEKIM1790217824

Incident Score: Analysis & Impact (DEEKIM1790217824)

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

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-58
Company Score Before Incident739 / 1000
Company Score After Incident681 / 1000
INCIDENT NUMBERDEEKIM1790217824
Type of Cyber IncidentBreach
ATTACK VECTORUnauthorized API routing / Data exfiltration
DATA EXPOSEDSensitive user data, potentially including...
INCIDENT DATE09/09/2026
STATUSOngoing

Key Highlights From The Incident Analysis

  • Timeline of Kimi (Moonshot AI)'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 Kimi (Moonshot AI) 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 Kimi (Moonshot AI) breach identified under incident ID DEEKIM1790217824.

The analysis begins with a detailed overview of Kimi (Moonshot AI)'s information like the linkedin page: https://www.linkedin.com/company/kimi-ai-linkedin, the number of followers: 12848, the industry type: Technology, Information and Internet and the number of employees: 164 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 739 and after the incident was 681 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 Kimi (Moonshot AI) and their customers.

On 10 September 2024, DeepSeek disclosed Data Leak / Unauthorized Data Transfer issues under the banner "China Launches Probe into DeepSeek and Moonshot AI Over Alleged Data Leaks to Anthropic".

China’s Cyberspace Administration (CAC) has opened an investigation into two prominent AI startups DeepSeek and Moonshot AI over allegations that they secretly routed sensitive user data to Anthropic’s servers.

The disruption is felt across the environment, affecting Anthropic’s servers (indirectly), DeepSeek and Moonshot AI’s infrastructure, and exposing Sensitive user data, potentially including police, military, or state-linked corporate data.

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 Trusted Relationship (T1199) with moderate to high confidence (80%), supported by evidence indicating rerouted queries to its servers, effectively providing users with Claude’s responses. Under the Collection tactic, the analysis identified Data from Information Repositories (T1213) with high confidence (90%), supported by evidence indicating illicit distillation training smaller AI models using outputs from Anthropic’s Claude and Data from Local System (T1005) with moderate to high confidence (70%), supported by evidence indicating sensitive user data, potentially including police, military, or state-linked corporate data. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with high confidence (90%), supported by evidence indicating secretly routed sensitive user data to Anthropic’s servers and Transfer Data to Cloud Account (T1537) with moderate to high confidence (80%), supported by evidence indicating data was transferred to U.S.-based servers. Under the Credential Access tactic, the analysis identified Steal Application Access Token (T1528) with moderate confidence (60%), supported by evidence indicating unauthorized API routing / Data exfiltration. Under the Defense Evasion tactic, the analysis identified Masquerading (T1036) with moderate to high confidence (70%), supported by evidence indicating illicit distillation training smaller AI models using outputs from Claude and Hide Artifacts: Email Hiding Rules (T1564.008) with moderate confidence (50%), supported by evidence indicating no penalties have been announced, underscores scrutiny of AI development. Under the Impact tactic, the analysis identified Defacement (T1491) with lower confidence (40%), supported by evidence indicating brand reputation impact such as High (for DeepSeek and Moonshot AI) and Service Stop (T1489) with lower confidence (30%), supported by evidence indicating potential IPO delays for Moonshot AI. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.

Initial Access
Trusted Relationship (80%)
Collection
Data from Information Repositories (90%)
Data from Local System (70%)
Exfiltration
Exfiltration Over C2 Channel (90%)
Transfer Data to Cloud Account (80%)
Credential Access
Steal Application Access Token (60%)
Defense Evasion
Masquerading (70%)
Hide Artifacts: Email Hiding Rules (50%)
Impact
Defacement (40%)
Service Stop (30%)

Sources & References