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Analyze » DeepSeek AI » DEE1774745353

Incident Score: Analysis & Impact (DEE1774745353)

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 Incident677 / 1000
Company Score After Incident658 / 1000
Company LinkView DeepSeek AI Profile
INCIDENT NUMBERDEE1774745353
Type of Cyber IncidentCyber Attack
ATTACK VECTORNA
DATA EXPOSEDNA
INCIDENT DATE27/01/2025
STATUSOngoing

Key Highlights From The Incident Analysis

  • Timeline of DeepSeek AI'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 DeepSeek 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 DeepSeek AI breach identified under incident ID DEE1774745353.

The analysis begins with a detailed overview of DeepSeek AI's information like the linkedin page: https://www.linkedin.com/company/deepseek-ai, the number of followers: 184520, the industry type: Technology, Information and Internet and the number of employees: 154 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 677 and after the incident was 658 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 DeepSeek AI and their customers.

On 21 October 2024, DeepSeek disclosed Cyberattack issues under the banner "DeepSeek R1 AI Model Service Disruption Due to Large-Scale Malicious Attacks".

DeepSeek announced temporary registration limits due to large-scale malicious attacks on its services following the release of its R1 reasoning model, which gained significant popularity and adoption.

The disruption is felt across the environment, affecting DeepSeek AI services (registration system).

In response, moved swiftly to contain the threat with measures like Temporary registration limits, and stakeholders are being briefed through Public announcement of temporary registration limits.

The case underscores how Ongoing, with advisories going out to stakeholders covering Existing users remain unaffected; new registrations temporarily limited.

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 Exploit Public-Facing Application (T1190) with moderate to high confidence (70%), with evidence including large-scale malicious attacks on its services, and temporary registration limits due to attacks and Trusted Relationship (T1199) with moderate confidence (50%), supported by evidence indicating aI services gained significant popularity and adoption. Under the Impact tactic, the analysis identified Endpoint Denial of Service (T1499) with moderate to high confidence (80%), supported by evidence indicating temporary registration limits imposed due to large-scale attacks and Defacement (T1491) with lower confidence (30%), supported by evidence indicating service disruption announced publicly. Under the Defense Evasion tactic, the analysis identified Network Denial of Service (T1498) with moderate confidence (60%), supported by evidence indicating large-scale malicious attacks on its services. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.

Initial Access
Exploit Public-Facing Application (70%)
Trusted Relationship (50%)
Impact
Endpoint Denial of Service (80%)
Defacement (30%)
Defense Evasion
Network Denial of Service (60%)

Sources & References