Incident Score: Analysis & Impact (TES1772642704)
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 Tesla's Vulnerability 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 Tesla 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 Tesla breach identified under incident ID TES1772642704.
The analysis begins with a detailed overview of Tesla's information like the linkedin page: https://www.linkedin.com/company/tesla-motors, the number of followers: 12311252, the industry type: Motor Vehicle Manufacturing and the number of employees: 81067 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 796 and after the incident was 794 with a difference of -2 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 Tesla and their customers.
Tesla, Inc. recently reported "Tesla’s Remote Hacking Vulnerabilities Contradict Executive Testimony", a noteworthy cybersecurity incident.
During a Senate Commerce Committee hearing, Tesla VP Lars Moravy claimed no one has ever remotely taken control of a Tesla vehicle, contradicting documented cybersecurity incidents.
The disruption is felt across the environment, affecting Tesla vehicle fleet and Tesla Model S, and exposing Vehicle location data and System information.
In response, teams activated the incident response plan, moved swiftly to contain the threat with measures like Patching vulnerabilities in Mothership server and Patching CAN bus vulnerabilities, and began remediation that includes Expanded bug bounty programs and Participation in hacking competitions (e.g., Pwn2Own), and stakeholders are being briefed through Responsible disclosure by researchers; public acknowledgment by Tesla.
The case underscores how Closed (vulnerabilities patched), teams are taking away lessons such as Historical vulnerabilities highlight the importance of transparent security claims, especially in regulated industries like autonomous vehicles. Tesla’s security improvements post-incident demonstrate the value of bug bounty programs and responsible disclosure, and recommending next steps like Ensure executive testimony accurately reflects historical security incidents to maintain credibility with regulators and the public, Continue investing in bug bounty programs and third-party security audits and Enhance transparency around past vulnerabilities to build trust with stakeholders, with advisories going out to stakeholders covering Tesla’s security improvements post-incident were noted, but historical breaches remain relevant for regulatory discussions on autonomous vehicle security.
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 high confidence (90%), with evidence including exploitation of Tesla’s central server (Mothership), and flaws in Tesla’s Mothership server and Exploitation of Remote Services (T1210) with moderate to high confidence (80%), supported by evidence indicating remotely compromised a Tesla Model S from 12 miles away. Under the Execution tactic, the analysis identified Exploitation for Client Execution (T1203) with moderate to high confidence (80%), supported by evidence indicating remotely activated the Summon feature on a California-based Tesla and Cloud Administration Command (T1651) with moderate to high confidence (70%), supported by evidence indicating send commands to any Tesla using only a VIN number. Under the Privilege Escalation tactic, the analysis identified Exploitation for Privilege Escalation (T1068) with moderate to high confidence (70%), supported by evidence indicating gaining control of its brakes by exploiting the vehicle’s CAN bus. Under the Defense Evasion tactic, the analysis identified Impair Defenses: Disable or Modify Tools (T1562.001) with moderate confidence (60%), supported by evidence indicating tesla patched the vulnerability overnight after disclosure. Under the Collection tactic, the analysis identified Data from Local System (T1005) with moderate to high confidence (80%), supported by evidence indicating access to vehicle location data, system information. Under the Command and Control tactic, the analysis identified Application Layer Protocol: Web Protocols (T1071.001) with moderate to high confidence (70%), supported by evidence indicating mothership server manages communication with its entire fleet. Under the Impact tactic, the analysis identified Endpoint Denial of Service: Application or System Exploitation (T1499.004) with moderate to high confidence (70%), supported by evidence indicating gaining control of its brakes by exploiting the vehicle’s CAN bus and System Shutdown/Reboot (T1529) with moderate confidence (50%), supported by evidence indicating remote control of vehicle features (e.g., Summon). These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.
Sources & References
- Tesla Rankiteo Cyber Incident Details: https://www.rankiteo.com/company/tesla-motors/incident/TES1772642704
- Tesla CyberSecurity Rating page: https://www.rankiteo.com/company/tesla-motors
- Tesla Rankiteo Cyber Incident Blog Article: https://blog.rankiteo.com/tes1772642704-tesla-vulnerability-february-2026/
- Tesla CyberSecurity Score History: https://www.rankiteo.com/company/tesla-motors/history
- Tesla CyberSecurity Incident Source: https://electrek.co/2026/02/06/tesla-exec-tells-congress-no-one-has-ever-taken-control-vehicles-but-thats-not-true/
- 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