I'm being cyberattacked by Tesla, Inc
Source Entity
Hacker News
A security researcher identified suspicious traffic originating from IP addresses associated with Tesla, Inc. The requests utilized Assetnote user agents and attempted SSRF attacks, raising questions about potential misconfiguration or unauthorized use of corporate infrastructure.
Analysis of Unusual Network Traffic Originating from Tesla Infrastructure
Recent logs have surfaced concerning persistent, potentially malicious network traffic originating from IP addresses linked to Tesla, Inc. The traffic, characterized by specific Host and Referer headers pointing to 'pool-ntp.tesla.com', has raised significant alarms within the cybersecurity community due to its suspicious nature and the use of specialized scanning tools.
The Mechanics of the Observed Attack
The observed traffic included specific attempts to execute Server-Side Request Forgery (SSRF) attacks against a target server. The logs reveal the use of Assetnote user agents, a platform often used for automated security reconnaissance. The payloads included complex strings designed to exploit potential vulnerabilities, such as JNDI lookups via LDAP, which are reminiscent of historical Log4j-style injection techniques. The inclusion of 'assetnote-callback.com' in the payload suggests an attempt to verify if the targeted server is vulnerable by forcing it to reach out to an external listener.
Infrastructure Misuse and Security Implications
The presence of Tesla-owned IP addresses in these logs is the most concerning aspect. Whether this represents a deliberate internal security audit that has gone awry, a compromise of Tesla's own infrastructure by a third party, or the unauthorized use of their resources, it highlights a critical failure in asset management. Large corporations often maintain vast fleets of cloud instances for NTP (Network Time Protocol) or internal testing, and these are frequently overlooked during broader security hardening processes.
The Risks of Automated Reconnaissance
Automated scanning tools like those provided by Assetnote are double-edged swords. While intended for security professionals to identify vulnerabilities in their own perimeters, they are frequently repurposed by actors to map out the attack surface of unsuspecting targets. The fact that these tools were observed using Tesla's network footprint implies that the origin of the traffic is either an internal Tesla security team conducting external testing or, more worryingly, an actor who has gained unauthorized access to Tesla's cloud environment.
Broader Implications for Corporate Cybersecurity
This incident serves as a stark reminder of the 'shadow IT' problem in large enterprises. When corporate infrastructure is used to probe external targets—even accidentally—it creates a trail of logs that can cause significant reputational and legal friction. It also underscores the necessity for strict egress filtering and monitoring of internal cloud-native applications, ensuring that automated security tools are not inadvertently performing actions that appear to be malicious from an external perspective.
Conclusion and Future Outlook
As organizations continue to scale their cloud footprints, the risk of misconfigured automated systems will only increase. This event highlights the need for better attribution and accountability for traffic originating from corporate-owned IP blocks. Moving forward, it is essential for major technology firms to implement more rigorous oversight of their automated security testing pipelines to prevent them from being mistaken for malicious actors, while also hardening their own infrastructure against being hijacked for such purposes.