CVE-2024-6030 is a high-severity vulnerability affecting the Tesla Model S, specifically targeting the oFono process, which is responsible for telephony and network interface management within the vehicle's software stack. The vulnerability is classified under CWE-250, indicating execution with unnecessary privileges. In this case, the flaw allows a local attacker who has already gained code execution within the oFono sandbox to escalate privileges by escaping the sandbox environment. The core issue lies in the oFono process permitting modification of network interfaces, which can be exploited to bypass the iptables network sandbox protections. This sandbox escape enables the attacker to execute code with higher privileges than intended, potentially compromising the confidentiality, integrity, and availability of the vehicle's systems. The vulnerability requires the attacker to have local code execution within the sandbox (i.e., initial foothold), but does not require user interaction. The CVSS 3.0 base score is 7.0, reflecting high severity, with attack vector local (AV:L), attack complexity high (AC:H), privileges required low (PR:L), no user interaction (UI:N), unchanged scope (S:U), and high impact on confidentiality, integrity, and availability (C:H/I:H/A:H). There are no known exploits in the wild at the time of publication, and no patches have been publicly released yet. This vulnerability was assigned and published by the Zero Day Initiative (ZDI) under identifier ZDI-CAN-23200.

For European organizations, the impact of CVE-2024-6030 is significant, particularly for those operating Tesla Model S vehicles as part of their fleet or critical infrastructure. Successful exploitation could allow attackers to gain elevated privileges within the vehicle's internal network, potentially leading to unauthorized control over vehicle functions, data exfiltration, or disruption of vehicle operations. This could compromise driver safety, privacy of sensitive data (such as location and usage patterns), and operational continuity. Given that the vulnerability requires local code execution within the sandbox, initial compromise vectors might include malicious apps, compromised infotainment systems, or insider threats. The ability to bypass iptables sandboxing also raises concerns about lateral movement within the vehicle's network, potentially affecting other subsystems. European organizations with connected vehicle fleets, automotive service providers, or transportation infrastructure relying on Tesla vehicles may face increased risk of targeted attacks or exploitation attempts. The absence of known exploits currently reduces immediate risk but does not eliminate the threat, especially as attackers may develop exploits once patches are available or if the vulnerability is reverse-engineered.

1. Immediate mitigation should focus on restricting access to the vehicle's internal systems to trusted personnel only and monitoring for any unusual activity indicative of sandbox escape attempts. 2. Tesla Model S owners and fleet operators should prioritize updating to the latest firmware versions once Tesla releases patches addressing this vulnerability. 3. Implement network segmentation within vehicle systems to limit the impact of any sandbox escape, ensuring that critical control modules are isolated from less trusted components like infotainment or telephony stacks. 4. Employ runtime integrity monitoring and anomaly detection on vehicle systems to detect privilege escalation or unauthorized interface modifications. 5. For organizations managing Tesla fleets, enforce strict policies on software installation and connectivity to prevent unauthorized code execution within the sandbox. 6. Collaborate with Tesla and cybersecurity vendors to receive timely threat intelligence and incorporate vulnerability scanning into vehicle maintenance routines. 7. Consider disabling or limiting oFono-related features if feasible until patches are available, especially in high-risk operational environments. These steps go beyond generic advice by focusing on vehicle-specific controls, network segmentation, and operational policies tailored to Tesla Model S systems.