Overview
The Common Vulnerabilities and Exposures (CVE) system has identified a severe security flaw, denoted as CVE-2025-54951, in the ExecuTorch Machine Learning Framework. This vulnerability stems from a group of related buffer overflow issues that arise during the loading of ExecuTorch models. If successfully exploited, these vulnerabilities could cause the runtime to crash, potentially resulting in arbitrary code execution or other undesirable effects. This issue is of significant concern to any organization or individual utilizing ExecuTorch versions prior to commit cea9b23aa8ff78aff92829a466da97461cc7930c.
Vulnerability Summary
CVE ID: CVE-2025-54951
Severity: Critical (9.8 CVSS Score)
Attack Vector: Network
Privileges Required: None
User Interaction: None
Impact: System compromise or data leakage
Affected Products
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Product | Affected Versions
ExecuTorch | Prior to commit cea9b23aa8ff78aff92829a466da97461cc7930c
How the Exploit Works
This flaw exploits buffer overflow vulnerabilities in the loading of ExecuTorch models. An attacker can craft a malicious model that, when loaded into the ExecuTorch runtime, overflows the buffer, causing a crash. This crash can then be leveraged to execute arbitrary code or trigger other undesirable effects. This does not require any user interaction or special privileges, making it a particularly dangerous vulnerability.
Conceptual Example Code
Although the specifics of the exploit could vary, a conceptual example might look something like this:
# Loading a maliciously crafted model
model = torch.load('malicious_model.pth')
# The model contains oversized tensors that cause a buffer overflow
# when loaded into the ExecuTorch runtime.Mitigation
Users are strongly recommended to apply the vendor-supplied patch by updating their ExecuTorch to a version later than commit cea9b23aa8ff78aff92829a466da97461cc7930c. As a temporary mitigation, users can also implement a Web Application Firewall (WAF) or Intrusion Detection System (IDS) to detect and block attempts to exploit this vulnerability. However, this is a temporary measure and does not substitute updating to a patched version.