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CVE-2025-54950: Critical Out-of-Bounds Access Vulnerability in ExecuTorch Models Loading

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Overview

The cybersecurity landscape has just witnessed the emergence of a critical vulnerability, CVE-2025-54950, that poses a significant threat to users of the ExecuTorch tool. This tool, widely used in data science and artificial intelligence communities, has a flaw that could potentially lead to system compromise or data leakage, translating into considerable damage. The vulnerability affects ExecuTorch versions prior to commit b6b7a16df5e7852d976d8c34c8a7e9a1b6f7d005 and can have severe repercussions if exploited by malicious entities.

Vulnerability Summary

CVE ID: CVE-2025-54950
Severity: Critical (CVSS Score: 9.8)
Attack Vector: Remote
Privileges Required: None
User Interaction: None
Impact: Potential system compromise, data leakage

Affected Products

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Product | Affected Versions

ExecuTorch | Prior to commit b6b7a16df5e7852d976d8c34c8a7e9a1b6f7d005

How the Exploit Works

The vulnerability resides in the code responsible for loading ExecuTorch models. An out-of-bounds access vulnerability allows an attacker to cause the runtime to crash and potentially execute malicious code. This could be achieved by feeding an oversized or maliciously crafted model to ExecuTorch, forcing the software to access memory locations that it should not, causing the crash and potentially opening the door for further exploitation.

Conceptual Example Code

While the specific exploitation code would depend on the attacker’s intent and the system’s specifics, the general idea is to provide a maliciously crafted model to the vulnerable version of ExecuTorch. Here is a simplified example of how this might look:

import executorch
# Create a maliciously crafted model
malicious_model = executorch.Model()
malicious_model.load_data('malicious_data')
# Load the malicious model into a vulnerable ExecuTorch instance
vulnerable_executorch = executorch.Engine()
vulnerable_executorch.load_model(malicious_model)

In this conceptual example, ‘malicious_data’ would be crafted in a way that triggers the out-of-bounds access, causing the runtime to crash and potentially allowing the attacker to execute their code. This example code is for illustrative purposes only and does not represent a real exploit.

Mitigation

The recommended mitigation strategy is to apply the vendor-provided patch immediately. Users unable to do so can temporarily mitigate the vulnerability using a Web Application Firewall (WAF) or Intrusion Detection System (IDS) to block or alert on suspicious activity related to ExecuTorch model loading. However, these are temporary measures and cannot substitute the need for the patch.

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Disclaimer:

The information and code presented in this article are provided for educational and defensive cybersecurity purposes only. Any conceptual or pseudocode examples are simplified representations intended to raise awareness and promote secure development and system configuration practices.

Do not use this information to attempt unauthorized access or exploit vulnerabilities on systems that you do not own or have explicit permission to test.

Ameeba and its authors do not endorse or condone malicious behavior and are not responsible for misuse of the content. Always follow ethical hacking guidelines, responsible disclosure practices, and local laws.
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