CVE-2025-23247: Nvidia Cuda Toolkit RCE Vulnerability

CVE-2025-23247 Overview

CVE-2025-23247 is a buffer length check vulnerability in the NVIDIA CUDA Toolkit's cuobjdump binary that affects all supported platforms. The vulnerability arises from a failure to properly check the length of a buffer when processing ELF files, which could allow an attacker to crash the tool or achieve arbitrary code execution by supplying a specially crafted malformed ELF file.

Critical Impact

Successful exploitation of this vulnerability could lead to arbitrary code execution on systems running affected versions of the NVIDIA CUDA Toolkit, potentially compromising development environments and GPU-accelerated computing infrastructure.

Affected Products

• NVIDIA CUDA Toolkit (all versions prior to patch)
• Linux Kernel-based systems running CUDA Toolkit
• Microsoft Windows systems running CUDA Toolkit

Discovery Timeline

• May 27, 2025 - CVE-2025-23247 published to NVD
• October 3, 2025 - Last updated in NVD database

Technical Details for CVE-2025-23247

Vulnerability Analysis

This vulnerability is classified under CWE-130 (Improper Handling of Length Parameter Inconsistency), which occurs when software fails to properly handle inconsistencies between length parameters and actual buffer sizes. In the context of cuobjdump, the binary utility is designed to examine CUDA binary files and extract information about GPU code sections.

When cuobjdump processes an ELF (Executable and Linkable Format) file, it reads various headers and data sections. The vulnerability exists because the tool does not adequately validate that buffer lengths specified in the ELF file structure match the actual allocated buffer sizes before performing memory operations. This creates a condition where carefully manipulated length values in a malformed ELF file can cause the program to read or write beyond intended memory boundaries.

The local attack vector requires user interaction—an attacker must convince a victim to process the malicious ELF file with cuobjdump. In development environments where developers routinely analyze binary files, this could be achieved through supply chain attacks, malicious code repositories, or social engineering.

Root Cause

The root cause of CVE-2025-23247 stems from insufficient input validation in the cuobjdump binary's ELF file parsing routines. Specifically, the code fails to verify that length parameters embedded within the ELF file structure are consistent with actual buffer allocations before using these values in memory operations. This type of length parameter handling error can lead to buffer over-reads or over-writes when processing maliciously crafted files.

Attack Vector

The attack requires local access and user interaction to exploit. An attacker would need to:

1. Create a malformed ELF file with manipulated length parameters designed to trigger the buffer handling flaw
2. Deliver this file to a target system (via email, file sharing, malicious repository, etc.)
3. Convince the victim to analyze the malicious file using cuobjdump

Upon successful exploitation, the attacker could cause the application to crash (denial of service) or potentially achieve arbitrary code execution with the privileges of the user running the tool. Given that CUDA development often occurs on systems with elevated permissions or access to sensitive resources, successful code execution could have significant security implications.

The vulnerability affects systems across all platforms where NVIDIA CUDA Toolkit is deployed, including Linux and Windows development environments. For detailed technical analysis, refer to the Talos Intelligence Vulnerability Report.

Detection Methods for CVE-2025-23247

Indicators of Compromise

• Unexpected crashes of the cuobjdump binary when processing ELF files
• Abnormal memory access patterns or segmentation faults in CUDA Toolkit utilities
• Presence of suspicious or malformed ELF files with inconsistent section headers
• Unusual child processes spawned from cuobjdump execution

Detection Strategies

• Monitor for crashes and exceptions in cuobjdump processes using application crash monitoring tools
• Implement file integrity monitoring for ELF files being processed in development environments
• Deploy endpoint detection rules to identify suspicious command-line invocations of CUDA Toolkit utilities
• Use static analysis tools to scan incoming binary files for malformed ELF structures before processing

Monitoring Recommendations

• Enable verbose logging for CUDA Toolkit utility invocations in development environments
• Implement process monitoring for cuobjdump to detect abnormal termination or behavior
• Configure alerts for unusual file access patterns involving ELF files in CUDA development directories
• Review audit logs for unexpected binary file downloads or transfers to development systems

How to Mitigate CVE-2025-23247

Immediate Actions Required

• Update NVIDIA CUDA Toolkit to the latest patched version immediately
• Restrict execution of cuobjdump to trusted files only until patching is complete
• Implement network and email filtering to block suspicious ELF file attachments
• Educate development teams about the risks of analyzing untrusted binary files

Patch Information

NVIDIA has released a security update to address this vulnerability. Administrators should consult the NVIDIA Support Article for specific patch information and updated CUDA Toolkit versions. The patch implements proper length validation for buffer operations when parsing ELF file structures in the cuobjdump binary.

Workarounds

• Avoid using cuobjdump to analyze ELF files from untrusted or unknown sources
• Implement application whitelisting to prevent unauthorized ELF file processing
• Use sandboxed or isolated environments when analyzing potentially malicious binary files
• Consider using alternative binary analysis tools for untrusted files until patching is complete

# Verify CUDA Toolkit version to check if patched
nvcc --version

# Restrict cuobjdump execution to specific directories (Linux example)
chmod 750 /usr/local/cuda/bin/cuobjdump
chown root:cuda-developers /usr/local/cuda/bin/cuobjdump