CVE-2024-0110: Nvidia CUDA Toolkit RCE Vulnerability

CVE-2024-0110 Overview

NVIDIA CUDA Toolkit contains a critical vulnerability in the cuobjdump command-line utility where a user may cause an out-of-bounds write by passing in a malformed ELF file. A successful exploit of this vulnerability may lead to arbitrary code execution or denial of service on affected systems.

Critical Impact

This out-of-bounds write vulnerability in NVIDIA CUDA Toolkit's cuobjdump utility can be exploited through malicious ELF files to achieve code execution or cause system instability.

Affected Products

• NVIDIA CUDA Toolkit (all versions prior to patched release)
• Systems utilizing the cuobjdump utility for CUDA binary analysis
• Development environments with NVIDIA CUDA Toolkit installed

Discovery Timeline

• 2024-08-31 - CVE-2024-0110 published to NVD
• 2024-09-18 - Last updated in NVD database

Technical Details for CVE-2024-0110

Vulnerability Analysis

This vulnerability is classified as CWE-787 (Out-of-bounds Write), a memory corruption flaw that occurs when the cuobjdump utility processes specially crafted ELF files. The vulnerability requires local access and user interaction, meaning an attacker must convince a user to process a malicious ELF file using the vulnerable utility.

The attack requires the victim to explicitly invoke cuobjdump against an attacker-controlled ELF file. When the malformed file is parsed, improper boundary checking allows writing data beyond the allocated buffer, potentially corrupting adjacent memory regions. This memory corruption can be leveraged to hijack program execution flow or crash the application.

Root Cause

The root cause lies in insufficient validation of ELF file structures within the cuobjdump parsing logic. When processing ELF section headers or program headers from untrusted input, the utility fails to properly validate size and offset fields before writing data to memory buffers. This allows attackers to craft ELF files with malicious metadata that triggers writes outside intended memory boundaries.

Attack Vector

The attack vector is local and requires user interaction. An attacker must deliver a malformed ELF file to the target system and convince a user or automated process to analyze it using cuobjdump. Attack scenarios include:

• Distributing malicious CUDA binary files through untrusted repositories
• Social engineering developers to analyze attacker-supplied binaries
• Compromising build pipelines that automatically process ELF files
• Targeting research environments analyzing third-party CUDA applications

The vulnerability does not require elevated privileges to exploit, but successful exploitation can lead to code execution with the privileges of the user running cuobjdump.

Detection Methods for CVE-2024-0110

Indicators of Compromise

• Unusual crash reports or segmentation faults from cuobjdump processes
• Core dumps indicating memory corruption in CUDA Toolkit utilities
• Suspicious ELF files with malformed section headers or abnormal sizes
• Unexpected child processes spawned from cuobjdump execution

Detection Strategies

• Monitor for anomalous behavior from cuobjdump processes including unexpected crashes or resource usage
• Implement file integrity monitoring on systems where CUDA Toolkit is installed
• Deploy endpoint detection rules for memory corruption patterns in NVIDIA utilities
• Audit execution of cuobjdump against files from untrusted sources

Monitoring Recommendations

• Enable detailed logging for CUDA Toolkit utility invocations
• Configure crash reporting to capture and analyze cuobjdump failures
• Implement network monitoring for ELF file downloads to development systems
• Establish baseline behavior for CUDA development environments to detect anomalies

How to Mitigate CVE-2024-0110

Immediate Actions Required

• Update NVIDIA CUDA Toolkit to the latest patched version immediately
• Restrict cuobjdump usage to trusted ELF files only
• Implement access controls to prevent unauthorized execution of CUDA utilities
• Audit recent usage of cuobjdump to identify potential exploitation attempts
• Isolate development environments processing untrusted binaries

Patch Information

NVIDIA has released a security update addressing this vulnerability. Organizations should consult the NVIDIA Security Advisory for detailed patch information and download the latest CUDA Toolkit version from official NVIDIA channels.

Workarounds

• Avoid processing ELF files from untrusted or unknown sources with cuobjdump
• Run cuobjdump in isolated or sandboxed environments when analyzing untrusted binaries
• Implement file validation checks before processing ELF files
• Use containerization to limit the impact of potential exploitation

# Configuration example - Run cuobjdump in restricted environment
# Create isolated user for CUDA binary analysis
sudo useradd -r -s /bin/false cuda-analyzer

# Run cuobjdump with restricted permissions
sudo -u cuda-analyzer cuobjdump -elf trusted_binary.cubin

# Alternative: Use container isolation for untrusted files
docker run --rm --read-only -v /path/to/file:/input:ro nvidia/cuda cuobjdump /input/binary.cubin