CVE-2024-23496 in GGUF
Summary
by MITRE • 02/26/2024
A heap-based buffer overflow vulnerability exists in the GGUF library gguf_fread_str functionality of llama.cpp Commit 18c2e17. A specially crafted .gguf file can lead to code execution. An attacker can provide a malicious file to trigger this vulnerability.
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Analysis
by VulDB Data Team • 02/13/2025
The heap-based buffer overflow vulnerability identified as CVE-2024-23496 resides within the GGUF library implementation of llama.cpp, specifically within the gguf_fread_str functionality. This vulnerability stems from improper bounds checking during string reading operations from gguf formatted files, creating a condition where maliciously crafted input can exceed allocated memory boundaries. The issue manifests when the library attempts to read string data from a .gguf file without adequate validation of the string length against allocated buffer size, leading to memory corruption that can be exploited for arbitrary code execution.
The technical flaw operates through a classic heap overflow mechanism where the gguf_fread_str function fails to validate the length of strings being read from the gguf file format. When processing specially crafted .gguf files, the function allocates a fixed-size buffer and proceeds to copy string data without verifying that the incoming data fits within the allocated space. This vulnerability falls under CWE-121 heap-based buffer overflow, which is a well-documented class of memory safety issues that can lead to complete system compromise. The vulnerability is particularly dangerous because it allows attackers to control the program flow by overwriting adjacent memory locations, potentially leading to remote code execution.
The operational impact of this vulnerability is significant within the machine learning and artificial intelligence ecosystem, as llama.cpp is widely used for running large language models locally on consumer and enterprise systems. Attackers can exploit this vulnerability by crafting malicious .gguf files that, when processed by applications using the vulnerable library, trigger the buffer overflow condition. This creates a potential attack surface where adversaries could execute arbitrary code on systems running vulnerable applications, potentially leading to data exfiltration, system compromise, or further lateral movement within networks. The vulnerability affects systems that utilize the gguf format for model storage and loading operations, particularly those implementing the llama.cpp library for local inference tasks.
Mitigation strategies for CVE-2024-23496 should prioritize immediate patching of the affected llama.cpp library to version containing the fix for the buffer overflow condition. Organizations should implement strict input validation and sanitization measures for all gguf file processing operations, including implementing proper bounds checking and length validation before any string operations. Network segmentation and access controls should be enforced to limit exposure to potentially malicious files, while security monitoring systems should be configured to detect unusual file processing patterns that might indicate exploitation attempts. Additionally, application developers should consider implementing defensive programming practices such as using safe string handling functions and memory management techniques that prevent buffer overflow conditions. The vulnerability aligns with ATT&CK technique T1059.007 for command and script interpreter execution, as successful exploitation could enable attackers to execute arbitrary commands on affected systems.