CVE-2024-0095 in Triton Inference Server
Summary
by MITRE • 06/14/2024
NVIDIA Triton Inference Server for Linux and Windows contains a vulnerability where a user can inject forged logs and executable commands by injecting arbitrary data as a new log entry. A successful exploit of this vulnerability might lead to code execution, denial of service, escalation of privileges, information disclosure, and data tampering.
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Analysis
by VulDB Data Team • 09/27/2025
The vulnerability identified as CVE-2024-0095 affects NVIDIA Triton Inference Server across both Linux and Windows operating systems, representing a critical security flaw that stems from improper input validation within the logging mechanism. This issue allows authenticated users to manipulate the logging system by injecting arbitrary data as new log entries, effectively bypassing normal security controls that should prevent unauthorized command execution or data manipulation. The vulnerability resides in the server's handling of log data, where insufficient sanitization enables attackers to craft malicious log entries that can be interpreted as executable commands or forged log information.
The technical exploitation of this vulnerability falls under CWE-20, which describes improper input validation, and can be mapped to ATT&CK technique T1059.001 for command and scripting interpreter. When a user successfully injects malicious data into the logging system, the server processes this data without adequate validation, potentially executing injected commands or interpreting forged log entries as legitimate operations. This flaw creates a pathway for attackers to escalate privileges by manipulating system logs that may be processed by other components or services within the inference server environment. The impact extends beyond simple command execution to include denial of service scenarios where malicious log entries can cause system instability or resource exhaustion.
The operational consequences of this vulnerability are severe and multifaceted, affecting the integrity and availability of the inference server infrastructure. Attackers could leverage this vulnerability to gain unauthorized access to system resources, manipulate critical log data for stealthy persistence, or disrupt normal server operations through denial of service attacks. The information disclosure aspect of this vulnerability means that sensitive operational data could be exposed through manipulated log entries, while data tampering capabilities allow attackers to corrupt system logs and potentially hide their malicious activities. This vulnerability particularly impacts environments where the Triton Inference Server handles sensitive AI model inference workloads, as it could enable attackers to compromise the entire machine learning pipeline.
Mitigation strategies for CVE-2024-0095 should focus on implementing robust input validation and sanitization measures within the logging subsystem. Organizations should apply the latest security patches provided by NVIDIA as soon as they become available, while also implementing proper access controls to limit who can submit log entries to the system. Network segmentation and monitoring of log entry submissions can help detect anomalous behavior that might indicate exploitation attempts. The implementation of automated log integrity checking mechanisms and regular audit procedures can help identify tampered log entries. Additionally, organizations should consider implementing principle of least privilege for user accounts with logging permissions and establish comprehensive monitoring solutions that can detect unusual patterns in log data submissions, particularly those that might indicate command injection attempts.