Security vulnerabilities, privacy incidents, safety concerns, and policy updates affecting LLMs and AI agents.
NVIDIA Triton Inference Server for Linux has a security flaw where missing authorization checks allow attackers to access or modify data and disrupt service. An attacker could exploit this to steal information, change data, or make the system unavailable.
NVIDIA Triton Inference Server for Linux has a security flaw (CVE-2026-16497) where an attacker can trick the system into repeating operations excessively, potentially causing a denial of service (a situation where a service becomes unavailable to legitimate users).
ONNX (a machine learning model format) versions before 1.21.0 have a vulnerability in the 'save_external_data' function where it unsafely opens files for writing without proper protections. A local attacker with write access to the same directory can create a symlink (a shortcut to another file) that tricks the function into writing to sensitive files like SSH authorization keys or system configuration files instead of the intended target.
NVIDIA Triton Inference Server for Linux contains a vulnerability that allows an attacker to perform absolute path traversal (accessing files outside intended directories by using full file paths), potentially leading to code execution. The vulnerability has a CVSS score (a 0-10 rating of how severe a vulnerability is) of 4.0. As of the publication date, no detailed information or patch has been provided in this source.
CVE-2026-47629 is a vulnerability in NVIDIA Triton Inference Server for Linux that involves improper input validation (the failure to check that data entering a system is safe and correctly formatted), which could allow an attacker to cause a denial of service (making the service unavailable to legitimate users). The vulnerability has a CVSS 4.0 severity rating, though a detailed assessment is not yet available.
NVIDIA Triton Inference Server for Linux contains a vulnerability (CVE-2026-47628) that allows an attacker to allocate unlimited resources, potentially causing a denial of service (a situation where a system becomes unavailable to legitimate users). The vulnerability is classified as CWE-770, which refers to allocation of resources without limits or throttling (controls that prevent excessive resource use).
NVIDIA Triton Inference Server for Linux has a path traversal vulnerability (CVE-2026-47627), which is a flaw where an attacker can access files outside of intended directories by manipulating file paths. A successful attack could cause denial of service (making the service unavailable to legitimate users).
CVE-2026-47606 is a vulnerability in NVIDIA Triton Inference Server for Linux that allows an attacker to perform absolute path traversal (accessing files outside their intended directory by using path tricks like "../"). If successfully exploited, this vulnerability could allow an attacker to run code on the system or access sensitive information.
A security flaw in vLLM Hardware Plugin for Intel Gaudi software versions before 0.16.0 fails to properly validate user input (check that data is safe before using it), which could allow an authorized user to crash the system through a denial of service attack (making a service unavailable). The flaw affects system availability but not the security of stored data or system integrity.
A protection mechanism failure in Intel Extension for TensorFlow (a library that adds TensorFlow AI capabilities to Intel systems) before version 2.15.0.3 could allow someone with basic system access to gain higher-level privileges, potentially compromising the confidentiality, integrity, and availability of the system. The attack requires local access and low complexity, with passive user interaction.
NVIDIA Triton Inference Server for Linux has a vulnerability where an attacker could read, write, or modify files outside the intended model repository by providing a specially crafted path in the model name to the MLflow plugin. This could lead to denial of service (making a system unavailable) and information disclosure (leaking sensitive data).
NVIDIA TensorRT-LLM (a tool for running large language models efficiently) contains a vulnerability in its OpenAI-compatible API where an attacker could trigger a reachable assertion (a failed safety check in the code) in the sampler thread, potentially causing the system to crash. This vulnerability could lead to a denial of service attack (making the service unavailable to legitimate users).
NVIDIA TensorRT-LLM (a tool for running large language models efficiently on NVIDIA GPUs) has a vulnerability in its OpenAI-compatible inference API that allows attackers to request unlimited GPU resources without restrictions. This could cause a denial of service (making the system unavailable to legitimate users) by exhausting the GPU's memory and processing power.
NVIDIA TensorRT-LLM for Linux has a vulnerability in its unpickler (a tool that converts serialized data back into usable objects) that allows local attackers to deserialize untrusted data. A successful attack could lead to code execution, privilege escalation, data tampering, and information disclosure.
CVE-2026-47482 is a memory leak vulnerability (a bug where a program fails to free up memory it's no longer using) in NVIDIA Triton Inference Server for Linux that allows attackers to cause a denial of service (making a service unavailable to legitimate users). The vulnerability stems from the software not properly releasing memory after it's finished using it.
CVE-2026-47481 is a vulnerability in NVIDIA Triton Inference Server for Linux that allows attackers to bypass authentication (security checks that verify a user's identity) through an alternative path or channel. If successfully exploited, this flaw could let attackers run their own code on the system, gain higher-level access, steal information, or modify data.
CVE-2026-47480 is a vulnerability in NVIDIA Triton Inference Server for Linux that allows an attacker to trigger an uncaught exception (an error that the program doesn't handle properly), potentially causing a denial of service (making the service unavailable to legitimate users). The vulnerability has a CVSS 4.0 severity rating, though a detailed assessment has not yet been provided.
CVE-2026-47479 is a vulnerability in NVIDIA Triton Inference Server for Linux that allows an attacker to cause uncontrolled resource consumption (using up all available computing power or memory), potentially leading to a denial of service (making the service unavailable to legitimate users). The vulnerability has a CVSS 4.0 severity rating, though a complete assessment from NIST has not yet been provided.
CVE-2026-47478 is a vulnerability in NVIDIA Triton Inference Server for Linux where an attacker can exploit the use of an expired file descriptor (a reference to an open file that is no longer valid), potentially causing a denial of service (making the service unavailable to legitimate users). The vulnerability has a CVSS 4.0 severity rating, though the exact scoring details have not yet been provided.
CVE-2026-47477 is a vulnerability in NVIDIA Triton Inference Server for Linux that allows an attacker to cause a stack-based buffer overflow (a situation where data written to memory exceeds its allocated space, potentially crashing the system). A successful attack could result in denial of service (making the service unavailable to legitimate users).
Fix: Fixed in version 1.21.0. Users should upgrade ONNX to version 1.21.0 or later.
NVD/CVE DatabaseFix: Update to vLLM Hardware Plugin for Intel Gaudi software version 0.16.0 or later.
NVD/CVE DatabaseFix: Update Intel Extension for TensorFlow to version 2.15.0.3 or later.
NVD/CVE Database