Security vulnerabilities, privacy incidents, safety concerns, and policy updates affecting LLMs and AI agents.
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).
CVE-2026-47476 is a vulnerability in NVIDIA Triton Inference Server for Linux that allows attackers to cause uncontrolled resource consumption (using up computing resources like memory or CPU without limit), potentially leading to denial of service (making the system unavailable to legitimate users). The vulnerability is classified as CWE-400 (uncontrolled resource consumption), though a CVSS severity score has not yet been assigned by NIST.
NVIDIA Triton Inference Server for Linux has a use-after-free vulnerability (a bug where software tries to access memory that has already been freed, potentially causing crashes). An attacker could exploit this to cause a denial of service (making the service unavailable to legitimate users), though the severity rating from NIST has not yet been provided.
CVE-2026-24264 is a vulnerability in NVIDIA Triton Inference Server for Linux where an attacker can exploit improper handling of highly compressed data (data that has been reduced in size), potentially causing a denial of service (making a system unavailable to users). The vulnerability has a CVSS score of 4.0, which indicates a moderate severity rating.
vLLM (a system for running large language models) versions 0.10.2 through 0.12.x lack proper validation of sparse tensors (data structures with mostly empty values) when processing multimodal embeddings (numerical representations combining text and images). An attacker can send malicious embedding requests with invalid tensor indices to crash the system, exhaust resources, or potentially corrupt memory if the prompt-embeds feature is enabled.
NVIDIA Transformers4Rec for Linux has a vulnerability where attackers can exploit improper deserialization (unsafe processing of data that was converted into a storable format) of untrusted data, potentially leading to code execution (running commands on the system), data tampering, and information disclosure. The vulnerability is tracked as CVE-2026-24162 and a CVSS score (a 0-10 rating of how severe a vulnerability is) has not yet been assigned by NIST.
NVIDIA Triton Inference Server has a vulnerability in its DALI backend (a component that processes data) that allows attackers to cause uncontrolled resource consumption, potentially leading to a denial of service attack (making the service unavailable to legitimate users).
NVIDIA Triton Inference Server has a vulnerability in its DALI backend (a component that processes data) where an attacker could trigger an integer overflow (a bug where a number exceeds the maximum value a system can store). This could allow an attacker to execute malicious code, modify data, or crash the service.
NVIDIA Triton Inference Server contains a vulnerability in the DALI backend (a component that processes data) where an attacker could perform an out-of-bounds read (accessing memory locations outside the intended range). Exploiting this could allow code execution (running malicious commands), data tampering (changing information), denial of service (making the system unavailable), or information disclosure (leaking sensitive data).
NVIDIA Triton Inference Server has a vulnerability where an attacker could cause an integer overflow (a situation where a number exceeds the maximum value a program can store, causing unexpected behavior), potentially leading to denial of service (making a system unavailable to users). The vulnerability has a CVSS 4.0 severity rating (a 0-10 scale measuring how serious a security flaw is).
CVE-2026-24209 is a path traversal vulnerability (a flaw where an attacker manipulates file paths to access files outside their intended directory) in NVIDIA Triton Inference Server that could allow an attacker to cause a denial of service (making a system unavailable to users). The vulnerability has a CVSS 4.0 severity rating, though a full assessment from NIST has not yet been provided.