Inference infrastructure

NVIDIA Triton Inference Server contains a vulnerability, CVE-2026-24175, classified as CWE-248 (Uncaught Exception). An attacker can crash the server by sending a malformed request header, which may lead to denial of service. NVD published the entry on 04/07/2026 and has not yet provided its own assessment.

CVE-2026-24174 affects NVIDIA Triton Inference Server. An attacker can crash the server by sending a malformed request, which might lead to denial of service. The weakness is classified as CWE-681, Incorrect Conversion between Numeric Types, and NVD has not yet provided an assessment.

NVIDIA Triton Inference Server contains a vulnerability, tracked as CVE-2026-24173, where an attacker can cause a server crash by sending a malformed request. The source states that a successful exploit might lead to denial of service. The weakness is classified as CWE-190, Integer Overflow or Wraparound, and NVD published the entry on 04/07/2026.

CVE-2026-24146 affects NVIDIA Triton Inference Server. Insufficient input validation combined with a large number of outputs can crash the server, which a successful exploit may use to cause denial of service. The source tags the weakness as CWE-789, Memory Allocation with Excessive Size Value.

CVE-2026-27893 affects vLLM, an inference and serving engine for large language models, from version 0.10.1 before 0.18.0. Two model implementation files hardcode `trust_remote_code=True` when loading sub-components, overriding a user's explicit `--trust-remote-code=False` opt-out. This enables remote code execution through malicious model repositories even when remote code trust is disabled.

CVE-2026-24158 affects the HTTP endpoint of NVIDIA Triton Inference Server. An attacker can cause a denial of service by sending a large compressed payload, and a successful exploit may lead to denial of service. The weakness is classified as CWE-789, Memory Allocation with Excessive Size Value.

NVIDIA Triton Inference Server contains a vulnerability, CVE-2025-33254, where an attacker may cause internal state corruption. A successful exploit may lead to a denial of service. The weakness is classified as CWE-362, Concurrent Execution using Shared Resource with Improper Synchronization ('Race Condition').

NVIDIA Triton Inference Server's Sagemaker HTTP server contains a vulnerability, tracked as CVE-2025-33238, that lets an attacker cause an exception. A successful exploit may lead to denial of service. The weakness is classified as CWE-362, a race condition from concurrent execution using a shared resource with improper synchronization. NVD has not yet provided an assessment.

CVE-2026-0599 affects huggingface/text-generation-inference version 3.3.6. Unauthenticated remote attackers can trigger unbounded external image fetching during input validation in VLM mode, because the router performs a blocking HTTP GET on Markdown image links and reads the entire response into memory. This can exhaust network bandwidth, memory and CPU, and the default deployment, which lacks memory limits and authentication, could crash the host machine.

CVE-2026-24779 affects vLLM versions prior to 0.14.1. The `MediaConnector` class in its multimodal feature set has an SSRF flaw in the `load_from_url` and `load_from_url_async` methods, where two Python parsing libraries interpret backslashes differently, letting an attacker bypass the host name restriction. A successful attacker can make the vLLM server send arbitrary requests to internal network resources, which is especially serious in containerized deployments such as `llm-d`.

CVE-2025-15063 is a command injection flaw in the execAsync method of the Ollama MCP Server. It stems from the lack of proper validation of a user-supplied string before the string is used in a system call. Remote attackers can exploit it without authentication to execute code in the context of the service account.