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SGLang AI inference server hit with critical CVE-2026-5760 vulnerability

By PulseAugur Editorial · [1 sources] ·

A critical security vulnerability (CVE-2026-5760) with a severity score of 9.8 has been identified in SGLang, an AI inference server. The issue arises from a poisoned GGUF model file containing a chat-template that SGLang processes via an unsandboxed Jinja2, allowing arbitrary Python code execution on the host system. This vulnerability is similar to past issues found in llama-cpp-python and vLLM, highlighting a persistent oversight in handling model file templates across multiple AI frameworks. AI

IMPACT Critical vulnerability in SGLang allows arbitrary code execution, impacting the security of AI model deployments.

RANK_REASON Security advisory for an open-source AI inference server with a critical severity score.

Read on Mastodon — fosstodon.org →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

SGLang AI inference server hit with critical CVE-2026-5760 vulnerability

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Security advisory for an open-source AI inference server with a critical severity score.
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safety, infra
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150 days old
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COVERAGE [1]

  1. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    CERT/CC issued advisory VU#915947 for SGLang (an AI inference server), CVE-2026-5760, severity 9.8. A poisoned GGUF model file carries a chat-template that SGLa

    CERT/CC issued advisory VU#915947 for SGLang (an AI inference server), CVE-2026-5760, severity 9.8. A poisoned GGUF model file carries a chat-template that SGLang renders through Jinja2 with no sandbox. Arbitrary Python runs on the host. Same root cause as llama-cpp-python (2024)…

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