Malicious GGUF Models Could Trigger Remote Code Execution on SGLang Servers

Gbhackers •Divya • April 21, 2026

Security researchers have uncovered a critical vulnerability in SGLang, a widely used framework for running large language models, that allows threat actors to compromise inference servers. Tracked as CVE-2026-5760, this flaw enables Remote Code Execution (RCE) when a server loads a maliciously crafted GGUF model file. By simply hosting a weaponized model on platforms like […]

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Critical RCE Vulnerability Discovered in SGLang Framework via GGUF Models A remote code execution vulnerability has been identified in the SGLang framework, specifically affecting the reranking endpoint (/v1/rerank) and tracked as CVE-2026-5760. This flaw allows attackers to exploit maliciously crafted GGUF model files containing Jinja2 templates, leading to the execution of arbitrary Python code on the server. The vulnerability arises from the unsandboxed use of jinja2.Environment() in the rendering process of chat templates. Successful exploitation could result in host compromise, lateral movement, data exfiltration, or denial-of-service attacks. The issue affects deployments of SGLang that expose the vulnerable interface to untrusted networks. Despite attempts to coordinate with project maintainers, no response or patch has been issued. The severity of this vulnerability is underscored by its potential impact on enterprise AI deployments. Security researchers recommend using ImmutableSandboxedEnvironment to mitigate the risk of exploitation. 7 sources 70

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Malicious GGUF Models Could Trigger Remote Code Execution on SGLang Servers

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