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Mallory
MediumPublic exploit

RCE via unsafe deserialization in lmsys sglang 0.4.6 /update_weights_from_tensor

IdentifiersCVE-2025-10164CWE-502· Deserialization of Untrusted Data

In lmsys sglang 0.4.6, the /update_weights_from_tensor endpoint (function main) is vulnerable to unsafe deserialization due to improper handling of the serialized_named_tensors argument. A remote attacker can supply crafted serialized data that is deserialized by the service, enabling remote exploitation. Public exploit code is reported as available.

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ANALYST BRIEF

Impact, mitigation & remediation

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Impact

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Remote code execution on the SGLang inference server via unsafe deserialization in the /update_weights_from_tensor endpoint, potentially leading to full compromise of the host running the service (including access to model-serving infrastructure and any reachable internal resources from that host).

Mitigation

If you can’t patch tonight, do this now.

Restrict network exposure of the SGLang service (do not expose /update_weights_from_tensor to untrusted networks), enforce strong authentication/authorization on administrative/model-update endpoints, and place the service behind a reverse proxy/WAF with request filtering to block unexpected serialized payloads. Run the inference service with least privilege and strong container/VM isolation to reduce blast radius if exploited.

Remediation

Patch, then assume compromise.

Upgrade/patch SGLang to a vendor-fixed release that removes or hardens deserialization in /update_weights_from_tensor (e.g., by eliminating unsafe deserialization of attacker-controlled data and enforcing strict input validation/allowlisting). If no fixed version is available in the provided content, obtain and apply the upstream patch addressing CVE-2025-10164.
PUBLIC EXPLOITS

Exploits

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VALID 0 / 0 TOTALView more in app

No public exploit code observed for this vulnerability.

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