Improper Input ValidationWeakness · CWE-20

CVE-2025-10164

HIGH · 7.3 CVSS v3.1 Published 2025-09-09
Mitigation only
No fix yet — a mitigation exists. There is no fixed release. A documented workaround reduces exposure in the meantime.
See remediation →
82/100
Remediation priority · High
Remotely reachable No privileges Zero-click

Official description Straight from the sourceThe vendor's or NVD's own wording, published unedited. Authoritative, but often terse — it says what broke, rarely what to do.

NVD · unedited
A security flaw has been discovered in lmsys sglang 0.4.6. Affected by this vulnerability is the function main of the file /update_weights_from_tensor. The manipulation of the argument serialized_named_tensors results in deserialization. The attack can be launched remotely. The exploit has been released to the public and may be exploited. The vendor was contacted early about this disclosure but did not respond in any way.

Technical summary Written by usOur analysis, written from the advisory, the CVSS vector and the affected-version data. It adds context the advisory leaves out, and never invents facts that are not in the source.

dbcve analysis · moderate confidence

A deserialization vulnerability in lmsys sglang 0.4.6 allows remote attackers to execute arbitrary code via the /update_weights_from_tensor endpoint by supplying maliciously crafted serialized tensor data to the serialized_named_tensors argument.

MitigationUpgrade to a patched version of sglang once available. In the interim, restrict network access to the affected endpoint and implement strict input validation on the serialized tensor data before deserialization.

Verify against the referenced sources before acting — the references below are authoritative for this CVE, this summary is not.

CVSS breakdown How the score is builtThe industry scoring standard. It rates how the flaw is reached, what it takes to exploit, and what an attacker gains — the score is derived from those, not the other way round.

From the vector
Attack vector
Network
Complexity
Low
Privileges
None
User interaction
None
Scope
Unchanged
Confidentiality
Low
Integrity
Low
Availability
Low

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:L

Am I affected? How to checkSteps we derive from the advisory and the affected-version data, so you can decide whether this CVE reaches your setup. They are a guide, not a scan — your own configuration is the authority.

dbcve checks

Work through these to decide whether this CVE applies to you.

  1. Identify sglang installation and version
    Run 'pip show sglang' or 'pip list | grep sglang' to check if sglang is installed and its version number
    Affected if The installed version is exactly 0.4.6 or falls within the 0.4.6 release line (e.g., 0.4.6.x)
  2. Locate the update_weights_from_tensor endpoint
    Search the sglang source code for '/update_weights_from_tensor' or inspect the API routes defined in the server implementation
    Affected if The endpoint is present in the codebase and registered as an available API route
  3. Check if the serialized_named_tensors parameter is handled
    Examine the handler function for /update_weights_from_tensor to see if it accepts and deserializes the serialized_named_tensors argument without strict validation
    Affected if The endpoint processes the serialized_named_tensors argument through an unsafe deserialization method (e.g., pickle, torch.load) without sanitization
  4. Determine API server network exposure
    Check the sglang server startup configuration and running process (e.g., 'ps aux | grep sglang', netstat, or ss) to see if the API listens on 0.0.0.0 or a publicly accessible IP address
    Affected if The sglang server is bound to a network interface accessible to untrusted users (e.g., 0.0.0.0 or external IP) and the vulnerable endpoint is enabled

You are affected if sglang version 0.4.6 is installed AND the /update_weights_from_tensor endpoint is exposed to a network where remote attackers can send malicious serialized tensor data.

Generated from the published advisory. Verify against your own configuration.

Check your environment

Paste your version and any relevant configuration and it will be compared against the affected criteria above. Do not include secrets or credentials.

AI-assisted, checked against the advisory. Informational, not a guarantee.

Remediation Closing itWhat it takes to close this. Where a vendor fix exists we point at it; where none exists we say so plainly, and can build one. Effort estimates are scoped from the advisory, not from your codebase.

From vendor data
Mitigation available No clean upgrade yet — mitigate in the meantime
Mitigation

Upgrade to a patched version of sglang once available. In the interim, restrict network access to the affected endpoint and implement strict input validation on the serialized tensor data before deserialization.

Have this fixed Scoped from the published advisory
  • Consultation4.0 h
  • Implementation16.0 h
  • Testing8.0 h
  • Review / QA4.0 h
32.0 hours of engineering $5,600
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References Go to the primary sourcePrimary sources — vendor advisories, patches and trackers. Where our summary and a reference disagree, the reference wins.

Primary sources

Practitioner notes

Contributed

Peer-ranked notes from engineers who’ve handled CVE-2025-10164 in production — separate from our analysis above.

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What this is

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