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CVE-2026-85668 – Unauthenticated Arbitrary File Read – Xinference (xorbitsai/inference) ≤3.3.0

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Summary

CVE-2026-85668 is an unauthenticated arbitrary-path file read vulnerability in Xinference (the xinference PyPI package by xorbitsai), an open-source distributed AI model inference framework. The flaw resides in the POST /v1/models/llm/auto-register API endpoint, which accepts a caller-supplied model_path without authentication or path confinement, allowing attackers to read configuration files from arbitrary locations on the host filesystem. The issue affects versions 0 through 3.3.0 and carries a severity score of 8.7 (HIGH).

Technical details

  • Root cause: The auto-register endpoint accepts an attacker-controlled model_path parameter and uses it to load and parse files without validating or confining the path to an approved directory.
  • Trigger conditions: An attacker sends a crafted POST request to /v1/models/llm/auto-register specifying a path to a location of interest on the target server; no prior authentication or user interaction is required.
  • Attack vector: Network — the endpoint is reachable over HTTP(S) without credentials (Attack Complexity: Low, Privileges Required: None, User Interaction: None).
  • Impact: The endpoint reads and parses config.json, tokenizer_config.json, and chat_template.jinja at the supplied path and reflects the parsed content back in the API response, letting an unauthenticated remote attacker probe the filesystem and extract the contents of files matching those names anywhere on the server.

Affected software

  • xorbitsai inference (PyPI package xinference), versions 0 through 3.3.0

Severity

  • CVSS score: 8.7 (HIGH)
  • CVSS v4.0 vector: CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:N/VA:N/SC:N/SI:N/SA:N
  • CVSS v3.1 equivalent: 7.5 (HIGH), vector CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N

Mitigation and recommended actions

  • Immediate: No official patched release has been published by the maintainers as of this writing — the issue tracker entry for this vulnerability was closed by the project as "not planned." Security teams should not assume upgrading resolves this issue and should verify current project guidance before relying on a version bump alone.
  • Network mitigations: Restrict or disable public/unauthenticated access to the Xinference API, especially the /v1/models/llm/auto-register endpoint, by placing it behind an authenticating reverse proxy, VPN, or network ACLs limiting access to trusted hosts only.
  • Workarounds: Do not expose Xinference management/registration endpoints directly to the internet; monitor for unexpected requests to auto-register and audit for unauthorized file-read attempts; restrict filesystem permissions available to the Xinference process to limit the value of any successfully read files.

How IONIX identifies potentially affected assets

IONIX matches the following signals against data already collected when it crawled the asset; identifying the technology sends no request beyond that crawl.

  • Page title: Xinference

References

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