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VulnerabilityPublished Updated

CVE-2026-92365: vllm · Inefficient Algorithmic Complexity

Affects vllmSource CVE Database V5

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Not known to be exploited · CVSS 5.3 Medium.

Data as of 1 Nov 2026, 08:20 UTC

CVSS 4.0 base score
5.3Medium
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.5% chance of exploitation in 30 days – higher than 44% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N/E:X

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 16 Sep 2026

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponized: no evidence on record.

    No public exploit code indexed in Metasploit or Exploit-DB

  4. Exploited in the wild: no evidence on record.

    Not in CISA KEV and no source reports exploitation

  5. Observed by OffSeq Mirage: no evidence on record.

    No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 31 Oct 2026.

What to do

Affected software

ProductAffectedFixed in
vllm-projectvllmAffected
  • 0.1 – 0.29.0
29 affected builds
Fixed in–
PyPIvllmpkg:pypi/vllmOther threatsAffected
  • 0.1 – 0.29.0
29 affected builds
Fixed in–

CPE configurations (1)

  • cpe:2.3:a:vllm-project:vllm:*:*:*:*:*:*:*:*

Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.

AI-suggested

A fix for this vulnerability is not yet officially available as the pull request awaits acceptance. Users should monitor the vendor's repository or advisory channels for the official patch release and apply it once available. Until then, no official workaround or mitigation is documented.

Description

A vulnerability was found in vllm-project vllm up to 0.29.0. Affected by this issue is some unknown functionality of the file vllm/v1/sample/thinking_budget_state.py. The manipulation results in inefficient algorithmic complexity. It is possible to launch the attack remotely. The pull request to fix this issue awaits acceptance.

References

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