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VulnerabilityPublished

CVE-2026-73558: vllm · Integer Overflow or Wraparound

Affects vllmSource CVE Database V5

0
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Not known to be exploited · CVSS 5.3 Medium : upgrade to 0.27.0 when convenient.

Data as of 12 Nov 2026, 23:24 UTC

CVSS 3.1 base score
5.3Medium
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.4% chance of exploitation in 30 days – higher than 36% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
Patch
Available – fixed in 0.27.0
CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:N/A:N

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 13 Aug 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 13 Nov 2026.

What to do

Upgrade vllm and vllm-project/vllm to 0.27.0.

Affected software

ProductAffectedFixed in
vllm-projectvllmAffected
  • <0.27.0
Fixed in
  • 0.27.0
GitHubvllm-project/vllmpkg:github/vllm-project/vllmOther threatsAffected
  • <0.27.0
Fixed in
  • 0.27.0

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

AI-suggested

Upgrade to vllm version 0.27.0 or later, where this integer overflow vulnerability is fixed. No other mitigation or temporary workaround is documented. Patch status is confirmed by the vendor advisory stating the fix is included in version 0.27.0.

Description

vLLM is an inference and serving engine for large language models. Prior to 0.27.0, an integer overflow in blockIdx.x * 2 * d in activation_kernels.cu can cause act_and_mul_kernel to consume another batched user's input, allowing a request processed in the same inference batch to receive a partial or complete copy of another user's inference result. This issue is fixed in version 0.27.0.

References

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