CVE-2025-2149: PyTorch Quantized Sigmoid Module nnq_Sigmoid initialization
Affects pytorchSource GCVE Database
Not known to be exploited : upgrade to 2.7.0 when convenient.
Data as of 25 Oct 2026, 19:02 UTC
Rated by Threat Radar · No CVSS score from NVD or the CNA
- EPSS
- 0.2% chance of exploitation in 30 days – higher than 17% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
- Patch
- Available – fixed in 2.7.0
Exploitation evidence
Disclosed: evidence found.
CVE published 26 Feb 2026
Detectable: no evidence on record.
No public nuclei template indexed
Weaponised: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by 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 2026-10-25.
What to do
Upgrade pytorch to 2.7.0.
Affected software
| Product | Affected | Fixed in |
|---|---|---|
Bitnamipytorchpkg:bitnami/pytorchOther threats | Affected
| Fixed in
|
Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.
AI-suggested
A patch is available for this vulnerability. Users should update PyTorch to version 2.7.0 or later where the issue is fixed. Applying the official patch will remediate the improper initialization flaw.
Description
A vulnerability in PyTorch's Quantized Sigmoid Module (nnq_Sigmoid) affects versions 2.6.0 up to but not including 2.7.0. The issue involves improper initialization caused by manipulation of the scale and zero_point arguments. Exploitation requires local access and is considered difficult due to high attack complexity. The vulnerability has been publicly disclosed, but no known exploits are reported in the wild. A patch is available to address this issue.