CVE-2023-38674: PaddlePaddle · Divide By Zero
Affects PaddlePaddleSource CVE Database V5
Not known to be exploited · CVSS 4.7 Medium : upgrade to 2.6.0 when convenient.
Data as of 26 Oct 2026, 06:26 UTC
- EPSS
- 0.4% chance of exploitation in 30 days – higher than 41% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
- Patch
- Available – fixed in 2.6.0
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:N/I:N/A:LExploitation evidence
Disclosed: evidence found.
CVE published 3 Jan 2024
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 2026-10-26.
What to do
Upgrade PaddlePaddle to 2.6.0.
Affected software
| Product | Affected | Fixed in |
|---|---|---|
PyPIpaddlepaddlepkg:pypi/paddlepaddleOther 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
European organizations should promptly upgrade PaddlePaddle to version 2.6.0 or later once available, as this version addresses the divide-by-zero flaw in the nanmedian function. If you cannot patch yet, organizations should implement input validation and sanitization on all data fed into PaddlePaddle, especially inputs to the nanmedian function, to prevent zero or invalid values that could trigger the divide-by-zero error. Monitoring and logging of PaddlePaddle runtime errors should be enhanced to detect early signs of crashes or abnormal behavior. Access controls should be tightened to restrict who can submit data or interact with PaddlePaddle services, minimizing the risk of malicious or accidental triggering of the vulnerability. Additionally, organizations should consider isolating AI workloads in containerized or sandboxed environments to limit the impact of potential crashes. Regular backups and failover mechanisms for AI services can help maintain availability during incidents. Security teams should stay alert for any emerging exploit reports and apply patches promptly.
Description
FPE in paddle.nanmedian in PaddlePaddle before 2.6.0. This flaw can cause a runtime crash and a denial of service.