CVE-2024-34997: joblib · Deserialization of Untrusted Data
Affects joblibSource CVE Database V5
Not known to be exploited · CVSS 7.5 High.
Data as of 26 Oct 2026, 17:16 UTC
- EPSS
- 0.6% chance of exploitation in 30 days – higher than 51% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:H/I:H/A:HExploitation evidence
Disclosed: evidence found.
CVE published 17 May 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 26 Oct 2026.
What to do
Affected software
| Product | Affected | Fixed in |
|---|---|---|
PyPIjoblibpkg:pypi/joblibOther 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
- Restrict joblib cache usage strictly to trusted data sources; avoid caching or loading data from untrusted or unauthenticated inputs.
- Implement strict access controls on cache directories to prevent unauthorized modification or injection of malicious cache files.
- Monitor and audit cache file integrity regularly to detect tampering.
- Consider disabling caching features in joblib where feasible, especially in environments exposed to untrusted users or data.
- Use containerization or sandboxing to isolate processes using joblib to limit potential impact of exploitation.
- Stay alert for official patches or updates from the joblib maintainers and apply them promptly once available.
- Educate developers and data scientists about the risks of deserialization vulnerabilities and safe handling of cached data.
- Employ runtime application self-protection (RASP) or endpoint detection and response (EDR) tools to detect anomalous behavior indicative of exploitation attempts.
Description
joblib v1.4.2 was discovered to contain a deserialization vulnerability via the component joblib.numpy_pickle::NumpyArrayWrapper().read_array(). NOTE: this is disputed by the supplier because NumpyArrayWrapper is only used during caching of trusted content.