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🛡️ CVE-2024-34072 — sagemaker

🟠 CVSS 8.0 — High ✅ No Known Exploit CWE-502 NVD
8.0
CVSS Score
0 Low4 Medium7 High9 Critical10

Description

sagemaker-python-sdk vulnerable to Deserialization of Untrusted Data

Impact

sagemaker.base_deserializers.NumpyDeserializer module before v2.218.0 allows potentially unsafe deserialization when untrusted data is passed as pickled object arrays. This consequently may allow an unprivileged third party to cause remote code execution, denial of service, affecting both confidentiality and integrity.

Impacted versions: <2.218.0.

Credit

We would like to thank HiddenLayer for collaborating on this issue through the coordinated vulnerability disclosure process.

Workarounds

Do not pass pickled numpy object arrays which originated from an untrusted source, or that could have been tampered with. Only pass pickled numpy object arrays from sources you trust.

References

If you have any questions or comments about this advisory we ask that you contact AWS/Amazon Security via our vulnerability reporting page [1] or directly via email to [[email protected]](mailto:[email protected]). Please do not create a public GitHub issue.

[1] Vulnerability reporting page: https://aws.amazon.com/security/vulnerability-reporting

Fixed by: [https://github.com/aws/sagemaker-python-sdk/pull/4557](https://github.com/aws/sagemaker-python-sdk/pull/4557)

How this vulnerability can be exploited

This issue can be reached with local access to the system, attack complexity is low, an attacker needs no privileges on the target. A user must be tricked into taking some action. The scope is unchanged, so the impact stays within the vulnerable component. Rated impact: confidentiality high, integrity high, availability high.

CVSS metrics in full

The score comes from this vector: CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H

  • Attack vector: Local — a local account, shell or session on the host is needed.
  • Attack complexity: Low — the attack works reliably, with no preparation.
  • Privileges required: None — an unauthenticated stranger can try it.
  • User interaction: Required — someone has to click, open or visit something.
  • Scope: Unchanged — the damage stays inside the vulnerable component.
  • Confidentiality impact: High — total loss, or loss the attacker controls.
  • Integrity impact: High — total loss, or loss the attacker controls.
  • Availability impact: High — total loss, or loss the attacker controls.

Weakness class

CVE-2024-34072 is classified as CWE-502: Deserialization of Untrusted Data. Serialised data from an untrusted source is reconstructed into objects, which can trigger code during the process.

Affected software

CVE-2024-34072 is recorded against 2 packages.

  • sagemaker (fixed in 2.218.0)
  • unknown

Timeline and source

Published on 7 July 2026. No public exploit is currently recorded for this entry. A vendor advisory or fix has been published. Record sourced from NVD.

References

github.com (Web)
nvd.nist.gov (Advisory)
github.com (Web)
github.com (Fix)
github.com (Package)
pypi.org (Package)
github.com (Advisory)

Other advisories for this package

sagemaker has other advisories on record. If you are patching this one, these are worth checking on the same host:

Same weakness in other software

These advisories are the same class of weakness (CWE-502: Deserialization of Untrusted Data) in other software:

Details

Severity HIGH
CVSS Score 8.0
CVSS Vector CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
CWE CWE-502
Public Exploit ✅ No
Source NVD
Published 2026-07-07
Updated 2026-08-20
Modified 2026-07-07

Affected Packages

Software From version Fixed in
sagemaker — 2.218.0
unknown — —

Similar Threats

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ⓘ Data Notice: The information presented above has been compiled from publicly available internet sources. Boteraser aggregates this data solely for informational purposes and does not independently classify, evaluate, or endorse any findings about the vulnerabilities listed. The accuracy and completeness of this information is the sole responsibility of the original publishers. Boteraser and its operators accept no liability for any decisions made based on this data.

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