sagemaker-python-sdk: Deserialization of Untrusted Data
CVE-2024-34072 is a high-severity deserialization of untrusted data vulnerability in sagemaker-python-sdk from AWS, with a CVSS 3.1 base score of 7.8 out of 10. It can be exploited with local access to the system by an unauthenticated attacker, but only if a user takes part, for example by opening a link or file. The record lists version 2.218.0 as the first without the flaw, so updating sagemaker-python-sdk to that release or later removes the exposure. There is no confirmed exploitation so far. EPSS estimates a 0.41% chance of exploitation within 30 days, which is low compared with other CVEs.
High severity with no evidence of exploitation so far.
What to do
- Update sagemaker-python-sdk to 2.218.0 or a later version.
- Read the advisory on github.com for workarounds and exact fixed builds.
- Because the attack needs a user to take part, warn users about unexpected links and files related to this product until it is patched.
Affected products and versions
| Vendor | Product | Affected versions | Fixed in |
|---|---|---|---|
| AWS | sagemaker-python-sdk | < 2.218.0; before 2.218.0 | 2.218.0 |
Version data comes from the organisation that assigned the CVE. Confirm against the vendor advisory before deciding you are unaffected.
How the severity score breaks down
- Attack vector
- LocalThe attacker needs local access or must trick a user into running something.
- Attack complexity
- LowNo special conditions are needed; the attack works reliably.
- Privileges required
- NoneNo account or login is needed.
- User interaction
- RequiredA user must take an action such as opening a file or link.
- Scope
- UnchangedImpact stays within the vulnerable component.
- Confidentiality
- HighAll data handled by the component can be read.
- Integrity
- HighData or code can be modified at will.
- Availability
- HighThe component can be taken down completely.
Vector: CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H. Scored by CNA (github.com).
Official description
sagemaker-python-sdk is a library for training and deploying machine learning models on Amazon SageMaker. The 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. Users are advised to upgrade to version 2.218.0. Users unable to upgrade should 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 trusted sources.
Source: the CVE record as published by its numbering authority, via NVD and CVE.org.
The underlying weakness: Deserialization of Untrusted Data
The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid.
How developers prevent this class of flaw
- If available, use the signing/sealing features of the programming language to assure that deserialized data has not been tainted. For example, a hash-based message authentication code (HMAC) could be used to ensure that data has not been modified.
- When deserializing data, populate a new object rather than just deserializing. The result is that the data flows through safe input validation and that the functions are safe.
- Explicitly define a final object() to prevent deserialization.
More Deserialization of Untrusted Data vulnerabilities (CWE-502)
Timeline
- CVE record published.
- CISA published its SSVC assessment (exploitation: none, automatable: no, technical impact: total).
- Record last changed materially (score, affected products, status or references).
References
Patches and release notes
Other vulnerabilities in sagemaker-python-sdk
- 7.2 High severity
- 7.2 High severity
- 7.8 High severity
Recent Deserialization of Untrusted Data vulnerabilities
- 9.8 Critical severity
- 8.8 High severity
- 8.8 High severity
- 8.8 High severity
- 8.8 High severity
- 8.8 High severity
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