Process crash via unvalidated empty pooling tensors
Published Aug 12, 2021 · Updated Aug 4, 2024
Improper input validation in Google TensorFlow before 2.3.4, 2.4.0 through 2.4.2, and 2.5.0 allows local users to crash a process. The MaxPoolGrad kernel accepts empty orig_input and orig_output tensors and continues into pooling calculations that end in a segmentation fault. Exploitation requires the ability to submit crafted tensors to a local TensorFlow execution context, and the reported consequence is limited to that process crash.
Summary
What happened
Improper input validation in Google TensorFlow before 2.3.4, 2.4.0 through 2.4.2, and 2.5.0 allows local users to crash a process. The MaxPoolGrad kernel accepts empty orig_input and orig_output tensors and continues into pooling calculations that end in a segmentation fault. Exploitation requires the ability to submit crafted tensors to a local TensorFlow execution context, and the reported consequence is limited to that process crash.
The record
- CVE
- CVE-2021-37674
- Published
- Aug 12, 2021
- Updated
- Aug 4, 2024
- Vendor
- Product
- TensorFlow
- Classifications
- CWE-1284, CWE-20, T1499.004
- Attack vector
- local
- Privileges
- authenticated
Timeline
How it unfolded
- Aug 12, 2021CVE publishedPublication date reported by the CVE source.
- Aug 4, 2024Record updatedLatest update available in the CVE record.
Exploitability
Present is not the same as exploitable
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Is a vulnerable build present?
Compare these published version ranges with your installed build and any vendor patches.
- Affected versionversion=< 2.3.4
- Affected versionversion=>= 2.4.0, < 2.4.3
- Affected versionversion=>= 2.5.0, < 2.5.1
What conditions does exploitation require?
What is affected?
Published CVSS scores
CVSS describes severity. EPSS estimates exploitation probability.
Attacks
What attackers are doing with it
Daily unique IPs observed by Shadowserver honeypots for known exploited vulnerabilities (KEVs). Missing observations do not establish an absence of attacks.
Weakness, pattern, technique
Public exploit references
- TensorFlow MaxPoolGrad segmentation-fault reproducerproof of concept · demonstrated
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Technologies
Your stack
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Your stack
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