Service interruption via oversized gradient dimensions
Published Nov 18, 2022 · Updated Apr 22, 2025
Integer overflow in Google TensorFlow before 2.8.4, 2.9.0 through 2.9.2, and 2.10.0 allows remote authenticated users to interrupt service. ResizeNearestNeighborOpGrad directly constructed an output TensorShape from supplied height and width values without rejecting overflow in the dimension product before allocation. Reachability requires an application path that invokes the gradient operation with user-controlled dimensions and user interaction; the reported impact is limited to availability.
Summary
What happened
Integer overflow in Google TensorFlow before 2.8.4, 2.9.0 through 2.9.2, and 2.10.0 allows remote authenticated users to interrupt service. ResizeNearestNeighborOpGrad directly constructed an output TensorShape from supplied height and width values without rejecting overflow in the dimension product before allocation. Reachability requires an application path that invokes the gradient operation with user-controlled dimensions and user interaction; the reported impact is limited to availability.
The record
- CVE
- CVE-2022-41907
- Published
- Nov 18, 2022
- Updated
- Apr 22, 2025
- Vendor
- Product
- TensorFlow
- Classifications
- CWE-131, T1499.004
- Attack vector
- network
- Privileges
- authenticated
Timeline
How it unfolded
- Nov 18, 2022CVE publishedPublication date reported by the CVE source.
- Apr 22, 2025Record 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=>= 2.10.0, < 2.10.1
- Affected versionversion=< 2.8.4
- Affected versionversion=>= 2.9.0, < 2.9.3
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 oversized ResizeNearestNeighborGrad invocationproof of concept · demonstrated
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Technologies
Your stack
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Your stack
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