Process crash via non-scalar SparseMatrixNNZ input
Published Nov 18, 2022 · Updated Apr 22, 2025
Improper input validation in TensorFlow allows attackers to crash a process by passing a non-scalar tensor to SparseMatrixNNZ. ExtractVariantFromInput treats the sparse_matrix input as a scalar Variant without first verifying that its tensor shape has rank zero, which reaches a fatal CHECK. The crash occurs only when a consuming application invokes the affected raw operation with attacker-controlled input, and the demonstrated consequence is process interruption.
Summary
What happened
Improper input validation in TensorFlow allows attackers to crash a process by passing a non-scalar tensor to SparseMatrixNNZ. ExtractVariantFromInput treats the sparse_matrix input as a scalar Variant without first verifying that its tensor shape has rank zero, which reaches a fatal CHECK. The crash occurs only when a consuming application invokes the affected raw operation with attacker-controlled input, and the demonstrated consequence is process interruption.
The record
- CVE
- CVE-2022-41901
- Published
- Nov 18, 2022
- Updated
- Apr 22, 2025
- Vendor
- Product
- TensorFlow
- Classifications
- CWE-20, CWE-617, T1499
- Attack vector
- network
- Privileges
- unauthenticated
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
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Weakness, pattern, technique
Public exploit references
- Upstream SparseMatrixNNZ crash reproducerproof of concept · demonstrated
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Technologies
Your stack
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Your stack
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