Process crash via mismatched empty sparse tensors
Published Aug 12, 2021 · Updated Aug 4, 2024
Null pointer dereference 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. SparseTensorSliceDataset fails to require indices and values to be empty together, then calls dim_size on a null indices tensor during monotonicity validation. Local access to a process that evaluates attacker-controlled sparse-tensor arguments is required, and the consequence is limited to interrupting that process.
Summary
What happened
Null pointer dereference 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. SparseTensorSliceDataset fails to require indices and values to be empty together, then calls dim_size on a null indices tensor during monotonicity validation. Local access to a process that evaluates attacker-controlled sparse-tensor arguments is required, and the consequence is limited to interrupting that process.
The record
- CVE
- CVE-2021-37647
- Published
- Aug 12, 2021
- Updated
- Aug 4, 2024
- Vendor
- Product
- TensorFlow
- Classifications
- CWE-476, 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?
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
- SparseTensorSliceDataset crash reproducerproof of concept · demonstrated
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Technologies
Your stack
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Your stack
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