Process crash via zero batch-dimension divisor
Published May 14, 2021 · Updated Aug 3, 2024
Divide-by-zero in Google's TensorFlow DenseCountSparseOutput allows local users to crash a process via crafted zero-dimension tensors. The count_ops.cc kernel multiplies values-tensor batch dimensions into num_batch_elements, then divides by that user-controlled result without rejecting zero. Exploitation requires local code capable of invoking the raw operation and controlling its values argument; the demonstrated consequence is termination of the current TensorFlow process.
Summary
What happened
Divide-by-zero in Google's TensorFlow DenseCountSparseOutput allows local users to crash a process via crafted zero-dimension tensors. The count_ops.cc kernel multiplies values-tensor batch dimensions into num_batch_elements, then divides by that user-controlled result without rejecting zero. Exploitation requires local code capable of invoking the raw operation and controlling its values argument; the demonstrated consequence is termination of the current TensorFlow process.
The record
- CVE
- CVE-2021-29554
- Published
- May 14, 2021
- Updated
- Aug 3, 2024
- Vendor
- Product
- TensorFlow
- Classifications
- CWE-369, T1499.004
- Attack vector
- local
- Privileges
- authenticated
Timeline
How it unfolded
- May 14, 2021CVE publishedPublication date reported by the CVE source.
- Aug 3, 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?
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- Affected versionversion=< 2.3.3
- Affected versionversion=>= 2.4.0, < 2.4.2
What conditions does exploitation require?
What is affected?
Published CVSS scores
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Attacks
What attackers are doing with it
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Weakness, pattern, technique
Public exploit references
- DenseCountSparseOutput floating-point exception reproducerproof of concept · demonstrated
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Technologies
Your stack
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Your stack
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