Service interruption via TensorKey heap buffer over-read
Published May 20, 2022 · Updated Apr 23, 2025
Heap buffer over-read in Google TensorFlow 2.8.0 allows local users to interrupt a process through TensorKey hashing. AbslHashValue in tensorflow/core/framework/tensor_key.h reads tensor.data() for AllocatedBytes(), although that estimate includes noncontiguous pointed-to storage. Reachability requires local code that causes an affected TensorKey to hash such a tensor; the bounded consequence is process failure rather than data disclosure or modification.
Summary
What happened
Heap buffer over-read in Google TensorFlow 2.8.0 allows local users to interrupt a process through TensorKey hashing. AbslHashValue in tensorflow/core/framework/tensor_key.h reads tensor.data() for AllocatedBytes(), although that estimate includes noncontiguous pointed-to storage. Reachability requires local code that causes an affected TensorKey to hash such a tensor; the bounded consequence is process failure rather than data disclosure or modification.
The record
- CVE
- CVE-2022-29210
- Published
- May 20, 2022
- Updated
- Apr 23, 2025
- Vendor
- Product
- TensorFlow
- Classifications
- CWE-787, CWE-122, CWE-120
- Attack vector
- local
- Privileges
- Unavailable
Timeline
How it unfolded
- May 20, 2022CVE publishedPublication date reported by the CVE source.
- Apr 23, 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?
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- Affected versionversion=== 2.8.0
What conditions does exploitation require?
What is affected?
Attacks
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Public exploit references
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