CVE-2020-15196
Heap buffer overflow in Tensorflow
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Description
In Tensorflow version 2.3.0, the `SparseCountSparseOutput` and `RaggedCountSparseOutput` implementations don't validate that the `weights` tensor has the same shape as the data. The check exists for `DenseCountSparseOutput`, where both tensors are fully specified. In the sparse and ragged count weights are still accessed in parallel with the data. But, since there is no validation, a user passing fewer weights than the values for the tensors can generate a read from outside the bounds of the heap buffer allocated for the weights. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
Affected
Our own answer: ranges merged, affected separated from platform-only, with confidence and review flags.
Remediation
No guide yetNo remediation guidance has been written for this CVE yet. What the record does show:
Patch and advisory references
References (3)
CVSS
- Attack Vector
- NETWORK
- Complexity
- LOW
- Privileges
- LOW
- User Interaction
- NONE
- Scope
- CHANGED
- Confidentiality
- HIGH
- Integrity
- HIGH
- Availability
- HIGH
Quick Info
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