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CVE-2021-29512

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Date: May 14, 2021

TensorFlow is an end-to-end open source platform for machine learning. If the `splits` argument of `RaggedBincount` does not specify a valid `SparseTensor`(https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor), then an attacker can trigger a heap buffer overflow. This will cause a read from outside the bounds of the `splits` tensor buffer in the implementation of the `RaggedBincount` op(https://github.com/tensorflow/tensorflow/blob/8b677d79167799f71c42fd3fa074476e0295413a/tensorflow/core/kernels/bincount_op.cc#L430-L433). Before the `for` loop, `batch_idx` is set to 0. The user controls the `splits` array, making it contain only one element, 0. Thus, the code in the `while` loop would increment `batch_idx` and then try to read `splits(1)`, which is outside of bounds. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3, as these are also affected.

Language: Python

Severity Score

Severity Score

Weakness Type (CWE)

Out-of-bounds Write

CWE-787

Buffer Copy without Checking Size of Input ('Classic Buffer Overflow')

CWE-120

Top Fix

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CVSS v3.1

Base Score:
Attack Vector (AV): LOCAL
Attack Complexity (AC): HIGH
Privileges Required (PR): LOW
User Interaction (UI): NONE
Scope (S): UNCHANGED
Confidentiality (C): NONE
Integrity (I): NONE
Availability (A): LOW

CVSS v2

Base Score:
Access Vector (AV): LOCAL
Access Complexity (AC): LOW
Authentication (AU): NONE
Confidentiality (C): PARTIAL
Integrity (I): PARTIAL
Availability (A): PARTIAL
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