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CVE-2021-29514

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-L446). Before the `for` loop, `batch_idx` is set to 0. The attacker sets `splits(0)` to be 7, hence the `while` loop does not execute and `batch_idx` remains 0. This then results in writing to `out(-1, bin)`, which is before the heap allocated buffer for the output tensor. 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.

Published

2021-05-14T20:15:11.247

Last Modified

2024-11-21T06:01:17.233

Status

Modified

Source

[email protected]

Severity

CVSSv3.1: 2.5 (LOW)

CVSSv2 Vector

AV:L/AC:L/Au:N/C:P/I:P/A:P

  • Access Vector: LOCAL
  • Access Complexity: LOW
  • Authentication: NONE
  • Confidentiality Impact: PARTIAL
  • Integrity Impact: PARTIAL
  • Availability Impact: PARTIAL
Exploitability Score

3.9

Impact Score

6.4

Weaknesses
  • Type: Primary
    CWE-787
Affected Vendors & Products
Type Vendor Product Version/Range Vulnerable?
Application google tensorflow < 2.3.3 Yes
Application google tensorflow < 2.4.2 Yes
References