Vulnerability Monitor

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CVE-2021-29609


TensorFlow is an end-to-end open source platform for machine learning. Incomplete validation in `SparseAdd` results in allowing attackers to exploit undefined behavior (dereferencing null pointers) as well as write outside of bounds of heap allocated data. The implementation(https://github.com/tensorflow/tensorflow/blob/656e7673b14acd7835dc778867f84916c6d1cac2/tensorflow/core/kernels/sparse_add_op.cc) has a large set of validation for the two sparse tensor inputs (6 tensors in total), but does not validate that the tensors are not empty or that the second dimension of `*_indices` matches the size of corresponding `*_shape`. This allows attackers to send tensor triples that represent invalid sparse tensors to abuse code assumptions that are not protected by validation. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.


Published

2021-05-14T20:15:15.850

Last Modified

2024-11-21T06:01:29.180

Status

Modified

Source

[email protected]

Severity

CVSSv3.1: 5.3 (MEDIUM)

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: Secondary
    CWE-665
  • Type: Primary
    CWE-476
    CWE-787

Affected Vendors & Products
Type Vendor Product Version/Range Vulnerable?
Application google tensorflow < 2.1.4 Yes
Application google tensorflow < 2.2.3 Yes
Application google tensorflow < 2.3.3 Yes
Application google tensorflow < 2.4.2 Yes

References