Vulnerability Monitor

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CVE-2020-15201

In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Hence, the code is prone to heap buffer overflow. If `split_values` does not end with a value at least `num_values` then the `while` loop condition will trigger a read outside of the bounds of `split_values` once `batch_idx` grows too large. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.

Published

2020-09-25T19:15:15.353

Last Modified

2024-11-21T05:05:04.303

Status

Modified

Source

[email protected]

Severity

CVSSv3.1: 4.8 (MEDIUM)

CVSSv2 Vector

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

  • Access Vector: NETWORK
  • Access Complexity: MEDIUM
  • Authentication: NONE
  • Confidentiality Impact: PARTIAL
  • Integrity Impact: PARTIAL
  • Availability Impact: PARTIAL
Exploitability Score

8.6

Impact Score

6.4

Weaknesses
  • Type: Secondary
    CWE-20
    CWE-122
  • Type: Primary
    CWE-787
Affected Vendors & Products
Type Vendor Product Version/Range Vulnerable?
Application google tensorflow 2.3.0 Yes
References