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BIT-tensorflow-2020-15201

Published Mar 6, 2024·Last modified May 20, 2025
Affected Components(0)

No affected components available

Description

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.

Risk Scores
Base Score
0.0

Measures severity based on intrinsic characteristics of the vulnerability, independent of environment.

Threat Intelligence
0.0

No exploitation activity has been observed at this time. Continue routine monitoring.

EPSS
0.57%

The exploit probability is very low. The vulnerability is unlikely to be exploited in the next 30 days.

Exploit
Not available

We did not find any exploit available. Neither in GitHub repositories nor in the Exploit-Database.

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