CVE-2020-15200

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. Thus, the code sets up conditions to cause a heap buffer overflow. A BatchedMap is equivalent to a vector where each element is a hashmap. However, if the first element of splits_values is not 0, batch_idx will never be 1, hence there will be no hashmap at index 0 in per_batch_counts. Trying to access that in the user code results in a segmentation fault. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.

Risk Information

Base Score

5.9

MODERATE

Vector

CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H

EPSS Score

Exploitation Probability

0.276

Associated Vulnerability

Vulnerability	OS Platform
Multiple vulnerabilities are fixed in Python-tensorflow 2.3.1	Windows
Multiple vulnerabilities are fixed in Python-tensorflow-cpu 2.3.1	Windows
Multiple vulnerabilities are fixed in Python-tensorflow-gpu 2.3.1	Windows
Multiple vulnerabilities are fixed in Python-tensorflow for linux 2.3.1	Linux
Multiple vulnerabilities are fixed in Python-tensorflow-cpu for linux 2.3.1	Linux
Multiple vulnerabilities are fixed in Python-tensorflow-gpu for linux 2.3.1	Linux

Patch Details

No records found

References

https://nvd.nist.gov/vuln/detail/CVE-2023-1234
https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2023-1234