Vulnerability Information
Although we use advanced large model technology, its output may still contain inaccurate or outdated information.Shenlong tries to ensure data accuracy, but please verify and judge based on the actual situation.
Vulnerability Title
Segfault in Tensorflow
Vulnerability 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.
CVSS Information
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Vulnerability Type
输入验证不恰当
Vulnerability Title
Google TensorFlow 缓冲区错误漏洞
Vulnerability Description
Google TensorFlow是美国谷歌（Google）公司的一套用于机器学习的端到端开源平台。 Tensorflow 2.3.1之前版本中存在缓冲区错误漏洞，该漏洞源于 RaggedCountSparseOutput 不会验证输入参数是否形成有效的参差张量。
CVSS Information
N/A
Vulnerability Type
N/A