Heap OOB in TensorFlow Lite

TensorFlow is an end-to-end open source platform for machine learning. In affected versions TFLite's [`expand_dims.cc`](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/expand_dims.cc#L36-L50) contains a vulnerability which allows reading one element outside of bounds of heap allocated data. If `axis` is a large negative value (e.g., `-100000`), then after the first `if` it would still be negative. The check following the `if` statement will pass and the `for` loop would read one element before the start of `input_dims.data` (when `i = 0`). We have patched the issue in GitHub commit d94ffe08a65400f898241c0374e9edc6fa8ed257. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

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

跨界内存读

Google TensorFlow 缓冲区错误漏洞

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。 Google TensorFlow 存在缓冲区错误漏洞，该漏洞源于TensorFlow 可能允许本地经过身份验证的攻击者获取敏感信息，这是由 TFLite 中 expand_dims.cc 中的堆越界读取缺陷引起的。通过发送特制的请求，攻击者可以利用此漏洞读取堆分配数据边界之外的一个元素，并使用此信息对受影响的系统发起进一步攻击。

N/A

缓冲区错误