CVE-2020-15214
Out of bounds write in tensorflow-lite
描述
In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a write out bounds / segmentation fault if the segment ids are not sorted. Code assumes that the segment ids are in increasing order, using the last element of the tensor holding them to determine the dimensionality of output tensor. This results in allocating insufficient memory for the output tensor and in a write outside the bounds of the output array. This usually results in a segmentation fault, but depending on runtime conditions it can provide for a write gadget to be used in future memory corruption-based exploits. The issue is patched in commit 204945b19e44b57906c9344c0d00120eeeae178a and is released in TensorFlow versions 2.2.1, or 2.3.1. A potential workaround would be to add a custom `Verifier` to the model loading code to ensure that the segment ids are sorted, although this only handles the case when the segment ids are stored statically in the model. A similar validation could be done if the segment ids are generated at runtime between inference steps. If the segment ids are generated as outputs of a tensor during inference steps, then there are no possible workaround and users are advised to upgrade to patched code.
如何修補 CVE-2020-15214
要修補 CVE-2020-15214,請將受影響套件升級到下列已修補版本。
- —升級至 2.2.1 或更新版本
- —升級至 2.2.1 或更新版本
- —升級至 2.2.1 或更新版本
CVE-2020-15214 正在被利用嗎?
低 — EPSS 為 0.6%,目前沒有觀察到大規模利用活動。
受影響套件(3)
- >= 2.2.0, < 2.2.1
- >= 2.2.0, < 2.2.1