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Although we use advanced large model technology, its output may still contain inaccurate or outdated information.Shenlong tries to ensure data accuracy, but please verify and judge based on the actual situation.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
Denial of service in tensorflow-lite
Vulnerability Description
In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a denial of service by causing an out of memory allocation in the implementation of segment sum. Since code uses the last element of the tensor holding them to determine the dimensionality of output tensor, attackers can use a very large value to trigger a large allocation. 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 limit the maximum value in the segment ids tensor. This only handles the case when the segment ids are stored statically in the model, but a similar validation could be done if the segment ids are generated at runtime, between inference steps. However, 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.
CVSS Information
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:N/I:N/A:L
Vulnerability Type
内存缓冲区边界内操作的限制不恰当
Vulnerability Title
Google TensorFlow 安全漏洞
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 Lite 2.2.1之前版本,2.3.1版本中存在安全漏洞,该漏洞允许攻击者通过一定手段获取到很大内存,导致内存不足触发拒绝服务。
CVSS Information
N/A
Vulnerability Type
N/A