CVE-2020-15197— Denial of Service in Tensorflow
Quick assessment
Affected
tensorflow tensorflow
Exploitation
No confirmed in-the-wild exploitation; assess based on exposure
Recommended action
Check the vendor advisory and references for a fixed version. If immediate upgrade is impossible, restrict exposure and increase monitoring.
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之前版本中存在安全漏洞，该漏洞源SparseCountSparseOutput实现无法验证输入参数是否形成有效的稀疏张量，该漏洞允许攻击者造成安装中的服务被拒绝。
Possible ATT&CK Techniques 1 AI
T1499 · Endpoint Denial of Service
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I. Basic Information for CVE-2020-15197
Vulnerability Information
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Vulnerability Title
Denial of Service in Tensorflow
Source: CVE Program / CVE List V5
Vulnerability Description
In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has rank 2. This tensor must be a matrix because code assumes its elements are accessed as elements of a matrix. However, malicious users can pass in tensors of different rank, resulting in a `CHECK` assertion failure and a crash. This can be used to cause denial of service in serving installations, if users are allowed to control the components of the input sparse tensor. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
Source: CVE Program / CVE List V5
CVSS Information
CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:C/C:N/I:N/A:H
Source: CVE Program / CVE List V5
Vulnerability Type
可达断言
Source: CVE Program / CVE List V5
Vulnerability Title
Google TensorFlow 安全漏洞
Source: CNNVD (China National Vulnerability Database)
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之前版本中存在安全漏洞，该漏洞源SparseCountSparseOutput实现无法验证输入参数是否形成有效的稀疏张量，该漏洞允许攻击者造成安装中的服务被拒绝。
Source: CNNVD (China National Vulnerability Database)
CVSS Information
N/A
Source: CNNVD (China National Vulnerability Database)
Vulnerability Type
N/A
Source: CNNVD (China National Vulnerability Database)
Affected Products
| Vendor | Product | Affected Versions | CPE | Subscribe |
|---|---|---|---|---|
| tensorflow | tensorflow | = 2.3.0 | - |
|
II. Public POCs for CVE-2020-15197
| # | POC Description | Source Link | Shenlong Link |
|---|
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Patches & Fixes for CVE-2020-15197 (1)
Vendor Advisories for CVE-2020-15197 (1)
-
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qc53-44cj-vfvx x_refsource_CONFIRM
Other References for CVE-2020-15197 (1)
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https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1 x_refsource_MISC
Same Patch Batch · tensorflow · 2020-09-25 · 25 CVEs total
| CVE-2020-15202 | 9.0 CRITICAL | Integer truncation in Shard API usage |
| CVE-2020-15205 | 9.0 CRITICAL | Data leak in Tensorflow |
| CVE-2020-15206 | 9.0 CRITICAL | Denial of Service in Tensorflow |
| CVE-2020-15207 | 8.7 HIGH | Segfault and data corruption in tensorflow-lite |
| CVE-2020-15196 | 8.5 HIGH | Heap buffer overflow in Tensorflow |
| CVE-2020-15195 | 8.5 HIGH | Heap buffer overflow in Tensorflow |
| CVE-2020-15212 | 8.1 HIGH | Out of bounds access in tensorflow-lite |
| CVE-2020-15214 | 8.1 HIGH | Out of bounds write in tensorflow-lite |
| CVE-2020-15203 | 7.5 HIGH | Denial of Service in Tensorflow |
| CVE-2020-15208 | 7.4 HIGH | Data corruption in tensorflow-lite |
| CVE-2020-15193 | 7.1 HIGH | Memory corruption in Tensorflow |
| CVE-2020-15210 | 6.5 MEDIUM | Segmentation fault in tensorflow-lite |
| CVE-2020-15209 | 5.9 MEDIUM | Null pointer dereference in tensorflow-lite |
| CVE-2020-15199 | 5.9 MEDIUM | Denial of Service in Tensorflow |
| CVE-2020-15200 | 5.9 MEDIUM | Segfault in Tensorflow |
| CVE-2020-15198 | 5.4 MEDIUM | Heap buffer overflow in Tensorflow |
| CVE-2020-15190 | 5.3 MEDIUM | Segfault in Tensorflow |
| CVE-2020-15191 | 5.3 MEDIUM | Undefined behavior in Tensorflow |
| CVE-2020-15204 | 5.3 MEDIUM | Segfault in Tensorflow |
| CVE-2020-15194 | 5.3 MEDIUM | Denial of Service in Tensorflow |
Showing top 20 of 25 CVEs. View all on vendor page → →
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