CVE-2022-36003— `CHECK` fail in `RandomPoissonV2` in TensorFlow
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I. Basic Information for CVE-2022-36003
Vulnerability Information
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Vulnerability Title
`CHECK` fail in `RandomPoissonV2` in TensorFlow
Source: NVD (National Vulnerability Database)
Vulnerability Description
TensorFlow is an open source platform for machine learning. When `RandomPoissonV2` receives large input shape and rates, it gives a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit 552bfced6ce4809db5f3ca305f60ff80dd40c5a3. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
Source: NVD (National Vulnerability Database)
CVSS Information
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Source: NVD (National Vulnerability Database)
Vulnerability Type
可达断言
Source: NVD (National Vulnerability Database)
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。 Google TensorFlow 存在安全漏洞，该漏洞源于当 RandomPoissonV2 接收到较大的输入形状和速率时，它会给出断言失败，从而触发拒绝服务攻击。该漏洞将在 2.10.0 版本， 2.9.1 版本， 2.8.1 版本， 2.7.2 版本中得到修复。
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 | < 2.7.2 | - |
II. Public POCs for CVE-2022-36003
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|---|
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Same Patch Batch · tensorflow · 2022-09-16 · 59 CVEs total
| CVE-2022-35938 | 7.0 HIGH | OOB read in `Gather_nd` op in TensorFlow Lite Micro |
| CVE-2022-35939 | 7.0 HIGH | Out of bounds write in `scatter_nd` op in TensorFlow Lite |
| CVE-2022-35937 | 7.0 HIGH | OOB read in `Gather_nd` op in TensorFlow Lite |
| CVE-2022-35974 | 5.9 MEDIUM | Segfault in `QuantizeDownAndShrinkRange` in TensorFlow |
| CVE-2022-35959 | 5.9 MEDIUM | `CHECK` failures in `AvgPool3DGrad` in TensorFlow |
| CVE-2022-35941 | 5.9 MEDIUM | `CHECK` failure in `AvgPoolOp` in Tensorflow |
| CVE-2022-35940 | 5.9 MEDIUM | Int overflow in `RaggedRangeOp` in Tensoflow |
| CVE-2022-35952 | 5.9 MEDIUM | `CHECK` failures in `UnbatchGradOp` in TensorFlow |
| CVE-2022-35970 | 5.9 MEDIUM | Segfault in `QuantizedInstanceNorm` in TensorFlow |
| CVE-2022-35969 | 5.9 MEDIUM | `CHECK` fail in `Conv2DBackpropInput` in TensorFlow |
| CVE-2022-35971 | 5.9 MEDIUM | `CHECK` fail in `FakeQuantWithMinMaxVars` in TensorFlow |
| CVE-2022-35973 | 5.9 MEDIUM | Segfault in `QuantizedMatMul` in TensorFlow |
| CVE-2022-35972 | 5.9 MEDIUM | Segfault in `QuantizedBiasAdd` in TensorFlow |
| CVE-2022-35967 | 5.9 MEDIUM | Segfault in `QuantizedAdd` in TensorFlow |
| CVE-2022-35979 | 5.9 MEDIUM | Segfault in `QuantizedRelu` and `QuantizedRelu6` |
| CVE-2022-35981 | 5.9 MEDIUM | `CHECK` fail in `FractionalMaxPoolGrad` in TensorFlow |
| CVE-2022-35982 | 5.9 MEDIUM | Segfault in `SparseBincount` in TensorFlow |
| CVE-2022-35988 | 5.9 MEDIUM | `CHECK` fail in `tf.linalg.matrix_rank` in TensorFlow |
| CVE-2022-35989 | 5.9 MEDIUM | `CHECK` fail in `MaxPool` in TensorFlow |
| CVE-2022-35983 | 5.9 MEDIUM | `CHECK` fail in `Save` and `SaveSlices` in TensorFlow |
Showing top 20 of 59 CVEs. View all on vendor page → →
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