CVE-2022-36014— Null-dereference in `mlir::tfg::TFOp::nameAttr` in TensorFlow
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I. Basic Information for CVE-2022-36014
Vulnerability Information
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Vulnerability Title
Null-dereference in `mlir::tfg::TFOp::nameAttr` in TensorFlow
Source: NVD (National Vulnerability Database)
Vulnerability Description
TensorFlow is an open source platform for machine learning. When `mlir::tfg::TFOp::nameAttr` receives null type list attributes, it crashes. We have patched the issue in GitHub commits 3a754740d5414e362512ee981eefba41561a63a6 and a0f0b9a21c9270930457095092f558fbad4c03e5. 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
空指针解引用
Source: NVD (National Vulnerability Database)
Vulnerability Title
Google TensorFlow 代码问题漏洞
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 存在代码问题漏洞，该漏洞源于当 mlir::tfg::TFOp::nameAttr 接收到空类型列表属性时，它会崩溃。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-2022-36014
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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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