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CVE-2022-35996— Floating point exception in `Conv2D` in TensorFlow

CVSS 5.9 · Medium EPSS 0.06% · P20
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I. Basic Information for CVE-2022-35996

Vulnerability Information

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Vulnerability Title
Floating point exception in `Conv2D` in TensorFlow
Source: NVD (National Vulnerability Database)
Vulnerability Description
TensorFlow is an open source platform for machine learning. If `Conv2D` is given empty `input` and the `filter` and `padding` sizes are valid, the output is all-zeros. This causes division-by-zero floating point exceptions that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 611d80db29dd7b0cfb755772c69d60ae5bca05f9. 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
除零错误
Source: NVD (National Vulnerability Database)
Vulnerability Title
Google TensorFlow 数字错误漏洞
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 存在数字错误漏洞,该漏洞源于如果 Conv2D 被指定为空 input 并且 filter 和 padding 大小有效,则输出全为零。这会导致除零浮点异常,可用于触发拒绝服务攻击。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

VendorProductAffected VersionsCPESubscribe
tensorflowtensorflow < 2.7.2 -

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III. Intelligence Information for CVE-2022-35996

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Same Patch Batch · tensorflow · 2022-09-16 · 59 CVEs total

CVE-2022-359387.0 HIGHOOB read in `Gather_nd` op in TensorFlow Lite Micro
CVE-2022-359397.0 HIGHOut of bounds write in `scatter_nd` op in TensorFlow Lite
CVE-2022-359377.0 HIGHOOB read in `Gather_nd` op in TensorFlow Lite
CVE-2022-359745.9 MEDIUMSegfault in `QuantizeDownAndShrinkRange` in TensorFlow
CVE-2022-359595.9 MEDIUM`CHECK` failures in `AvgPool3DGrad` in TensorFlow
CVE-2022-359415.9 MEDIUM`CHECK` failure in `AvgPoolOp` in Tensorflow
CVE-2022-359405.9 MEDIUMInt overflow in `RaggedRangeOp` in Tensoflow
CVE-2022-359525.9 MEDIUM`CHECK` failures in `UnbatchGradOp` in TensorFlow
CVE-2022-359705.9 MEDIUMSegfault in `QuantizedInstanceNorm` in TensorFlow
CVE-2022-359695.9 MEDIUM`CHECK` fail in `Conv2DBackpropInput` in TensorFlow
CVE-2022-359715.9 MEDIUM`CHECK` fail in `FakeQuantWithMinMaxVars` in TensorFlow
CVE-2022-359735.9 MEDIUMSegfault in `QuantizedMatMul` in TensorFlow
CVE-2022-359725.9 MEDIUMSegfault in `QuantizedBiasAdd` in TensorFlow
CVE-2022-359675.9 MEDIUMSegfault in `QuantizedAdd` in TensorFlow
CVE-2022-359795.9 MEDIUMSegfault in `QuantizedRelu` and `QuantizedRelu6`
CVE-2022-359815.9 MEDIUM`CHECK` fail in `FractionalMaxPoolGrad` in TensorFlow
CVE-2022-359825.9 MEDIUMSegfault in `SparseBincount` in TensorFlow
CVE-2022-359885.9 MEDIUM`CHECK` fail in `tf.linalg.matrix_rank` in TensorFlow
CVE-2022-359895.9 MEDIUM`CHECK` fail in `MaxPool` in TensorFlow
CVE-2022-359835.9 MEDIUM`CHECK` fail in `Save` and `SaveSlices` in TensorFlow

Showing top 20 of 59 CVEs. View all on vendor page &rarr; →

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