Goal Reached Thanks to every supporter — we hit 100%!

Goal: 1000 CNY · Raised: 1000 CNY

100.0%

CVE-2022-35939— Out of bounds write in `scatter_nd` op in TensorFlow Lite

CVSS 7.0 · High EPSS 0.23% · P46
Get alerts for future matching vulnerabilitiesLog in to subscribe

I. Basic Information for CVE-2022-35939

Vulnerability Information

Have questions about the vulnerability? See if Shenlong's analysis helps!
View Shenlong Deep Dive ↗

Although we use advanced large model technology, its output may still contain inaccurate or outdated information.Shenlong tries to ensure data accuracy, but please verify and judge based on the actual situation.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
Out of bounds write in `scatter_nd` op in TensorFlow Lite
Source: NVD (National Vulnerability Database)
Vulnerability Description
TensorFlow is an open source platform for machine learning. The `ScatterNd` function takes an input argument that determines the indices of of the output tensor. An input index greater than the output tensor or less than zero will either write content at the wrong index or trigger a crash. We have patched the issue in GitHub commit b4d4b4cb019bd7240a52daa4ba61e3cc814f0384. 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:L/I:L/A:H
Source: NVD (National Vulnerability Database)
Vulnerability Type
跨界内存写
Source: NVD (National Vulnerability Database)
Vulnerability Title
Google TensorFlow 缓冲区错误漏洞
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 存在缓冲区错误漏洞,该漏洞源于 ScatterNd 函数接受一个输入参数,该参数确定输出张量的索引。大于输出张量或小于零的输入索引将在错误的索引处写入内容或触发崩溃。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

VendorProductAffected VersionsCPESubscribe
tensorflowtensorflow < 2.7.2 -

II. Public POCs for CVE-2022-35939

#POC DescriptionSource LinkShenlong Link
AI-Generated POCPremium

No public POC found.

Login to generate AI POC

III. Intelligence Information for CVE-2022-35939

登录查看更多情报信息。

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-2022-359377.0 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-2022-359665.9 MEDIUMSegfault in `QuantizedAvgPool` 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
CVE-2022-359845.9 MEDIUM`CHECK` fail in `ParameterizedTruncatedNormal` in TensorFlow

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

IV. Related Vulnerabilities

V. Comments for CVE-2022-35939

No comments yet


Leave a comment