CVE-2022-35938— OOB read in `Gather_nd` op in TensorFlow Lite Micro
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。 Google TensorFlow 存在缓冲区错误漏洞，该漏洞源于 GatherNd 函数接受确定输入和输出大小的参数。如果给定的输入大于或等于输出的大小，则会触发越界内存读取或崩溃。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。
Possible ATT&CK Techniques 1 AI
T1203 · Exploitation for Client Execution
Get alerts for future matching vulnerabilities
Log in to subscribe
I. Basic Information for CVE-2022-35938
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Although we use advanced large model technology, its output may still contain inaccurate or outdated information.Shenlong tries to ensure data accuracy, but please verify and judge based on the actual situation.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
OOB read in `Gather_nd` op in TensorFlow Lite Micro
Source: CVE Program / CVE List V5
Vulnerability Description
TensorFlow is an open source platform for machine learning. The `GatherNd` function takes arguments that determine the sizes of inputs and outputs. If the inputs given are greater than or equal to the sizes of the outputs, an out-of-bounds memory read or a crash is triggered. This issue has been patched in GitHub commit 4142e47e9e31db481781b955ed3ff807a781b494. 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: CVE Program / CVE List V5
CVSS Information
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:L/A:H
Source: CVE Program / CVE List V5
Vulnerability Type
跨界内存读
Source: CVE Program / CVE List V5
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 GatherNd 函数接受确定输入和输出大小的参数。如果给定的输入大于或等于输出的大小，则会触发越界内存读取或崩溃。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-2022-35938
| # | POC Description | Source Link | Shenlong Link |
|---|
AI-Generated POC
Premium
No public POC found.
Login to generate AI POCIII. Intelligence Information for CVE-2022-35938
请登录查看更多情报信息。
Patches & Fixes for CVE-2022-35938 (1)
Vendor Advisories for CVE-2022-35938 (1)
-
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3m3g-pf5v-5hpj x_refsource_CONFIRM
Other References for CVE-2022-35938 (1)
Same Patch Batch · tensorflow · 2022-09-16 · 59 CVEs total
| 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-2022-35966 | 5.9 MEDIUM | Segfault in `QuantizedAvgPool` 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 |
| CVE-2022-35984 | 5.9 MEDIUM | `CHECK` fail in `ParameterizedTruncatedNormal` in TensorFlow |
Showing top 20 of 59 CVEs. View all on vendor page → →
IV. Related Vulnerabilities
Same product: tensorflow
Same vendor: tensorflow
-
CVE-2026-2492
TensorFlow HDF5 Library Uncontrolled Search Path Element Loc -
CVE-2023-33976
TensorFlow segfault in array_ops.upper_bound -
CVE-2024-3660
Arbitrary code injection vulnerability in Keras framework < -
CVE-2023-25661
Denial of Service in TensorFlow -
CVE-2023-25660
TensorFlow vulnerable to seg fault in `tf.raw_ops.Print`
Same weakness: CWE-125
-
CVE-2026-79616
Out-of-bounds read vulnerability in Context2D.path and PathS -
CVE-2026-91807
Foxit PDF Editor/Reader PDF File Parsing Out-Of-Bounds Read -
CVE-2026-91808
Foxit PDF Editor/Reader JPEG File Parsing Out-Of-Bounds Read -
CVE-2026-91810
Foxit PDF Editor/Reader Doc Object Out-Of-Bounds Read Inform -
CVE-2026-91817
Foxit PDF Editor/Reader AcroForm Out-of-Bounds Read Remote C
V. Comments for CVE-2022-35938
No comments yet