CVE-2021-1062
published 2021-01-08CVE-2021-1062: NVIDIA vGPU manager contains a vulnerability in the vGPU plugin, in which an input data length is not validated, which may lead to tampering of data or denial…
PriorityP430high7.1CVSS 3.1
AVLACLPRLUINSUCNIHAH
EPSS
0.34%
26.4th percentile
NVIDIA vGPU manager contains a vulnerability in the vGPU plugin, in which an input data length is not validated, which may lead to tampering of data or denial of service. This affects vGPU version 8.x (prior to 8.6) and version 11.0 (prior to 11.3).
Affected
7 ranges
| Vendor | Product | Version range | Fixed in |
|---|---|---|---|
| intel | optimization_for_tensorflow | >= 0 < 2.1.4 | 2.1.4 |
| intel | optimization_for_tensorflow | >= 2.2.0 < 2.2.3 | 2.2.3 |
| intel | optimization_for_tensorflow | >= 2.3.0 < 2.3.3 | 2.3.3 |
| intel | optimization_for_tensorflow | >= 2.4.0 < 2.4.2 | 2.4.2 |
| nvidia | nvidia_virtual_gpu_manager | — | — |
| nvidia | virtual_gpu_manager | >= 11.0 < 11.3 | 11.3 |
| nvidia | virtual_gpu_manager | >= 8.0 < 8.6 | 8.6 |
CVSS provenance
nvdv3.17.1HIGHCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:H
nvdv2.03.6LOWAV:L/AC:L/Au:N/C:N/I:P/A:P
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GHSA
GHSA-p739-mvjp-w433: NVIDIA vGPU manager contains a vulnerability in the vGPU plugin, in which an input data length is not validated, which may lead to tampering of data o
ghsa_unreviewed·2022-05-24
CVE-2021-1062 [HIGH] CWE-20 GHSA-p739-mvjp-w433: NVIDIA vGPU manager contains a vulnerability in the vGPU plugin, in which an input data length is not validated, which may lead to tampering of data o
NVIDIA vGPU manager contains a vulnerability in the vGPU plugin, in which an input data length is not validated, which may lead to tampering of data or denial of service. This affects vGPU version 8.x (prior to 8.6) and version 11.0 (prior to 11.3).
GHSA
Heap OOB access in `Dilation2DBackpropInput`
ghsa·2021-05-21
CVE-2021-29566 [LOW] CWE-787 Heap OOB access in `Dilation2DBackpropInput`
Heap OOB access in `Dilation2DBackpropInput`
### Impact
An attacker can write outside the bounds of heap allocated arrays by passing invalid arguments to `tf.raw_ops.Dilation2DBackpropInput`:
```python
import tensorflow as tf
input_tensor = tf.constant([1.1] * 81, shape=[3, 3, 3, 3], dtype=tf.float32)
filter = tf.constant([], shape=[0, 0, 3], dtype=tf.float32)
out_backprop = tf.constant([1.1] * 1062, shape=[3, 2, 59, 3], dtype=tf.float32)
tf.raw_ops.Dilation2DBackpropInput(
input=input_tensor, filter=filter, out_backprop=out_backprop,
strides=[1, 40, 1, 1], rates=[1, 56, 56, 1], padding='VALID')
```
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/afd954e65f15aea4d438d0a219136fc4a63a573d/tensorflow/core/kernels/dilation_ops.cc#L321-L322) does not vali
No detection rules found.
No public exploits indexed.
No writeups or analysis indexed.
2021-01-08
Published