PYSEC-2021-620

TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for QuantizeV2 can trigger a read outside of bounds of heap allocated array. This occurs whenever axis is a negative value less than -1. In this case, we are accessing data before the start o...

PYSEC-2021-403

TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for QuantizeV2 can trigger a read outside of bounds of heap allocated array. This occurs whenever axis is a negative value less than -1. In this case, we are accessing data before the start o...

CVE-2021-41211

TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for QuantizeV2 can trigger a read outside of bounds of heap allocated array. This occurs whenever axis is a negative value less than -1. In this case, we are accessing data before the start o...

PYSEC-2021-818

TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for QuantizeV2 can trigger a read outside of bounds of heap allocated array. This occurs whenever axis is a negative value less than -1. In this case, we are accessing data before the start o...

PYSEC-2021-403

TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for QuantizeV2 can trigger a read outside of bounds of heap allocated array. This occurs whenever axis is a negative value less than -1. In this case, we are accessing data before the start o...

CVE-2021-41211

TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for QuantizeV2 can trigger a read outside of bounds of heap allocated array. This occurs whenever axis is a negative value less than -1. In this case, we are accessing data before the start o...

PT-2021-23184 · Google · Tensorflow

Name of the Vulnerable Software and Affected Versions: TensorFlow versions 2.6.1 through 2.6.1 TensorFlow versions prior to 2.7.0 Description: The shape inference code for QuantizeV2 can trigger a read outside of bounds of heap allocated array. This occurs whenever axis is a negative value less...

Google TensorFlow 缓冲区错误漏洞

Google TensorFlow is a suite of end-to-end open source platforms for machine learning from Google, Inc. in the United States. Google TensorFlow suffers from a buffer error vulnerability that stems from the fact that in the affected version, QuantizeV2's shape inference code could trigger a read...

PT-2021-23177 · Google · Tensorflow

Name of the Vulnerable Software and Affected Versions: TensorFlow versions prior to 2.7.0 TensorFlow versions 2.6.1 and earlier TensorFlow versions 2.5.2 and earlier TensorFlow versions 2.4.4 and earlier Description: The shape inference functions for the QuantizeAndDequantizeV operations can...

IP Surveillance Bugs in Axis Gear Allow RCE, Data Theft

Three vulnerabilities in the IP video-surveillance systems created by Axis Communications could allow arbitrary code execution, among other attacks. That’s according to Nozomi Networks Labs, whose researchers examined the company’s Axis Companion Recorder, a compact network video recorder NVR tha...

Axis Os 缓冲区错误漏洞

Axis Os is an edge device operating system from Axis of Sweden. A security vulnerability exists in AXIS OS 6.40 or later that stems from not properly validating control parameters related to SMTP notifications. This could lead to a buffer overflow and data leakage...

Axis Os 注入漏洞

Axis Os is an edge device operating system from Axis of Sweden. An injection vulnerability exists in Axis devices AXIS OS version 5.51 and later versions, which stems from a failure to properly validate a control parameter related to the SMTP test function, and as a result, it is possible to add...

Axis OS 安全漏洞

Axis Os is an edge device operating system from Axis of Sweden. A security vulnerability exists in Axis devices AXIS OS version 5.51 and later versions, which stems from a failure to properly validate user control parameters related to the SMTP test function...

CVE-2021-31989

A user with permission to log on to the machine hosting the AXIS Device Manager client could under certain conditions extract a memory dump from the built-in Windows Task Manager application. The memory dump may potentially contain credentials of connected Axis devices...

CVE-2021-31989

A user with permission to log on to the machine hosting the AXIS Device Manager client could under certain conditions extract a memory dump from the built-in Windows Task Manager application. The memory dump may potentially contain credentials of connected Axis devices...

Design/Logic Flaw

A user with permission to log on to the machine hosting the AXIS Device Manager client could under certain conditions extract a memory dump from the built-in Windows Task Manager application. The memory dump may potentially contain credentials of connected Axis devices...

CVE-2021-31989

A user with permission to log on to the machine hosting the AXIS Device Manager client could under certain conditions extract a memory dump from the built-in Windows Task Manager application. The memory dump may potentially contain credentials of connected Axis devices...

CVE-2021-31989

The CVE-2021-31989 entry affects AXIS Device Manager: a user with host permissions can, under certain conditions, extract a memory dump from the built-in Windows Task Manager, potentially exposing credentials of connected Axis devices. Documented across multiple sources (Axis tech note, Red Hat a...

CVE-2021-31989

A user with permission to log on to the machine hosting the AXIS Device Manager client could under certain conditions extract a memory dump from the built-in Windows Task Manager application. The memory dump may potentially contain credentials of connected Axis devices...

GHSA-9W2P-5MGW-P94C Integer overflow due to conversion to unsigned

Impact The implementation of tf.rawops.QuantizeAndDequantizeV4Grad is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. python import tensorflow as tf tf.rawops.QuantizeAndDequantizeV4Grad...