Security Notice: NVIDIA Response to Log4j Vulnerabilities - December 2021

This notice is a response to the remote code execution vulnerabilities in the Log4j Java library, which is also known as Log4Shell. The CVE IDs of these vulnerabilities are as follows: CVE-2021-44228 CVE-2021-45046 CVE-2021-45105 NVIDIA is aware of these vulnerabilities and is evaluating their...

Security Bulletin: NVIDIA DCGM - August 2021

NVIDIA has released a software update for NVIDIA® Data Center GPU Manager DCGM. The update addresses security issues that may lead to privilege escalation, total loss of confidentiality and integrity, and complete denial of service. To protect your system, download and install the latest DCGM...

NVIDIA Windows GPU Display Driver (January 2021)

A display driver installed on the remote Windows host is affected by multiple vulnerabilities: - NVIDIA GPU Display Driver contains a vulnerability in the NVIDIA Control Panel component, in which an attacker with local system access can corrupt a system file, which may lead to denial of service o...

Google TensorFlow Denial of Service Vulnerability (CNVD-2021-00093)

Google TensorFlow is a suite of end-to-end open source platforms for machine learning from Google USA. Google TensorFlow suffers from a denial-of-service vulnerability that stems from the LSTM GRU layer receiving a zero-length input when using a CUDA backend, which results in a check failure. An...

CVE-2020-26270

In affected versions of TensorFlow running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer...

CVE-2020-26270

In affected versions of TensorFlow running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer...

PYSEC-2020-336

In affected versions of TensorFlow running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer...

PYSEC-2020-256

In affected versions of TensorFlow running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer...

PYSEC-2020-256

In affected versions of TensorFlow running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer...

CVE-2020-26270 CHECK-fail in LSTM with zero-length input in TensorFlow

In affected versions of TensorFlow running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer...

CVE-2020-26270

In affected versions of TensorFlow running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer...

CVE-2020-26270

In affected versions of TensorFlow running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer...

CVE-2020-26270

CVE-2020-26270 affects TensorFlow: when an LSTM/GRU layer receives a zero-length input, the CUDA backend triggers a CHECK failure leading to a denial-of-service (query-of-death). Public sources consistently describe this as a vulnerability in affected TensorFlow builds, with fixes implemented in ...

CHECK-fail in LSTM with zero-length input in TensorFlow

Impact Running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer. Patches We have patched the...

CVE-2020-26270: Improper Input Validation

In affected versions of TensorFlow running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer...

Google TensorFlow 输入验证错误漏洞

Google TensorFlow is a suite of end-to-end open source platforms for machine learning from Google USA. Google TensorFlow suffers from a denial-of-service vulnerability that stems from the LSTM GRU layer receiving a zero-length input when using a CUDA backend, which results in a check failure. An...

NVIDIA CUDA Toolkit < 11.1.1 ( 11.1 Update 1 ) Arbitrary Code Execution Vulnerability

NVIDIA CUDA Toolkit contains a vulnerability in the NVJPEG library in which an out-of-bounds read or write operation may lead to code execution, denial of service, or information disclosure. Note that Nessus has not tested for this issue but has instead relied only on the application's...

NVIDIA CUDA Toolkit Installed (Windows)

Binary data nvidiacudatoolkitwininstalled.nbin...

CVE-2020-5991

NVIDIA CUDA Toolkit, all versions prior to 11.1.1, contains a vulnerability in the NVJPEG library in which an out-of-bounds read or write operation may lead to code execution, denial of service, or information disclosure...

CVE-2020-5991

NVIDIA CUDA Toolkit, all versions prior to 11.1.1, contains a vulnerability in the NVJPEG library in which an out-of-bounds read or write operation may lead to code execution, denial of service, or information disclosure...