GHSA-PR5M-4W22-8483 NanoHTTPD Cross-site Scripting vulnerability

An issue was discovered in RouterNanoHTTPD.java in NanoHTTPD through 2.3.1. The GeneralHandler class implements a basic GET handler that prints debug information as an HTML page. Any web server that extends this class without implementing its own GET handler is vulnerable to reflected XSS, becaus...

CVE-2021-26539

Apostrophe Technologies sanitize-html before 2.3.1 does not properly handle internationalized domain name IDN which could allow an attacker to bypass hostname whitelist validation set by the "allowedIframeHostnames" option...

PT-2021-17026

Name of the Vulnerable Software and Affected Versions sanitize-html versions prior to 2.3.1 Description The issue arises from improper handling of internationalized domain names IDN, which could allow an attacker to bypass hostname whitelist validation set by the allowedIframeHostnames option. Th...

AZL-45072 CVE-2020-27814 affecting package openjpeg2 for versions less than 2.3.1-12

A heap-buffer overflow was found in the way openjpeg2 handled certain PNG format files. An attacker could use this flaw to cause an application crash or in some cases execute arbitrary code with the permission of the user running such an application...

Fedora 33 : adplug / audacious-plugins / ocp (2021-64168929e4)

The remote Fedora 33 host has packages installed that are affected by multiple vulnerabilities as referenced in the FEDORA-2021-64168929e4 advisory. - An issue was discovered in AdPlug 2.3.1. There are several double-free vulnerabilities in the CEmuopl class in emuopl.cpp because of a destructor'...

Type confusion

beforeupstreamconnection in AuthPlugin in http/proxy/auth.py in proxy.py before 2.3.1 accepts incorrect Proxy-Authorization header data because of a boolean confusion and versus or...

PT-2021-19195 · Proxy.Py · Proxy.Py

Name of the Vulnerable Software and Affected Versions: proxy.py versions prior to 2.3.1 Description: The issue arises from a boolean confusion in the before upstream connection function within the AuthPlugin in http/proxy/auth.py, where it incorrectly accepts Proxy-Authorization header data due t...

Abhinavsingh Proxy.py Authorization Issues Vulnerability

Abhinavsingh Proxy.py is a Python-based proxy server for network monitoring, control and application development, testing, and debugging by Abhinavsingh Personal Developer. A security vulnerability exists in Abhinavsingh Proxy.py version 2.3.1 and earlier versions of AuthPlugin that allows...

AZL-44106 CVE-2020-27842 affecting package openjpeg2 for versions less than 2.3.1-12

There's a flaw in openjpeg's t2 encoder in versions prior to 2.4.0. An attacker who is able to provide crafted input to be processed by openjpeg could cause a null pointer dereference. The highest impact of this flaw is to application availability...

OpenJPEG Code Issue Vulnerability

OpenJPEG is an open source C-based JPEG2000 codec. A code issue vulnerability exists in OpenJPEG 2.3.1, which stems from a heap buffer overwrite error found in lib /openjp2/mqc.c, leading to out-of-bounds writes. An attacker could exploit this vulnerability to cause a remote denial of service or...

Authentication flaw

Apache Kylin 2.0.0, 2.1.0, 2.2.0, 2.3.0, 2.3.1, 2.3.2, 2.4.0, 2.4.1, 2.5.0, 2.5.1, 2.5.2, 2.6.0, 2.6.1, 2.6.2, 2.6.3, 2.6.4, 2.6.5, 2.6.6, 3.0.0-alpha, 3.0.0-alpha2, 3.0.0-beta, 3.0.0, 3.0.1, 3.0.2, 3.1.0, 4.0.0-alpha has one restful api which exposed Kylin's configuration information without any...

Unspecified Vulnerability in Google Tensorflow (CNVD-2020-57075)

Google TensorFlow is a suite of end-to-end open source platforms for machine learning from Google USA. A security vulnerability exists in Tensorflow versions prior to 2.2.1, 2.3.1, which can be exploited by an attacker to cause memory leakage issues...

Google TensorFlow Input Validation Error Vulnerability

Google TensorFlow is a suite of end-to-end open source platforms for machine learning from Google USA. A security vulnerability exists in Tensorflow versions prior to 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1, and 2.3.1, which stems from a lack of validation of the datasplits parameter of...

Google TensorFlow code issue vulnerability (CNVD-2020-54473)

Google TensorFlow is a suite of end-to-end open source platforms for machine learning from Google USA. A security vulnerability exists in TensorFlow eager mode versions prior to 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1, and 2.3.1, which can be exploited by attackers to cause segmentation errors...

CVE-2020-15199

In Tensorflow before version 2.3.1, the RaggedCountSparseOutput does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the splits tensor has the minimum required number of elements. Code uses this quantity to initialize a different data...

CVE-2020-15203

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, by controlling the fill argument of tf.strings.asstring, a malicious attacker is able to trigger a format string vulnerability due to the way the internal format use in a printf call is constructed. This may result in segmentati...

CVE-2020-15198

In Tensorflow before version 2.3.1, the SparseCountSparseOutput implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the indices tensor has the same shape as the values one. The values in these tensors are always accessed...

CVE-2020-15199

In Tensorflow before version 2.3.1, the RaggedCountSparseOutput does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the splits tensor has the minimum required number of elements. Code uses this quantity to initialize a different data...

CVE-2020-15196

In Tensorflow version 2.3.0, the SparseCountSparseOutput and RaggedCountSparseOutput implementations don't validate that the weights tensor has the same shape as the data. The check exists for DenseCountSparseOutput, where both tensors are fully specified. In the sparse and ragged count weights a...

CVE-2020-15197

In Tensorflow before version 2.3.1, the SparseCountSparseOutput implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the indices tensor has rank 2. This tensor must be a matrix because code assumes its elements are access...