Huawei EulerOS: Security Advisory for unbound (EulerOS-SA-2022-2482)

The remote host is missing an update for the Huawei EulerOS SPDX-FileCopyrightText: 2022 Greenbone AG Some text descriptions might be excerpted from a referenced sources, and are Copyright C by the respective right holders. SPDX-License-Identifier: GPL-2.0-only ifdescription...

Zinc Delete Template Function Cross-Site Scripting Vulnerability

Zinc is a full-text indexing search engine open sourced by Zinc Labs. Zinc v0.1.9 and later, v0.3.1 and earlier versions have a cross-site scripting vulnerability that can be exploited by attackers to obtain sensitive information such as user credentials...

Zinc delete user function cross-site scripting vulnerability

Zinc is a full-text indexing search engine open sourced by Zinc Labs. Zinc v0.1.9 and later, v0.3.1 and earlier versions have a cross-site scripting vulnerability that could be exploited by attackers to obtain sensitive information such as user credentials...

EulerOS 2.0 SP8 : unbound (EulerOS-SA-2022-2482)

According to the versions of the unbound packages installed, the EulerOS installation on the remote host is affected by the following vulnerabilities : - NLnet Labs Unbound, up to and including version 1.16.1 is vulnerable to a novel type of the 'ghost domain names' attack. The vulnerability work...

Fedora: Security Advisory for unbound (FEDORA-2022-164cf7837e)

The remote host is missing an update for the Copyright C 2022 Greenbone Networks GmbH Some text descriptions might be excerpted from a referenced sources, and are Copyright C by the respective right holders. SPDX-License-Identifier: GPL-2.0-or-later This program is free software; you can...

[SECURITY] Fedora 36 Update: unbound-1.16.3-1.fc36

Unbound is a validating, recursive, and caching DNSSEC resolver. The C implementation of Unbound is developed and maintained by NLnet Labs. It is based on ideas and algorithms taken from a java prototype developed by Verisign labs, Nominet, Kirei and ep.net. Unbound is designed as a set of modula...

PT-2022-21443 · Puppet +1 · Puppetlabs-Apt +1

Name of the Vulnerable Software and Affected Versions: puppetlabs-apt versions prior to 9.0.0 Description: Command injection is possible in the puppetlabs-apt module. A malicious actor can exploit this issue if they can provide unsanitized input to the module. This condition is rare in most...

Zinc 跨站脚本漏洞

Zinc is a full-text indexing search engine open sourced by Zinc Labs. Zinc v0.1.9 and later, v0.3.1 and earlier versions have a cross-site scripting vulnerability that could be exploited by attackers to obtain sensitive information such as user credentials...

Sensio Labs Twig Path Traversal Vulnerability

Sensio Labs Twig is a PHP templating engine from Sensio Labs, France, which supports custom tags and filters and creates DSLs. A path traversal vulnerability exists in Sensio Labs Twig 1.0.0 and later, versions prior to 1.44.7, 2.0.0 and later, versions prior to 2.15.3, and 3.0.0 and later,...

[SECURITY] Fedora 37 Update: unbound-1.16.3-1.fc37

Unbound is a validating, recursive, and caching DNSSEC resolver. The C implementation of Unbound is developed and maintained by NLnet Labs. It is based on ideas and algorithms taken from a java prototype developed by Verisign labs, Nominet, Kirei and ep.net. Unbound is designed as a set of modula...

TensorFlow vulnerable to `CHECK` fail in `Save` and `SaveSlices`

Impact If Save or SaveSlices is run over tensors of an unsupported dtype, it results in a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf filename = tf.constant"" tensornames = tf.constant"" Save data = tf.casttf.random.uniformshape=1,...

TensorFlow vulnerable to `CHECK` fail in `LRNGrad`

Impact If LRNGrad is given an outputimage input tensor that is not 4-D, it results in a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf depthradius = 1 bias = 1.59018219 alpha = 0.117728651 beta = 0.404427052 inputgrads = tf.random.uniformshape=4,...

TensorFlow vulnerable to segfault in `RaggedBincount`

Impact If RaggedBincount is given an empty input tensor splits, it results in a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf binaryoutput = True splits = tf.random.uniformshape=0, minval=-10000, maxval=10000, dtype=tf.int64, seed=-7430 values =...

TensorFlow vulnerable to segfault in `SparseBincount`

Impact If SparseBincount is given inputs for indices, values, and denseshape that do not make a valid sparse tensor, it results in a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf binaryoutput = True indices = tf.random.uniformshape=, minval=-10000...

TensorFlow vulnerable to `CHECK` fail in `FractionalMaxPoolGrad`

Impact FractionalMaxPoolGrad validates its inputs with CHECK failures instead of with returning errors. If it gets incorrectly sized inputs, the CHECK failure can be used to trigger a denial of service attack: python import tensorflow as tf overlapping = True originput = tf.constant.453409232,...

TensorFlow vulnerable to segfault in `QuantizeDownAndShrinkRange`

Impact If QuantizeDownAndShrinkRange is given nonscalar inputs for inputmin or inputmax, it results in a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf outtype = tf.quint8 input = tf.constant1, shape=3, dtype=tf.qint32 inputmin = tf.constant,...

TensorFlow vulnerable to segfault in `QuantizedMatMul`

Impact If QuantizedMatMul is given nonscalar input for: - mina - maxa - minb - maxb It gives a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf Toutput = tf.qint32 transposea = False transposeb = False Tactivation = tf.quint8 a = tf.constant7,...

TensorFlow vulnerable to segfault in `QuantizedBiasAdd`

Impact If QuantizedBiasAdd is given mininput, maxinput, minbias, maxbias tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf outtype = tf.qint32 input = tf.constant85,170,255, shape=3, dtype=tf.quint8 bias =...

TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVars`

Impact If FakeQuantWithMinMaxVars is given min or max tensors of a nonzero rank, it results in a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf numbits = 8 narrowrange = False inputs = tf.constant0, shape=2,3, dtype=tf.float32 min = tf.constant0,...

TensorFlow vulnerable to segfault in `QuantizedInstanceNorm`

Impact If QuantizedInstanceNorm is given xmin or xmax tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf outputrangegiven = False givenymin = 0 givenymax = 0 varianceepsilon = 1e-05 minseparation = 0.001 x =...