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TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.ReverseSequence` allows for stack overflow and/or `CHECK`-fail based denial of service. The implementation(https://github.com/tensorflow/tensorflow/blob/5b3b071975e01f0d250c928b2a8f901cd53b90a7/tensorflow/core/kernels/reverse_sequence_op.cc#L114-L118) fails to validate that `seq_dim` and `batch_dim` arguments are valid. Negative values for `seq_dim` can result in stack overflow or `CHECK`-failure, depending on the version of Eigen code used to implement the operation. Similar behavior can be exhibited by invalid values of `batch_dim`. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

XWiki Platform is a generic wiki platform offering runtime services for applications built on top of it. Starting in version 2.40m-2 and prior to versions 14.4.8, 14.10.4, and 15.0, any user with view rights on any document can execute code with programming rights, leading to remote code execution by crafting an url with a dangerous payload. The problem has been patched in XWiki 15.0, 14.10.4 and 14.4.8.

Authenticated attackers can exploit a weakness in the XML parser functionality of the Visual Planning application in order to obtain read access to arbitrary files on the application server. Depending on configured access permissions, this vulnerability could be used by an attacker to exfiltrate secrets stored on the local file system. All versions prior to Visual Planning 8 (Build 240207) are affected.

In BIND 9.3.0 -> 9.11.35, 9.12.0 -> 9.16.21, and versions 9.9.3-S1 -> 9.11.35-S1 and 9.16.8-S1 -> 9.16.21-S1 of BIND Supported Preview Edition, as well as release versions 9.17.0 -> 9.17.18 of the BIND 9.17 development branch, exploitation of broken authoritative servers using a flaw in response processing can cause degradation in BIND resolver performance. The way the lame cache is currently designed makes it possible for its internal data structures to grow almost infinitely, which may cause significant delays in client query processing.

By Waqas Ukraine used Clearview AI, now it is up for grabs by US Defense agencies! This is a post from HackRead.com Read the original post: Controversial Clearview AI Added to US Government’s Tech Marketplace

The System Dashboard plugin for WordPress is vulnerable to unauthorized access of data due to a missing capability check on the sd_constants() function hooked via an AJAX action in all versions up to, and including, 2.8.7. This makes it possible for authenticated attackers, with subscriber-level access and above, to retrieve sensitive information such as database credentials.

The System Dashboard plugin for WordPress is vulnerable to unauthorized access of data due to a missing capability check on the sd_php_info() function hooked via an AJAX action in all versions up to, and including, 2.8.7. This makes it possible for authenticated attackers, with subscriber-level access and above, to retrieve sensitive information provided by PHP info.

Tensorflow is an Open Source Machine Learning Framework. The `GraphDef` format in TensorFlow does not allow self recursive functions. The runtime assumes that this invariant is satisfied. However, a `GraphDef` containing a fragment such as the following can be consumed when loading a `SavedModel`. This would result in a stack overflow during execution as resolving each `NodeDef` means resolving the function itself and its nodes. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

The AudioCodes VoIP phones can be managed centrally, whereby configuration files are provided and requested by the phones at a central location. These configuration files can also be provided in encrypted form. This is intended to protect sensitive information within the configuration files from unauthorized access. Due to the use of a hardcoded cryptographic key, an attacker is able to decrypt encrypted configuration files and retrieve sensitive information. Firmware versions greater than or equal to 3.4.8.M4 are affected.

It was found that the fix to address CVE-2021-44228 in Apache Log4j 2.15.0 was incomplete in certain non-default configurations. This could allows attackers with control over Thread Context Map (MDC) input data when the logging configuration uses a non-default Pattern Layout with either a Context Lookup (for example, $${ctx:loginId}) or a Thread Context Map pattern (%X, %mdc, or %MDC) to craft malicious input data using a JNDI Lookup pattern resulting in a denial of service (DOS) attack. Log4j 2.15.0 restricts JNDI LDAP lookups to localhost by default. Note that previous mitigations involving configuration such as to set the system property `log4j2.noFormatMsgLookup` to `true` do NOT mitigate this specific vulnerability. Log4j 2.16.0 fixes this issue by removing support for message lookup patterns and disabling JNDI functionality by default. This issue can be mitigated in prior releases (<2.16.0) by removing the JndiLookup class from the classpath (example: zip -q -d log4j-core-*.jar o...