Signing cookies is an application security feature that adds a digital signature to cookie data to verify its authenticity and integrity. The signature helps prevent malicious actors from modifying the cookie value, which can lead to security vulnerabilities and exploitation. Apache Hive’s service component accidentally exposes the signed cookie to the end user when there is a mismatch in signature between the current and expected cookie. Exposing the correct cookie signature can lead to further exploitation. The vulnerable CookieSigner logic was introduced in Apache Hive by HIVE-9710 (1.2.0) and in Apache Spark by SPARK-14987 (2.0.0). The affected components are the following: * org.apache.hive:hive-service * org.apache.spark:spark-hive-thriftserver_2.11 * org.apache.spark:spark-hive-thriftserver_2.12

In Apache Linkis <= 1.5.0, a Random string security vulnerability in Spark EngineConn, random string generated by the Token when starting Py4j uses the Commons Lang's RandomStringUtils. Users are recommended to upgrade to version 1.6.0, which fixes this issue.

Apache Airflow Spark Provider, versions before 4.1.3, is affected by a vulnerability that allows an attacker to pass in malicious parameters when establishing a connection giving an opportunity to read files on the Airflow server. It is recommended to upgrade to a version that is not affected.

Improper Input Validation vulnerability in Apache Software Foundation Apache Airflow Spark Provider.This issue affects Apache Airflow Spark Provider: before 4.0.1.

Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection') vulnerability in Apache Airflow Spark Provider, Apache Airflow allows an attacker to read arbtrary files in the task execution context, without write access to DAG files. This issue affects Spark Provider versions prior to 4.0.0. It also impacts any Apache Airflow versions prior to 2.3.0 in case Spark Provider is installed (Spark Provider 4.0.0 can only be installed for Airflow 2.3.0+). Note that you need to manually install the Spark Provider version 4.0.0 in order to get rid of the vulnerability on top of Airflow 2.3.0+ version that has lower version of the Spark Provider installed).