Amazon Redshift vulnerabilities

Unsafe use of Python's eval() on server-received data in the vector_in() function in amazon-redshift-python-driver before 2.1.14 allows a rogue server or man-in-the-middle actor to execute arbitrary code on the client. To remediate this issue, users should upgrade to version 2.1.14.

An issue exists in Amazon Redshift JDBC Driver versions prior to 2.2.2. Under certain conditions, the driver could load and execute arbitrary classes when processing JDBC connection URL parameters. An actor who can influence the connection URL could potentially execute code in the application context, provided a suitable class is available on the application's classpath. To mitigate this issue, users should upgrade to version 2.2.2 or later.

In the Linux kernel, the following vulnerability has been resolved: crypto: algif_aead - Revert to operating out-of-place This mostly reverts commit 72548b093ee3 except for the copying of the associated data. There is no benefit in operating in-place in algif_aead since the source and destination come from different mappings. Get rid of all the complexity added for in-place operation and just copy the AD directly.

Issue summary: Parsing CMS AuthEnvelopedData or EnvelopedData message with maliciously crafted AEAD parameters can trigger a stack buffer overflow. Impact summary: A stack buffer overflow may lead to a crash, causing Denial of Service, or potentially remote code execution. When parsing CMS (Auth)EnvelopedData structures that use AEAD ciphers such as AES-GCM, the IV (Initialization Vector) encoded in the ASN.1 parameters is copied into a fixed-size stack buffer without verifying that its length fits the destination. An attacker can supply a crafted CMS message with an oversized IV, causing a stack-based out-of-bounds write before any authentication or tag verification occurs. Applications and services that parse untrusted CMS or PKCS#7 content using AEAD ciphers (e.g., S/MIME (Auth)EnvelopedData with AES-GCM) are vulnerable. Because the overflow occurs prior to authentication, no valid key material is required to trigger it. While exploitability to remote code execution depends on platform and toolchain mitigations, the stack-based write primitive represents a severe risk. The FIPS modules in 3.6, 3.5, 3.4, 3.3 and 3.0 are not affected by this issue, as the CMS implementation is outside the OpenSSL FIPS module boundary. OpenSSL 3.6, 3.5, 3.4, 3.3 and 3.0 are vulnerable to this issue. OpenSSL 1.1.1 and 1.0.2 are not affected by this issue.

Improper Control of Generation of Code ('Code Injection') vulnerability in Progress DataDirect Connect for JDBC drivers, Progress DataDirect Open Access JDBC driver and Hybrid Data Pipeline allows Remote Code Inclusion. The SpyAttribute connection option implemented by the DataDirect Connect for JDBC drivers, DataDirect Hybrid Data Pipeline JDBC driver and the DataDirect OpenAccess JDBC driver log=(file) construct allows the user to specify an arbitrary file for the JDBC driver to write its log information to.  If an application allows an end user to specify a value for the SpyAttributes connection option then an attacker could cause java script to be written to a log file.  If the log file was in the correct location with the correct extension, an application server could see that log file as a resource to be served.  The attacker could fetch the resource from the server causing the java script to be executed. This issue affects: DataDirect Connect for JDBC for Amazon Redshift: through 6.0.0.001392, fixed in 6.0.0.001541 DataDirect Connect for JDBC for Apache Cassandra: through 6.0.0.000805, fixed in 6.0.0.000833 DataDirect Connect for JDBC for Hive: through 6.0.1.001499, fixed in 6.0.1.001628 DataDirect Connect for JDBC for Apache Impala: through 6.0.0.001155, fixed in 6.0.0.001279 DataDirect Connect for JDBC for Apache SparkSQL: through 6.0.1.001222, fixed in 6.0.1.001344 DataDirect Connect for JDBC Autonomous REST Connector: through 6.0.1.006961, fixed in 6.0.1.007063 DataDirect Connect for JDBC for DB2: through 6.0.0.000717, fixed in 6.0.0.000964 DataDirect Connect for JDBC for Google Analytics 4: through 6.0.0.000454, fixed in 6.0.0.000525 DataDirect Connect for JDBC for Google BigQuery: through 6.0.0.002279, fixed in 6.0.0.002410 DataDirect Connect for JDBC for Greenplum: through 6.0.0.001712, fixed in 6.0.0.001727 DataDirect Connect for JDBC for Informix: through 6.0.0.000690, fixed in 6.0.0.0851 DataDirect Connect for JDBC for Microsoft Dynamics 365: through 6.0.0.003161, fixed in 6.0.0.3198 DataDirect Connect for JDBC for Microsoft SQLServer: through 6.0.0.001936, fixed in 6.0.0.001957 DataDirect Connect for JDBC for Microsoft Sharepoint: through 6.0.0.001559, fixed in 6.0.0.001587 DataDirect Connect for JDBC for MongoDB: through 6.1.0.001654, fixed in 6.1.0.001669 DataDirect Connect for JDBC for MySQL: through 5.1.4.000330, fixed in 5.1.4.000364 DataDirect Connect for JDBC for Oracle Database: through 6.0.0.001747, fixed in 6.0.0.001776 DataDirect Connect for JDBC for Oracle Eloqua: through 6.0.0.001438, fixed in 6.0.0.001458 DataDirect Connect for JDBC for Oracle Sales Cloud: through 6.0.0.001225, fixed in 6.0.0.001316 DataDirect Connect for JDBC for Oracle Service Cloud: through 5.1.4.000298, fixed in 5.1.4.000309 DataDirect Connect for JDBC for PostgreSQL: through 6.0.0.001843, fixed in 6.0.0.001856 DataDirect Connect for JDBC for Progress OpenEdge: through 5.1.4.000187, fixed in 5.1.4.000189 DataDirect Connect for JDBC for Salesforce: through 6.0.0.003020, fixed in 6.0.0.003125 DataDirect Connect for JDBC for SAP HANA: through 6.0.0.000879, product retired DataDirect Connect for JDBC for SAP S/4 HANA: through 6.0.1.001818, fixed in 6.0.1.001858 DataDirect Connect for JDBC for Sybase ASE: through 5.1.4.000161, fixed in 5.1.4.000162 DataDirect Connect for JDBC for Snowflake: through 6.0.1.001821, fixed in 6.0.1.001856 DataDirect Hybrid Data Pipeline Server: through 4.6.2.3309, fixed in 4.6.2.3430 DataDirect Hybrid Data Pipeline JDBC Driver: through 4.6.2.0607, fixed in 4.6.2.1023 DataDirect Hybrid Data Pipeline On Premises Connector: through 4.6.2.1223, fixed in 4.6.2.1339 DataDirect Hybrid Data Pipeline Docker: through 4.6.2.3316, fixed in 4.6.2.3430 DataDirect OpenAccess JDBC Driver: through 8.1.0.0177, fixed in 8.1.0.0183 DataDirect OpenAccess JDBC Driver: through 9.0.0.0019, fixed in 9.0.0.0022

Improper Control of Generation of Code ('Code Injection') vulnerability in Progress DataDirect Connect for JDBC drivers, Progress DataDirect Open Access JDBC driver and Hybrid Data Pipeline allows Remote Code Inclusion. The SpyAttribute connection option implemented by the DataDirect Connect for JDBC drivers, DataDirect Hybrid Data Pipeline JDBC driver and the DataDirect OpenAccess JDBC driver supports an undocumented syntax construct for the option value that if discovered can be used by an attacker. If an application allows an end user to specify a value for the SpyAttributes connection option then an attacker can use the undocumented syntax to cause the driver to load an arbitrary class on the class path and execute a constructor on that class.   This issue affects: DataDirect Connect for JDBC for Amazon Redshift: through 6.0.0.001392, fixed in 6.0.0.001541 DataDirect Connect for JDBC for Apache Cassandra: through 6.0.0.000805, fixed in 6.0.0.000833 DataDirect Connect for JDBC for Hive: through 6.0.1.001499, fixed in 6.0.1.001628 DataDirect Connect for JDBC for Apache Impala: through 6.0.0.001155, fixed in 6.0.0.001279 DataDirect Connect for JDBC for Apache SparkSQL: through 6.0.1.001222, fixed in 6.0.1.001344 DataDirect Connect for JDBC Autonomous REST Connector: through 6.0.1.006961, fixed in 6.0.1.007063 DataDirect Connect for JDBC for DB2: through 6.0.0.000717, fixed in 6.0.0.000964 DataDirect Connect for JDBC for Google Analytics 4: through 6.0.0.000454, fixed in 6.0.0.000525 DataDirect Connect for JDBC for Google BigQuery: through 6.0.0.002279, fixed in 6.0.0.002410 DataDirect Connect for JDBC for Greenplum: through 6.0.0.001712, fixed in 6.0.0.001727 DataDirect Connect for JDBC for Informix: through 6.0.0.000690, fixed in 6.0.0.0851 DataDirect Connect for JDBC for Microsoft Dynamics 365: through 6.0.0.003161, fixed in 6.0.0.3198 DataDirect Connect for JDBC for Microsoft SQLServer: through 6.0.0.001936, fixed in 6.0.0.001957 DataDirect Connect for JDBC for Microsoft Sharepoint: through 6.0.0.001559, fixed in 6.0.0.001587 DataDirect Connect for JDBC for MongoDB: through 6.1.0.001654, fixed in 6.1.0.001669 DataDirect Connect for JDBC for MySQL: through 5.1.4.000330, fixed in 5.1.4.000364 DataDirect Connect for JDBC for Oracle Database: through 6.0.0.001747, fixed in 6.0.0.001776 DataDirect Connect for JDBC for Oracle Eloqua: through 6.0.0.001438, fixed in 6.0.0.001458 DataDirect Connect for JDBC for Oracle Sales Cloud: through 6.0.0.001225, fixed in 6.0.0.001316 DataDirect Connect for JDBC for Oracle Service Cloud: through 5.1.4.000298, fixed in 5.1.4.000309 DataDirect Connect for JDBC for PostgreSQL: through 6.0.0.001843, fixed in 6.0.0.001856 DataDirect Connect for JDBC for Progress OpenEdge: through 5.1.4.000187, fixed in 5.1.4.000189 DataDirect Connect for JDBC for Salesforce: through 6.0.0.003020, fixed in 6.0.0.003125 DataDirect Connect for JDBC for SAP HANA: through 6.0.0.000879, product retired DataDirect Connect for JDBC for SAP S/4 HANA: through 6.0.1.001818, fixed in 6.0.1.001858 DataDirect Connect for JDBC for Sybase ASE: through 5.1.4.000161, fixed in 5.1.4.000162 DataDirect Connect for JDBC for Snowflake: through 6.0.1.001821, fixed in 6.0.1.001856 DataDirect Hybrid Data Pipeline Server: through 4.6.2.3309, fixed in 4.6.2.3430 DataDirect Hybrid Data Pipeline JDBC Driver: through 4.6.2.0607, fixed in 4.6.2.1023 DataDirect Hybrid Data Pipeline On Premises Connector: through 4.6.2.1223, fixed in 4.6.2.1339 DataDirect Hybrid Data Pipeline Docker: through 4.6.2.3316, fixed in 4.6.2.3430 DataDirect OpenAccess JDBC Driver: through 8.1.0.0177, fixed in 8.1.0.0183 DataDirect OpenAccess JDBC Driver: through 9.0.0.0019, fixed in 9.0.0.0022

Dataease is an open source data analytics and visualization platform. In Dataease versions up to 2.10.12 the H2 data source implementation (H2.java) does not verify that a provided JDBC URL starts with jdbc:h2. This lack of validation allows a crafted JDBC configuration that substitutes the Amazon Redshift driver and leverages the socketFactory and socketFactoryArg parameters to invoke org.springframework.context.support.FileSystemXmlApplicationContext or ClassPathXmlApplicationContext with an attacker‑controlled remote XML resource, resulting in remote code execution. Versions up to and including 2.10.12 are affected. The issue is fixed in version 2.10.13. Updating to version 2.10.13 or later is the recommended remediation. No known workarounds exist.

When the Amazon Redshift Python Connector is configured with the BrowserAzureOAuth2CredentialsProvider plugin, the driver skips the SSL certificate validation step for the Identity Provider. An insecure connection could allow an actor to intercept the token exchange process and retrieve an access token. This issue has been addressed in driver version 2.1.7. Users should upgrade to address this issue and ensure any forked or derivative code is patched to incorporate the new fixes.

DataEase is an open-source BI tool alternative to Tableau. Prior to version 2.10.9, authenticated users can complete RCE through the backend JDBC link. This issue has been patched in version 2.10.9.

A SQL injection in the Amazon Redshift ODBC Driver v2.1.5.0 (Windows or Linux) allows a user to gain escalated privileges via the SQLTables or SQLColumns Metadata APIs. Users are recommended to upgrade to the driver version 2.1.6.0 or revert to driver version 2.1.4.0.

A SQL injection in the Amazon Redshift Python Connector v2.1.4 allows a user to gain escalated privileges via the get_schemas, get_tables, or get_columns Metadata APIs. Users are recommended to upgrade to the driver version 2.1.5 or revert to driver version 2.1.3.

A SQL injection in the Amazon Redshift JDBC Driver in v2.1.0.31 allows a user to gain escalated privileges via the getSchemas, getTables, or getColumns Metadata APIs. Users should upgrade to the driver version 2.1.0.32 or revert to driver version 2.1.0.30.

The Amazon JDBC Driver for Redshift is a Type 4 JDBC driver that provides database connectivity through the standard JDBC application program interfaces (APIs) available in the Java Platform, Enterprise Editions. Prior to version 2.1.0.28, SQL injection is possible when using the non-default connection property `preferQueryMode=simple` in combination with application code which has a vulnerable SQL that negates a parameter value. There is no vulnerability in the driver when using the default, extended query mode. Note that `preferQueryMode` is not a supported parameter in Redshift JDBC driver, and is inherited code from Postgres JDBC driver. Users who do not override default settings to utilize this unsupported query mode are not affected. This issue is patched in driver version 2.1.0.28. As a workaround, do not use the connection property `preferQueryMode=simple`. (NOTE: Those who do not explicitly specify a query mode use the default of extended query mode and are not affected by this issue.)

DataEase is an open source data visualization analysis tool. In Dataease users are normally allowed to modify data and the data sources are expected to properly sanitize data. The AWS redshift data source does not provide data sanitization which may lead to remote code execution. This vulnerability has been fixed in v1.18.5. Users are advised to upgrade. There are no known workarounds for this vulnerability.

In Amazon AWS Redshift JDBC Driver (aka amazon-redshift-jdbc-driver or redshift-jdbc42) before 2.1.0.8, the Object Factory does not check the class type when instantiating an object from a class name.