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Improper Control of Generation of Code ('Code Injection')...

High severity Unreviewed Published Nov 19, 2025 to the GitHub Advisory Database • Updated Nov 19, 2025

Package

No package listed— Suggest a package

Affected versions

Unknown

Patched versions

Unknown

Description

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

References

Published by the National Vulnerability Database Nov 19, 2025
Published to the GitHub Advisory Database Nov 19, 2025
Last updated Nov 19, 2025

Severity

High

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements None
Privileges Required Low
User interaction None
Vulnerable System Impact Metrics
Confidentiality Low
Integrity High
Availability High
Subsequent System Impact Metrics
Confidentiality High
Integrity High
Availability High

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:L/VI:H/VA:H/SC:H/SI:H/SA:H/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X

EPSS score

Exploit Prediction Scoring System (EPSS)

This score estimates the probability of this vulnerability being exploited within the next 30 days. Data provided by FIRST.
(43rd percentile)

Weaknesses

Improper Control of Generation of Code ('Code Injection')

The product constructs all or part of a code segment using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the syntax or behavior of the intended code segment. Learn more on MITRE.

CVE ID

CVE-2025-10703

GHSA ID

GHSA-xrqq-74w4-x876

Source code

No known source code

Dependabot alerts are not supported on this advisory because it does not have a package from a supported ecosystem with an affected and fixed version.

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