CVE-2025-5690: Exposure of Sensitive Information to an Unauthorized Actor in DALIBO PostgreSQL Anonymizer
PostgreSQL Anonymizer v2.0 and v2.1 contain a vulnerability that allows a masked user to bypass the masking rules defined on a table and read the original data using a database cursor or the --insert option of pg_dump. This problem occurs only when dynamic masking is enabled, which is not the default setting. The problem is resolved in version 2.2.1
AI Analysis
Technical Summary
CVE-2025-5690 is a vulnerability identified in DALIBO's PostgreSQL Anonymizer versions 2.0 and 2.1. This tool is designed to anonymize sensitive data within PostgreSQL databases by applying masking rules to protect confidential information. The vulnerability allows a user with masked access privileges to bypass these masking rules and retrieve the original unmasked data. Specifically, the flaw can be exploited by using a database cursor or the --insert option of the pg_dump utility, enabling unauthorized reading of sensitive information. This issue arises only when dynamic masking is enabled, which is not the default configuration, thereby limiting exposure to some extent. The vulnerability has a CVSS v3.1 base score of 6.5, indicating a medium severity level. The attack vector is network-based (AV:N), requires low attack complexity (AC:L), and requires privileges (PR:L) but no user interaction (UI:N). The impact is primarily on confidentiality (C:H), with no impact on integrity or availability. The flaw was addressed in PostgreSQL Anonymizer version 2.2.1, which corrects the masking bypass. No known exploits are currently reported in the wild. This vulnerability is significant because it undermines the core purpose of the anonymizer, potentially exposing sensitive data that organizations rely on for compliance with data protection regulations and privacy standards.
Potential Impact
For European organizations, the exposure of sensitive data due to this vulnerability can have serious consequences. Many European entities use PostgreSQL databases for storing personal and sensitive information, often under strict regulatory frameworks such as GDPR. The ability for a masked user to bypass anonymization and access original data could lead to unauthorized disclosure of personal data, resulting in privacy breaches, regulatory fines, reputational damage, and loss of customer trust. The impact is particularly critical for sectors handling highly sensitive information, such as healthcare, finance, and government services. Since dynamic masking is not enabled by default, the risk is somewhat mitigated; however, organizations that have enabled this feature for enhanced data protection are directly at risk. The vulnerability does not affect data integrity or availability but compromises confidentiality, which is a core requirement under European data protection laws. Additionally, the requirement for some level of privileges means insider threats or compromised accounts could exploit this vulnerability more easily. The absence of known exploits in the wild currently reduces immediate risk but does not eliminate the potential for future attacks.
Mitigation Recommendations
European organizations should immediately verify if they are using PostgreSQL Anonymizer versions 2.0 or 2.1 with dynamic masking enabled. If so, upgrading to version 2.2.1 or later is critical to remediate the vulnerability. Organizations should audit database user privileges to ensure that only necessary users have access to masked data and that privilege escalation paths are closed. Implement strict access controls and monitor database activities for unusual cursor usage or pg_dump operations that could indicate exploitation attempts. Additionally, consider disabling dynamic masking if it is not essential, as this reduces the attack surface. Regularly review and update anonymization policies and test them against bypass techniques. Employ database activity monitoring (DAM) tools to detect anomalous queries or data access patterns. Finally, ensure that incident response plans include procedures for data exposure incidents related to anonymization failures.
Affected Countries
Germany, France, United Kingdom, Netherlands, Sweden, Italy, Spain
CVE-2025-5690: Exposure of Sensitive Information to an Unauthorized Actor in DALIBO PostgreSQL Anonymizer
Description
PostgreSQL Anonymizer v2.0 and v2.1 contain a vulnerability that allows a masked user to bypass the masking rules defined on a table and read the original data using a database cursor or the --insert option of pg_dump. This problem occurs only when dynamic masking is enabled, which is not the default setting. The problem is resolved in version 2.2.1
AI-Powered Analysis
Technical Analysis
CVE-2025-5690 is a vulnerability identified in DALIBO's PostgreSQL Anonymizer versions 2.0 and 2.1. This tool is designed to anonymize sensitive data within PostgreSQL databases by applying masking rules to protect confidential information. The vulnerability allows a user with masked access privileges to bypass these masking rules and retrieve the original unmasked data. Specifically, the flaw can be exploited by using a database cursor or the --insert option of the pg_dump utility, enabling unauthorized reading of sensitive information. This issue arises only when dynamic masking is enabled, which is not the default configuration, thereby limiting exposure to some extent. The vulnerability has a CVSS v3.1 base score of 6.5, indicating a medium severity level. The attack vector is network-based (AV:N), requires low attack complexity (AC:L), and requires privileges (PR:L) but no user interaction (UI:N). The impact is primarily on confidentiality (C:H), with no impact on integrity or availability. The flaw was addressed in PostgreSQL Anonymizer version 2.2.1, which corrects the masking bypass. No known exploits are currently reported in the wild. This vulnerability is significant because it undermines the core purpose of the anonymizer, potentially exposing sensitive data that organizations rely on for compliance with data protection regulations and privacy standards.
Potential Impact
For European organizations, the exposure of sensitive data due to this vulnerability can have serious consequences. Many European entities use PostgreSQL databases for storing personal and sensitive information, often under strict regulatory frameworks such as GDPR. The ability for a masked user to bypass anonymization and access original data could lead to unauthorized disclosure of personal data, resulting in privacy breaches, regulatory fines, reputational damage, and loss of customer trust. The impact is particularly critical for sectors handling highly sensitive information, such as healthcare, finance, and government services. Since dynamic masking is not enabled by default, the risk is somewhat mitigated; however, organizations that have enabled this feature for enhanced data protection are directly at risk. The vulnerability does not affect data integrity or availability but compromises confidentiality, which is a core requirement under European data protection laws. Additionally, the requirement for some level of privileges means insider threats or compromised accounts could exploit this vulnerability more easily. The absence of known exploits in the wild currently reduces immediate risk but does not eliminate the potential for future attacks.
Mitigation Recommendations
European organizations should immediately verify if they are using PostgreSQL Anonymizer versions 2.0 or 2.1 with dynamic masking enabled. If so, upgrading to version 2.2.1 or later is critical to remediate the vulnerability. Organizations should audit database user privileges to ensure that only necessary users have access to masked data and that privilege escalation paths are closed. Implement strict access controls and monitor database activities for unusual cursor usage or pg_dump operations that could indicate exploitation attempts. Additionally, consider disabling dynamic masking if it is not essential, as this reduces the attack surface. Regularly review and update anonymization policies and test them against bypass techniques. Employ database activity monitoring (DAM) tools to detect anomalous queries or data access patterns. Finally, ensure that incident response plans include procedures for data exposure incidents related to anonymization failures.
Affected Countries
For access to advanced analysis and higher rate limits, contact root@offseq.com
Technical Details
- Data Version
- 5.1
- Assigner Short Name
- PostgreSQL
- Date Reserved
- 2025-06-04T18:41:30.661Z
- Cvss Version
- 3.1
- State
- PUBLISHED
Threat ID: 68418437182aa0cae2dcccdf
Added to database: 6/5/2025, 11:49:11 AM
Last enriched: 7/7/2025, 3:56:48 AM
Last updated: 8/4/2025, 4:43:48 PM
Views: 13
Related Threats
CVE-2025-8749: CWE-22 Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal') in Mobile Industrial Robots MiR Robots
MediumCVE-2025-8088: CWE-35 Path traversal in win.rar GmbH WinRAR
HighCVE-2025-8748: CWE-78 Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection') in Mobile Industrial Robots MiR Robots
HighCVE-2025-53606: CWE-502 Deserialization of Untrusted Data in Apache Software Foundation Apache Seata (incubating)
CriticalCVE-2025-48913: CWE-20 Improper Input Validation in Apache Software Foundation Apache CXF
HighActions
Updates to AI analysis are available only with a Pro account. Contact root@offseq.com for access.
External Links
Need enhanced features?
Contact root@offseq.com for Pro access with improved analysis and higher rate limits.