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Vulnerability Database/CVE-2025-12764

CVE-2025-12764: pgAdmin 4 LDAP Injection DoS Vulnerability

CVE-2025-12764 is an LDAP injection vulnerability in pgAdmin 4 that enables attackers to cause denial of service by injecting special characters in usernames. This article covers technical details, affected versions, and mitigation.

Published:

CVE-2025-12764 Overview

CVE-2025-12764 is an LDAP injection vulnerability affecting pgAdmin versions 9.9 and earlier. The flaw exists within the LDAP authentication flow, allowing an attacker to inject special LDAP characters into the username field. This injection causes the Domain Controller/LDAP server and the client to process an unusually large amount of data, resulting in a Denial of Service (DoS) condition.

Critical Impact

Unauthenticated attackers can exploit this LDAP injection vulnerability to cause denial of service by overwhelming the LDAP server and pgAdmin client with excessive data processing during authentication attempts.

Affected Products

  • pgAdmin 4 versions 9.9 and earlier
  • pgAdmin 4 for PostgreSQL (all platforms)

Discovery Timeline

  • 2025-11-13 - CVE-2025-12764 published to NVD
  • 2025-11-19 - Last updated in NVD database

Technical Details for CVE-2025-12764

Vulnerability Analysis

This vulnerability is classified as CWE-90 (Improper Neutralization of Special Elements used in an LDAP Query, or 'LDAP Injection'). The flaw resides in pgAdmin's LDAP authentication mechanism, which fails to properly sanitize user-supplied input before incorporating it into LDAP queries.

When a user attempts to authenticate via LDAP, the username provided is used to construct an LDAP search query. The vulnerable code path does not adequately filter or escape special LDAP metacharacters such as *, (, ), \, and null bytes. An attacker can craft a malicious username containing these special characters to manipulate the LDAP query structure.

The attack is network-accessible without requiring prior authentication or user interaction. While the vulnerability does not directly lead to data confidentiality or integrity compromise, it creates a significant availability impact by exhausting resources on both the LDAP server and the pgAdmin client.

Root Cause

The root cause of CVE-2025-12764 is insufficient input validation and sanitization in pgAdmin's LDAP authentication handler. When processing login requests, the application directly incorporates user-supplied username values into LDAP queries without properly escaping LDAP special characters. This allows an attacker to inject crafted payloads that alter the intended query behavior, forcing the LDAP server to perform resource-intensive operations.

Attack Vector

The attack vector is network-based, targeting the pgAdmin web interface's login functionality when LDAP authentication is enabled. An unauthenticated remote attacker can submit specially crafted username values containing LDAP metacharacters to the authentication endpoint. These injected characters cause the LDAP query to behave unexpectedly, triggering excessive data retrieval or processing that overwhelms both the LDAP server and the pgAdmin client, resulting in denial of service.

The attack does not require any privileges or user interaction, making it particularly dangerous in environments where pgAdmin's login page is exposed to untrusted networks.

Detection Methods for CVE-2025-12764

Indicators of Compromise

  • Unusual or malformed authentication attempts to pgAdmin containing special characters such as *, (, ), \, or null bytes in username fields
  • LDAP server logs showing abnormally large query responses or elevated resource consumption
  • pgAdmin authentication failures coinciding with LDAP server performance degradation
  • Network traffic showing repeated login attempts with varying special character payloads

Detection Strategies

  • Monitor pgAdmin authentication logs for usernames containing LDAP metacharacters (*, (, ), \, NUL)
  • Implement LDAP server query logging and alerting on queries that return unusually large result sets
  • Deploy web application firewall (WAF) rules to detect and block LDAP injection patterns in authentication requests
  • Configure rate limiting on pgAdmin login endpoints to reduce the impact of repeated exploitation attempts

Monitoring Recommendations

  • Enable detailed logging for pgAdmin authentication events and forward logs to a centralized SIEM platform
  • Set up alerts for LDAP server resource exhaustion indicators such as high CPU, memory usage, or query latency spikes
  • Monitor for patterns of failed authentication attempts that may indicate active exploitation
  • Track pgAdmin service availability and configure alerts for unexpected outages or degraded performance

How to Mitigate CVE-2025-12764

Immediate Actions Required

  • Upgrade pgAdmin to a version newer than 9.9 that includes the security fix for this vulnerability
  • If immediate upgrade is not possible, consider temporarily disabling LDAP authentication and using alternative authentication methods
  • Restrict network access to the pgAdmin login interface to trusted IP ranges or internal networks only
  • Implement input validation at the network perimeter using a WAF to filter LDAP injection payloads

Patch Information

The pgAdmin development team has acknowledged this vulnerability in GitHub Issue #9325. Organizations should monitor this issue and the official pgAdmin releases for an updated version containing the security fix. Upgrading to a patched version of pgAdmin 4 beyond version 9.9 is the recommended remediation.

Workarounds

  • Disable LDAP authentication in pgAdmin and use internal or OAuth-based authentication methods until a patch is available
  • Deploy a reverse proxy or WAF in front of pgAdmin to filter login requests containing LDAP metacharacters
  • Restrict access to the pgAdmin web interface using firewall rules to limit exposure to trusted networks only
  • Implement additional monitoring and rate limiting on authentication endpoints to detect and throttle exploitation attempts

Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.

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