CVE-2025-69662: GeoPandas SQL Injection Vulnerability

CVE-2025-69662 Overview

A SQL injection vulnerability exists in GeoPandas versions prior to v.1.1.2 that allows attackers to obtain sensitive information from PostgreSQL databases. The vulnerability resides in the to_postgis() function, which is commonly used to write GeoDataFrames to PostgreSQL databases. Due to improper input sanitization, malicious actors can craft specially formed inputs that manipulate SQL queries executed against the database backend.

Critical Impact

This vulnerability enables unauthorized extraction of sensitive database information through SQL injection attacks targeting the GeoPandas to_postgis() function, potentially exposing confidential geospatial data and database credentials.

Affected Products

• GeoPandas versions prior to v.1.1.2
• Applications using to_postgis() function with untrusted input
• PostgreSQL databases connected via vulnerable GeoPandas installations

Discovery Timeline

• 2026-01-30 - CVE CVE-2025-69662 published to NVD
• 2026-02-04 - Last updated in NVD database

Technical Details for CVE-2025-69662

Vulnerability Analysis

This SQL injection vulnerability (CWE-89) affects the to_postgis() function in GeoPandas, a popular Python library for working with geospatial data. The function is designed to export GeoDataFrame objects to PostgreSQL databases with PostGIS extensions. When user-controlled input is passed to this function without proper sanitization, an attacker can inject malicious SQL statements that execute against the underlying database.

The vulnerability is particularly dangerous in data pipeline scenarios where external data sources are processed and written to PostgreSQL databases. Applications that accept geospatial data from untrusted sources and persist it using to_postgis() are at risk of information disclosure attacks.

Root Cause

The root cause stems from insufficient input validation and parameterization in the to_postgis() function implementation. User-supplied data passed to the function is not properly escaped or parameterized before being incorporated into SQL statements, allowing attackers to break out of intended query contexts and inject arbitrary SQL commands.

Attack Vector

The attack requires network access and targets applications that use the vulnerable to_postgis() function with externally-provided data. An attacker can exploit this vulnerability by crafting malicious input that, when processed by the function, results in SQL injection. This enables the attacker to extract sensitive information from the PostgreSQL database, including table contents, schema information, and potentially database credentials.

The exploitation does not require authentication or user interaction. The attack exploits the trust boundary between the GeoPandas application and the PostgreSQL database, leveraging the database connection's privileges to access information beyond what the application intends to expose.

For detailed technical analysis of the SQL injection mechanism, refer to the security researcher's blog post documenting this vulnerability.

Detection Methods for CVE-2025-69662

Indicators of Compromise

• Unusual SQL error messages in application logs related to GeoPandas database operations
• Unexpected query patterns in PostgreSQL logs containing UNION, SELECT, or information_schema references
• Database audit logs showing unauthorized data access attempts
• Anomalous data extraction volumes from PostgreSQL databases

Detection Strategies

• Monitor PostgreSQL query logs for SQL injection patterns such as UNION-based attacks, stacked queries, or time-based blind injection attempts
• Implement database activity monitoring to detect unusual data extraction operations
• Review application logs for errors or exceptions originating from to_postgis() function calls
• Deploy web application firewall (WAF) rules to detect SQL injection payloads in incoming requests

Monitoring Recommendations

• Enable PostgreSQL statement logging to capture all queries executed via GeoPandas connections
• Implement alerting on database queries accessing system catalogs or information_schema
• Monitor for abnormal query execution times that may indicate time-based blind SQL injection attempts
• Audit data egress patterns from PostgreSQL databases for signs of bulk data extraction

How to Mitigate CVE-2025-69662

Immediate Actions Required

• Upgrade GeoPandas to version 1.1.2 or later immediately
• Audit all applications using to_postgis() to identify exposure to untrusted input
• Review database access logs for signs of exploitation
• Apply principle of least privilege to database user accounts used by GeoPandas applications

Patch Information

The vulnerability has been addressed in GeoPandas version 1.1.2. Organizations should upgrade to this version or later to remediate the vulnerability. The fix is documented in the GeoPandas Pull Request #3681 which implements proper input sanitization for the to_postgis() function.

Workarounds

• Validate and sanitize all user-supplied input before passing to to_postgis() function
• Implement strict input validation for geospatial data sources at the application boundary
• Use database user accounts with minimal required privileges when connecting GeoPandas to PostgreSQL
• Consider implementing prepared statements or parameterized queries at the application level as an additional defense layer

# Upgrade GeoPandas to patched version
pip install --upgrade geopandas>=1.1.2

# Verify installed version
pip show geopandas | grep Version