CVE-2020-18106
📋 TL;DR
CVE-2020-18106 is a critical SQL injection vulnerability in WMS v1.0 where the 'id' GET parameter is not properly filtered. This allows attackers to execute arbitrary SQL commands against the database. Any organization running WMS v1.0 is affected.
💻 Affected Systems
- WMS (Web Management System)
📦 What is this software?
Wms by Wms Project
⚠️ Risk & Real-World Impact
Worst Case
Complete database compromise including data theft, data manipulation, authentication bypass, and potential remote code execution on the database server.
Likely Case
Data exfiltration, privilege escalation, and unauthorized access to sensitive information stored in the database.
If Mitigated
Limited impact with proper input validation and parameterized queries preventing SQL injection.
🎯 Exploit Status
SQL injection vulnerabilities are well-understood and easily weaponized. The GitHub issue shows proof of concept exploitation.
🛠️ Fix & Mitigation
✅ Official Fix
Patch Version: Unknown
Vendor Advisory: https://github.com/FeMiner/wms/issues/7
Restart Required: No
Instructions:
No official patch available. Implement input validation and parameterized queries in the application code.
🔧 Temporary Workarounds
Web Application Firewall (WAF)
allDeploy a WAF with SQL injection protection rules to filter malicious requests.
Input Validation Filter
allImplement server-side input validation to sanitize the 'id' parameter before processing.
🧯 If You Can't Patch
- Isolate the WMS system from the internet and restrict access to authorized users only.
- Implement database-level controls: use least privilege accounts, enable database auditing, and monitor for suspicious queries.
🔍 How to Verify
Check if Vulnerable:
Test the 'id' parameter with SQL injection payloads like: ' OR '1'='1 or '; SELECT SLEEP(5);--Check Version:
Check application version in admin interface or configuration files.Verify Fix Applied:
Verify that SQL injection payloads no longer execute and return appropriate error messages or are blocked.📡 Detection & Monitoring
Log Indicators:
- Unusual SQL error messages in application logs
- Multiple failed login attempts with SQL payloads
- Database queries with unusual patterns or syntax
Network Indicators:
- HTTP requests containing SQL keywords in GET parameters
- Unusual database connection patterns from the application server
SIEM Query:
source="web_logs" AND ("UNION SELECT" OR "OR '1'='1" OR "';--" OR "sleep(" OR "benchmark(")