CVE-2019-13413
SQL Injection in The Rencontre plugin before 3
Executive Summary
CVE-2019-13413 is a critical severity vulnerability affecting appsec. It is classified as SQL Injection. Ensure your systems and dependencies are patched immediately to mitigate exposure risks.
Precogs AI Insight
"Precogs AI Analysis Engine identifies this vulnerability class through semantic code analysis powered by Code Property Graph (CPG) technology, performing inter-procedural taint tracking to detect injection flaws, broken authentication, and insecure data flows across your entire codebase."
What is this vulnerability?
CVE-2019-13413 is categorized as a critical SQL Injection flaw with a CVSS base score of 9.8. Based on our vulnerability intelligence, this issue occurs when the application fails to securely handle untrusted data boundaries.
The Rencontre plugin before 3.1.3 for WordPress allows SQL Injection via inc/rencontre_widget.php.
This architectural defect enables adversaries to bypass intended security controls, directly manipulating the application's execution state or data layer. Immediate strategic intervention is required.
Risk Assessment
| Metric | Value |
|---|---|
| CVSS Base Score | 9.8 (CRITICAL) |
| Vector String | CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H |
| Published | July 8, 2019 |
| Last Modified | November 21, 2024 |
| Related CWEs | CWE-89 |
Impact on Systems
✅ Data Exfiltration: Attackers can extract sensitive data from backend databases, configuration files, or internal services.
✅ Authentication Bypass: Exploiting this flaw may allow unauthorized access to protected resources and administrative interfaces.
✅ Lateral Movement: Once initial access is gained, attackers can pivot to internal systems and escalate privileges.
How to Fix and Mitigate CVE-2019-13413
- Apply Vendor Patches: Upgrade affected components to their latest, non-vulnerable versions immediately.
- Implement Input Validation: Ensure all user-supplied data is validated, sanitized, and type-checked before processing.
- Deploy Runtime Protection: Use Precogs continuous monitoring to detect exploitation attempts in real time.
- Audit Dependencies: Review and update all third-party libraries and transitive dependencies.
Defending with Precogs AI
Precogs AI Analysis Engine identifies this vulnerability class through semantic code analysis powered by Code Property Graph (CPG) technology, performing inter-procedural taint tracking to detect injection flaws, broken authentication, and insecure data flows across your entire codebase.
Use Precogs to continuously scan your codebase, binaries, APIs, and infrastructure for this vulnerability class and related attack patterns. Our AI-powered detection engine combines static analysis with threat intelligence to identify exploitable weaknesses before attackers do.
Vulnerability Code Signature
Attack Data Flow
| Stage | Detail |
|---|---|
| Source | User-controlled HTTP request parameter |
| Vector | String concatenation into SQL query string |
| Sink | Database engine executes the malformed query |
| Impact | Full database compromise, unauthorized data modification or exfiltration |
Vulnerable Code Pattern
# ❌ VULNERABLE: Direct string concatenation
def get_user(user_id):
query = "SELECT * FROM users WHERE id = '" + user_id + "'"
cursor.execute(query) # Taint sink: unparameterized query
return cursor.fetchone()
Secure Code Pattern
# ✅ SECURE: Parameterized query
def get_user(user_id):
query = "SELECT * FROM users WHERE id = %s"
cursor.execute(query, (user_id,)) # Sanitized binding
return cursor.fetchone()
How Precogs Detects This
Precogs AI Analysis Engine traces data flow from HTTP request parameters through string concatenation directly into database execution sinks, identifying critical SQL injection vectors via Code Property Graph traversal.