CVE-2018-18864
Cross-Site Scripting (XSS) in Loadbalancer
Executive Summary
CVE-2018-18864 is a critical severity vulnerability affecting appsec. It is classified as Cross-Site Scripting (XSS). 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-2018-18864 is categorized as a critical Cross-Site Scripting (XSS) flaw with a CVSS base score of 9.6. Based on our vulnerability intelligence, this issue occurs when the application fails to securely handle untrusted data boundaries.
Loadbalancer.org Enterprise VA MAX before 8.3.3 has XSS because Apache HTTP Server logs are displayed.
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 | 9.6 (CRITICAL) |
| Vector String | CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H |
| Published | November 20, 2018 |
| Last Modified | November 21, 2024 |
| Related CWEs | CWE-79 |
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-2018-18864
- 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 input (e.g., URL parameter or form field) |
| Vector | Input is reflected in the DOM without sanitization |
| Sink | Browser executes the payload as valid JavaScript |
| Impact | Session hijacking, credential theft, unauthorized actions on behalf of the user |
Vulnerable Code Pattern
// ❌ VULNERABLE: Direct DOM injection
const userComment = urlParams.get('comment');
// Taint sink: innerHTML executes injected scripts
document.getElementById('comments').innerHTML = userComment;
Secure Code Pattern
// ✅ SECURE: Safe DOM manipulation
const userComment = urlParams.get('comment');
// Sanitized binding: textContent escapes HTML entities
document.getElementById('comments').textContent = userComment;
How Precogs Detects This
Precogs AI Analysis Engine maps untrusted input sources directly to sensitive DOM manipulation functions, detecting Cross-Site Scripting (XSS) paths before deployment.