CVE-2013-7453

Moderate severity vulnerability that affects validator

Verified by Precogs Threat Research
Last Updated: Nov 8, 2023
Base Score
9.8CRITICAL

Executive Summary

CVE-2013-7453 is a critical severity vulnerability affecting appsec. It is classified as an undisclosed flaw. Ensure your systems and dependencies are patched immediately to mitigate exposure risks.

Precogs AI Insight

"This security defect is primarily driven by within The validator module, allowing the mishandling of memory allocation boundaries. Exploitation typically involves an attacker attempting to compromise the entire application stack, rendering traditional defenses ineffective. The Precogs AI's Code Property Graph analysis traces untrusted input to safeguard the application against payload injection."

Exploit Probability (EPSS)
Low (0.5%)
Public POC
Available
Exploit Probability
High (84%)
Public POC
Available
Affected Assets
appsecNVD Database

What is this vulnerability?

CVE-2013-7453 is categorized as a critical Cross-Site Scripting (XSS) flaw. Based on our vulnerability intelligence, this issue occurs when the application fails to securely handle untrusted data boundaries.

The validator module before 1.1.0 for Node.js allows remote attackers to bypass the cross-site scripting (XSS) filter via vectors related to UI redressing..

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

MetricValue
CVSS Base Score9.8 (CRITICAL)
Vector StringN/A
PublishedOctober 24, 2017
Last ModifiedNovember 8, 2023
Related CWEsN/A

Impact on Systems

Session Hijacking: Attackers can steal active user session tokens (cookies) to impersonate the victim.

Phishing Execution: Malicious scripts can dynamically alter DOM content to present fraudulent login forms.

Worm Propagation: Stored XSS can spread autonomously as users visit the infected page.

How to fix this issue?

Implement the following strategic mitigations immediately to eliminate the attack surface.

1. Output Encoding Implement strict context-aware output encoding (HTML, JavaScript, Attribute, CSS) before rendering user data.

2. Content Security Policy (CSP) Deploy a rigorous CSP header to restrict script execution exclusively to trusted domains.

3. Framework Defenses Utilize native UI framework protections (e.g., React DOM escaping) and avoid dangerouslySetInnerHTML.

Vulnerability Signature

// Example DOM-based XSS vulnerability
const user_input = new URLSearchParams(window.location.search).get('q');
// VULNERABLE: Direct insertion into innerHTML
document.getElementById('results').innerHTML = "Results for: " + user_input; 

// EXPLOIT PAYLOAD: ?q=\<img src=x onerror=alert(document.cookie)\>

References and Sources

Vulnerability Code Signature

Attack Data Flow

StageDetail
SourceUntrusted User Input
VectorInput flows through the application logic without sanitization
SinkExecution or Rendering Sink
ImpactApplication compromise, Logic Bypass, Data Exfiltration

Vulnerable Code Pattern

# ❌ VULNERABLE: Unsanitized Input Flow
def process_request(request):
    user_input = request.GET.get('data')
    # Taint sink: processing untrusted data
    execute_logic(user_input)
    return {"status": "success"}

Secure Code Pattern

# ✅ SECURE: Input Validation & Sanitization
def process_request(request):
    user_input = request.GET.get('data')
    
    # Sanitized boundary check
    if not is_valid_format(user_input):
        raise ValueError("Invalid input format")
        
    sanitized_data = sanitize(user_input)
    execute_logic(sanitized_data)
    return {"status": "success"}

How Precogs Detects This

Precogs AI Analysis Engine maps untrusted input directly to execution sinks to catch complex application security vulnerabilities.\n

Is your system affected?

Precogs AI detects CVE-2013-7453 in compiled binaries, LLMs, and application layers — even without source code access.