Performing Web Application Vulnerability Triage

Performing Web Application Vulnerability Triage

Overview

Web application vulnerability triage is the process of reviewing findings from DAST (Dynamic Application Security Testing) and SAST (Static Application Security Testing) tools to validate true positives, dismiss false positives, assign risk ratings using the OWASP Risk Rating Methodology, and prioritize remediation. Effective triage reduces alert fatigue and focuses development teams on the vulnerabilities that matter most.

When to Use

Trigger phrases:

• "performing web application vulnerability triage"

• "Triage web application vulnerability findings from DAST/SAST scanners using OWAS"

• When conducting security assessments that involve performing web application vulnerability triage

• When following incident response procedures for related security events

• When performing scheduled security testing or auditing activities

• When validating security controls through hands-on testing

Prerequisites

• DAST scan results (OWASP ZAP, Burp Suite, Acunetix)
• SAST scan results (Semgrep, SonarQube, Checkmarx, Snyk Code)
• Python 3.9+ with requests, beautifulsoup4
• Burp Suite Professional or OWASP ZAP for manual validation
• DefectDojo or similar for finding management

OWASP Risk Rating Methodology

This section covers owasp risk rating methodology for performing web application vulnerability triage.

• Ensure all prerequisites are met before proceeding
• Follow the documented workflow steps in sequence
• Record results and any anomalies encountered during this phase

Risk Calculation

Risk = Likelihood x Impact

Likelihood Factors (0-9 scale)

Impact Factors (0-9 scale)

Risk Matrix

Triage Process

1. Scope the task — define objectives, boundaries, and success criteria
2. Gather information — collect all necessary data and context before proceeding
3. Execute the core workflow — follow the domain-specific steps methodically
4. Validate results — verify outputs against expected outcomes or baselines
5. Document findings — record results, anomalies, and recommendations

Step 1: Categorize by OWASP Top 10

OWASP_TOP_10_2021 = {
    "A01": "Broken Access Control",
    "A02": "Cryptographic Failures",
    "A03": "Injection",
    "A04": "Insecure Design",
    "A05": "Security Misconfiguration",
    "A06": "Vulnerable and Outdated Components",
    "A07": "Identification and Authentication Failures",
    "A08": "Software and Data Integrity Failures",
    "A09": "Security Logging and Monitoring Failures",
    "A10": "Server-Side Request Forgery",
}

CWE_TO_OWASP = {
    "CWE-79": "A03",   # XSS -> Injection
    "CWE-89": "A03",   # SQL Injection
    "CWE-78": "A03",   # OS Command Injection
    "CWE-352": "A01",  # CSRF -> Access Control
    "CWE-22": "A01",   # Path Traversal
    "CWE-200": "A02",  # Information Exposure
    "CWE-327": "A02",  # Weak Cryptography
    "CWE-287": "A07",  # Authentication Issues
    "CWE-918": "A10",  # SSRF
    "CWE-502": "A08",  # Deserialization
    "CWE-611": "A05",  # XXE -> Misconfiguration
}

Step 2: Validate True vs False Positives

def triage_finding(finding):
    """Classify finding as true_positive, false_positive, or needs_review."""
    fp_indicators = [
        "Content-Security-Policy header not set",  # Often informational
        "X-Content-Type-Options header missing",    # Low severity header
        "Cookie without SameSite attribute",        # Context dependent
    ]

    for indicator in fp_indicators:
        if indicator.lower() in finding.get("title", "").lower():
            if finding.get("severity", "").lower() in ("info", "low"):
                return "false_positive", "Common informational finding"

    # Check for confirmed exploitation evidence
    if finding.get("evidence") and finding.get("confidence", "").lower() == "certain":
        return "true_positive", "Scanner confirmed exploitation"

    # SAST findings need manual code review
    if finding.get("source") == "sast":
        if finding.get("cwe") in ["CWE-89", "CWE-78", "CWE-79"]:
            return "needs_review", "Injection finding requires manual code review"

    return "needs_review", "Requires manual validation"

Step 3: Risk Score Calculation

def calculate_risk_score(finding, app_context):
    """Calculate OWASP risk rating for a web application finding."""
    # Likelihood factors
    likelihood = {
        "skill_level": 6 if finding["cwe"] in ["CWE-89", "CWE-79"] else 4,
        "motive": 7,  # Financial gain
        "opportunity": 7 if finding.get("authenticated") == False else 4,
        "size": 9 if finding.get("internet_facing") else 4,
        "ease_of_discovery": 8 if finding.get("scanner_detected") else 5,
        "ease_of_exploit": 7 if finding.get("exploit_available") else 4,
        "awareness": 6,
        "intrusion_detection": 3 if app_context.get("waf_enabled") else 8,
    }

    # Impact factors
    impact = {
        "confidentiality": 9 if "data_exposure" in finding.get("tags", []) else 5,
        "integrity": 9 if finding["cwe"] in ["CWE-89", "CWE-78"] else 4,
        "availability": 7 if "dos" in finding.get("tags", []) else 2,
        "accountability": 3 if app_context.get("logging_enabled") else 7,
        "financial": 7 if app_context.get("processes_payments") else 3,
        "reputation": 6 if app_context.get("customer_facing") else 2,
        "compliance": 8 if app_context.get("pci_scope") else 3,
        "privacy": 9 if app_context.get("handles_pii") else 2,
    }

    likelihood_score = sum(likelihood.values()) / len(likelihood)
    impact_score = sum(impact.values()) / len(impact)
    risk_score = likelihood_score * impact_score

    if risk_score >= 42:
        risk_level = "Critical"
    elif risk_score >= 24:
        risk_level = "High"
    elif risk_score >= 12:
        risk_level = "Medium"
    elif risk_score >= 3:
        risk_level = "Low"
    else:
        risk_level = "Note"

    return {
        "likelihood_score": round(likelihood_score, 1),
        "impact_score": round(impact_score, 1),
        "risk_score": round(risk_score, 1),
        "risk_level": risk_level,
    }

Step 4: Generate Triage Report

# Process DAST/SAST results through triage pipeline
python3 scripts/process.py \
  --input zap_results.json \
  --format zap \
  --app-context app_config.json \
  --output triage_report.json

Manual Validation Techniques

This section covers manual validation techniques for performing web application vulnerability triage.

• Ensure all prerequisites are met before proceeding
• Follow the documented workflow steps in sequence
• Record results and any anomalies encountered during this phase

SQL Injection Validation

# Test parameter with single quote
GET /search?q=test' HTTP/1.1

# Test with boolean-based payload
GET /search?q=test' AND 1=1-- HTTP/1.1
GET /search?q=test' AND 1=2-- HTTP/1.1

# Time-based verification
GET /search?q=test'; WAITFOR DELAY '0:0:5'-- HTTP/1.1

XSS Validation

# Reflected XSS test
GET /search?q=<script>alert(document.domain)</script> HTTP/1.1

# Check if output is encoded
GET /search?q="><img src=x HTTP/1.1

# DOM-based XSS
GET /page#<img src=x HTTP/1.1

When NOT to Use

• You don't have explicit written authorization to test
• Task is about defense/detection, not offense (use detection skills)
• You need to implement security controls (use implementing-* skills)
• Task requires compliance auditing (use auditing-* skills)
• You're investigating an incident (use incident response skills)
• Target is out of scope for your engagement
• Task is about vulnerability scanning only (use scanning tools)

Red Flags

• Performing actions without explicit written authorization from the asset owner
• Testing against production systems without a defined scope and rules of engagement
• Destroying potential evidence during the containment phase
• Failing to document the chain of custody for all collected artifacts
• Communicating incident details over unencrypted or monitored channels

Verification

• All steps executed successfully against a test environment before production use
• Output documented with screenshots or logs demonstrating expected behavior
• Timeline of events reconstructed with corroborating evidence
• Root cause identified and documented with contributing factors
• Post-incident review completed with lessons learned and action items

References

• OWASP Risk Rating Methodology
• OWASP Top 10 2021
• OWASP Testing Guide v4.2
• CWE/SANS Top 25

Process

1. Analyze the task requirements
2. Apply domain expertise
3. Verify output quality

Anti-Rationalization Table