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

• 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

Risk Calculation

Risk = Likelihood x Impact

Likelihood Factors (0-9 scale)

| Factor Group | Factor | Description | |-------------|--------|------------| | Threat Agent | Skill Level | How technically skilled is the attacker? | | Threat Agent | Motive | How motivated is the attacker? | | Threat Agent | Opportunity | What resources/access are needed? | | Threat Agent | Size | How large is the potential threat agent group? | | Vulnerability | Ease of Discovery | How easy is it to find the vulnerability? | | Vulnerability | Ease of Exploit | How easy is it to exploit? | | Vulnerability | Awareness | How well known is the vulnerability? | | Vulnerability | Intrusion Detection | How likely is exploitation to be detected? |

Impact Factors (0-9 scale)

| Factor Group | Factor | Description | |-------------|--------|------------| | Technical | Confidentiality | How much data could be disclosed? | | Technical | Integrity | How much data could be corrupted? | | Technical | Availability | How much service could be lost? | | Technical | Accountability | Can actions be traced to attacker? | | Business | Financial Damage | Revenue loss, regulatory fines | | Business | Reputation Damage | Brand trust erosion | | Business | Non-compliance | Regulatory violation exposure | | Business | Privacy Violation | PII/PHI exposure volume |

Risk Matrix

| | Low Impact (0-3) | Medium Impact (3-6) | High Impact (6-9) | |---|---|---|---| | High Likelihood (6-9) | Medium | High | Critical | | Medium Likelihood (3-6) | Low | Medium | High | | Low Likelihood (0-3) | Note | Low | Medium |

Triage Process

Step 1: Categorize by OWASP Top 10

python
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

python
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

python
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

bash
# 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

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 onerror=alert(1)> HTTP/1.1

# DOM-based XSS
GET /page#<img src=x onerror=alert(1)> HTTP/1.1

References

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