Performing Web Application Vulnerability Triage

TL;DR

• 目的：Triages web application vulnerability findings from DAST/SAST scanners such as Burp Suite and ZAP, using the OWASP Risk Rating Methodology t…
• 适用：Web 漏洞挖掘（Web目标）
• 输入：目标 URL + 端点/参数清单
• 输出：可复现 POC + 利用步骤
• 红线：仅限授权范围内；扫描限速 -c 10 -rl 10；所有动作记 oplog
• 关联：上游：003-src-session-start → 下游：043-hunt-nosqli, 027-hunt-cors, 028-hunt-csrf

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)

Impact Factors (0-9 scale)

Risk Matrix

Triage Process

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    "A06": "Vulnerable and Outdated Components",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

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

References

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

Validation Criteria

A successful discovery of this vulnerability class must demonstrate:

• POC reproducible against fresh target instance (timestamp documented)
• Impact scope quantified (data leaked / privilege gained / RCE achieved)
• CVSS or business risk score assigned
• Authorization scope documented (B SRC vs target, A 项目 vs 全量)
• No destructive side effects (if RCE, sandboxed proof preferred)
• Affected endpoint clearly identified with full URL/request

If any of these cannot be demonstrated, treat the finding as inconclusive and run 111-fp-check for cross-verification.

Output Format

{
  "vulnerability_type": "<class>",
  "endpoint": "<URL with vulnerable parameter>",
  "poc": "<minimal reproducible payload>",
  "impact": "<data disclosed / privilege / RCE / bypass>",
  "cvss_score": "<0.0-10.0>",
  "remediation": "<concise fix recommendation>"
}

Save findings to share/intel/findings/<target>-<timestamp>.md and follow the report template selected at session start.

Workflow

1. Recon — Identify the target endpoint via 96-osint-methodology or 009-osint-with-spiderfoot
2. Fingerprint — Confirm component/version using 01-component-nday or Burp Suite passive detection
3. Probe — Send payload variations matching the vulnerability class
4. Verify — Run 111-fp-check to confirm with second tool
5. Document — Fill report template (project-pentest / cnvd-common / edusrc / butian)
6. Submit — Manual submission (never auto-submit)

Tools & Systems

• Burp Suite Pro / Community — Intercepting proxy, scanner, and Repeater for manual testing
• OWASP ZAP — Open-source alternative to Burp with active scanner
• sqlmap — Automated SQL injection detection (for hunt-sqli)
• Nuclei — Template-based vulnerability scanner
• ffuf — Fast web fuzzer for endpoint discovery
• curl / wget — Manual HTTP request crafting
• httpx — HTTP probing and fingerprinting

Run all tools with -rate-limit 20 to avoid OPSEC issues. For deeper investigation, prefer manual testing with Burp over automated scanners (lower false-positive rate).