#!/usr/bin/env python3
"""
Exploitability Analyzer - Analyzes CVE exploitability in OpenClaw/NanoClaw deployments

Usage:
    python utils/analyze_exploitability.py --help
    echo '{"cve_id":"CVE-2026-27488","cvss_score":7.3}' | python utils/analyze_exploitability.py --json
    python utils/analyze_exploitability.py --test-cases

Example:
    cat cve-data.json | python utils/analyze_exploitability.py --json
"""

import argparse
import json
import sys
from typing import Any


def parse_cvss_vector(vector_string: str) -> dict[str, str]:
    """
    Parse CVSS v2, v3.0, or v3.1 vector string into components.

    Args:
        vector_string: CVSS vector (e.g., "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H")

    Returns:
        Dictionary of CVSS metrics and values
    """
    if not vector_string:
        return {}

    metrics = {}
    normalized = vector_string.strip()

    # Remove leading CVSS v3.x prefix if present (e.g., "CVSS:3.1/")
    if normalized.startswith("CVSS:3"):
        _, separator, remainder = normalized.partition("/")
        normalized = remainder if separator else ""

    # Remove surrounding parentheses/whitespace used by some CVSS v2 strings.
    normalized = normalized.strip().strip("()").strip()
    if not normalized:
        return metrics

    # Parse all vector formats with shared key/value extraction logic.
    for part in normalized.split("/"):
        if ":" in part:
            key, value = part.split(":", 1)
            metrics[key] = value

    return metrics


def analyze_attack_vector(cvss_metrics: dict[str, str]) -> dict[str, Any]:
    """
    Analyze attack vector from CVSS metrics.

    Args:
        cvss_metrics: Parsed CVSS metrics dictionary

    Returns:
        Dictionary with attack vector analysis
    """
    analysis = {
        "is_network_accessible": False,
        "requires_authentication": True,
        "requires_user_interaction": True,
        "complexity": "unknown"
    }

    # Attack Vector (AV)
    av = cvss_metrics.get("AV", "")
    if av == "N":  # Network
        analysis["is_network_accessible"] = True
    elif av == "A":  # Adjacent Network
        analysis["is_network_accessible"] = True
    elif av in ["L", "P"]:  # Local or Physical
        analysis["is_network_accessible"] = False

    # Privileges Required (PR) / Authentication (AU for v2)
    pr = cvss_metrics.get("PR", cvss_metrics.get("Au", ""))
    if pr in ["N", "NONE"]:
        analysis["requires_authentication"] = False
    elif pr in ["L", "H", "SINGLE", "MULTIPLE"]:
        analysis["requires_authentication"] = True

    # User Interaction (UI)
    ui = cvss_metrics.get("UI", "")
    if ui == "N":  # None
        analysis["requires_user_interaction"] = False
    elif ui == "R":  # Required
        analysis["requires_user_interaction"] = True

    # Attack Complexity (AC)
    ac = cvss_metrics.get("AC", "")
    if ac == "L":
        analysis["complexity"] = "low"
    elif ac in ["M", "H"]:
        analysis["complexity"] = "high"

    return analysis


def detect_exploit_availability(references: list[str]) -> dict[str, Any]:
    """
    Detect if exploits are publicly available based on reference URLs.

    Args:
        references: List of reference URLs

    Returns:
        Dictionary with exploit_available (bool) and exploit_sources (list)
    """
    exploit_indicators = [
        "exploit-db.com",
        "exploit-database",
        "exploitdb",
        "packetstormsecurity.com",
        "packetstorm",
        "github.com/exploit",
        "github.com/poc",
        "github.com/proof-of-concept",
        "metasploit",
        "exploit/",
        "/exploit",
        "/poc",
        "/proof-of-concept",
        "exploitability",
        "exploit-code",
    ]

    exploit_sources = []
    for ref in references:
        ref_lower = ref.lower()
        for indicator in exploit_indicators:
            if indicator in ref_lower:
                exploit_sources.append(ref)
                break

    return {
        "exploit_available": len(exploit_sources) > 0,
        "exploit_sources": exploit_sources
    }


def analyze_exploitability(cve_data: dict[str, Any], check_exploits: bool = False) -> dict[str, Any]:
    """
    Analyze CVE exploitability for OpenClaw/NanoClaw deployments.

    Args:
        cve_data: Dictionary containing CVE information with keys:
                  - cve_id: CVE identifier
                  - cvss_score: CVSS base score (float)
                  - cvss_vector: CVSS vector string (optional)
                  - type: Vulnerability type
                  - description: CVE description text
                  - references: List of reference URLs (optional)
        check_exploits: Whether to check references for exploit availability

    Returns:
        Dictionary with exploitability_score (high/medium/low/unknown) and rationale
    """
    cve_id = cve_data.get("cve_id", "unknown")
    cvss_score = cve_data.get("cvss_score", 0.0)
    cvss_vector = cve_data.get("cvss_vector", "")
    vuln_type = cve_data.get("type", "")
    description = cve_data.get("description", "")
    references = cve_data.get("references", [])

    # Parse CVSS vector if available
    cvss_metrics = parse_cvss_vector(cvss_vector)
    attack_analysis = analyze_attack_vector(cvss_metrics)

    # Initial scoring based on CVSS
    score = "unknown"
    rationale_parts = []

    # CVSS-based baseline
    if cvss_score >= 9.0:
        score = "high"
        rationale_parts.append(f"Critical CVSS score ({cvss_score})")
    elif cvss_score >= 7.0:
        score = "high"
        rationale_parts.append(f"High CVSS score ({cvss_score})")
    elif cvss_score >= 4.0:
        score = "medium"
        rationale_parts.append(f"Medium CVSS score ({cvss_score})")
    elif cvss_score > 0:
        score = "low"
        rationale_parts.append(f"Low CVSS score ({cvss_score})")
    else:
        score = "unknown"
        rationale_parts.append("No CVSS score available")

    # Adjust based on attack vector analysis
    if attack_analysis["is_network_accessible"]:
        if not attack_analysis["requires_authentication"] and not attack_analysis["requires_user_interaction"]:
            # Network accessible, no auth, no user interaction = highly exploitable
            if score == "medium":
                score = "high"
            rationale_parts.append("remotely exploitable without authentication")
        else:
            rationale_parts.append("network accessible")
    else:
        # Local-only vulnerabilities are less critical in agent deployments
        if score == "high":
            score = "medium"
        rationale_parts.append("requires local access")

    # OpenClaw/NanoClaw deployment context - adjust based on vulnerability type
    vuln_type_lower = vuln_type.lower()
    description_lower = description.lower()

    # High-risk vulnerability types in AI agent deployments
    if any(keyword in vuln_type_lower or keyword in description_lower for keyword in [
        "ssrf", "server_side_request_forgery", "server-side request forgery"
    ]):
        # SSRF is critical for agents that make external API calls
        if score != "high" and cvss_score >= 6.0:
            score = "high"
        rationale_parts.append("SSRF affects agents making external requests")

    elif any(keyword in vuln_type_lower or keyword in description_lower for keyword in [
        "path_traversal", "path traversal", "directory traversal", "file_inclusion"
    ]):
        # Path traversal is critical for agents with file system access
        if score != "high" and cvss_score >= 6.0:
            score = "high"
        rationale_parts.append("path traversal affects agents with file access")

    elif any(keyword in vuln_type_lower or keyword in description_lower for keyword in [
        "rce", "remote_code_execution", "remote code execution", "code_injection",
        "command_injection", "command injection", "arbitrary code"
    ]):
        # RCE is always critical regardless of other factors
        score = "high"
        rationale_parts.append("RCE is critical in agent deployments")

    elif any(keyword in vuln_type_lower or keyword in description_lower for keyword in [
        "prototype_pollution", "prototype pollution"
    ]):
        # Prototype pollution in Node.js agents can lead to RCE
        if score == "low":
            score = "medium"
        rationale_parts.append("prototype pollution can escalate in Node.js agents")

    elif any(keyword in vuln_type_lower or keyword in description_lower for keyword in [
        "xss", "cross_site_scripting", "cross-site scripting", "reflected xss", "stored xss"
    ]):
        # XSS is lower risk in headless agent deployments (no browser rendering)
        if score == "high" and not attack_analysis["is_network_accessible"]:
            score = "medium"
        rationale_parts.append("XSS has limited impact in headless agents")

    elif any(keyword in vuln_type_lower or keyword in description_lower for keyword in [
        "sql_injection", "sql injection", "nosql injection"
    ]):
        # SQL injection depends on whether agent uses databases
        if attack_analysis["is_network_accessible"] and not attack_analysis["requires_authentication"]:
            if score == "medium":
                score = "high"
        rationale_parts.append("injection affects agents with database access")

    # Check for exploit availability if requested
    exploit_info = {"exploit_available": False, "exploit_sources": []}
    if check_exploits and references:
        exploit_info = detect_exploit_availability(references)
        if exploit_info["exploit_available"]:
            # Elevate score if public exploits exist
            if score == "low":
                score = "medium"
            elif score == "medium":
                score = "high"
            elif score == "unknown" and cvss_score > 0:
                # If we have some CVSS score but it was unknown, upgrade to at least medium
                score = "medium"

            exploit_count = len(exploit_info["exploit_sources"])
            source_suffix = "s" if exploit_count > 1 else ""
            rationale_parts.append(
                f"public exploit available ({exploit_count} source{source_suffix})"
            )

    # Build rationale string
    rationale = "; ".join(rationale_parts[:5])  # Limit to first 5 parts for context

    result = {
        "cve_id": cve_id,
        "exploitability_score": score,
        "exploitability_rationale": rationale,
        "attack_vector_analysis": attack_analysis
    }

    # Include exploit info if check_exploits was enabled
    if check_exploits:
        result["exploit_detection"] = exploit_info

    return result


def run_test_cases():
    """
    Run comprehensive test cases for attack vector analysis.
    Tests CVSS vector parsing and attack vector analysis logic.
    """
    test_cases = [
        {
            "name": "CVSS 3.1 - Network accessible, no auth, no UI (critical)",
            "cvss_vector": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
            "expected": {
                "is_network_accessible": True,
                "requires_authentication": False,
                "requires_user_interaction": False,
                "complexity": "low"
            }
        },
        {
            "name": "CVSS 3.1 - Network accessible, requires auth",
            "cvss_vector": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
            "expected": {
                "is_network_accessible": True,
                "requires_authentication": True,
                "requires_user_interaction": False,
                "complexity": "low"
            }
        },
        {
            "name": "CVSS 3.1 - Network accessible, requires UI",
            "cvss_vector": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
            "expected": {
                "is_network_accessible": True,
                "requires_authentication": False,
                "requires_user_interaction": True,
                "complexity": "low"
            }
        },
        {
            "name": "CVSS 3.1 - Local access required",
            "cvss_vector": "CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
            "expected": {
                "is_network_accessible": False,
                "requires_authentication": False,
                "requires_user_interaction": False,
                "complexity": "low"
            }
        },
        {
            "name": "CVSS 3.1 - Adjacent network, high auth",
            "cvss_vector": "CVSS:3.1/AV:A/AC:H/PR:H/UI:R/S:U/C:L/I:L/A:L",
            "expected": {
                "is_network_accessible": True,
                "requires_authentication": True,
                "requires_user_interaction": True,
                "complexity": "high"
            }
        },
        {
            "name": "CVSS 3.0 - Physical access required",
            "cvss_vector": "CVSS:3.0/AV:P/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
            "expected": {
                "is_network_accessible": False,
                "requires_authentication": False,
                "requires_user_interaction": False,
                "complexity": "low"
            }
        },
        {
            "name": "CVSS v2 - Network, no auth required",
            "cvss_vector": "(AV:N/AC:L/Au:N/C:C/I:C/A:C)",
            "expected": {
                "is_network_accessible": True,
                "requires_authentication": False,
                "requires_user_interaction": True,  # v2 doesn't have UI, defaults to True
                "complexity": "low"
            }
        },
        {
            "name": "CVSS v2 - Network, single auth",
            "cvss_vector": "AV:N/AC:M/Au:SINGLE/C:P/I:P/A:P",
            "expected": {
                "is_network_accessible": True,
                "requires_authentication": True,
                "requires_user_interaction": True,  # v2 doesn't have UI, defaults to True
                "complexity": "high"
            }
        },
        {
            "name": "CVSS v2 - Local access, multiple auth",
            "cvss_vector": "(AV:L/AC:L/Au:MULTIPLE/C:C/I:C/A:C)",
            "expected": {
                "is_network_accessible": False,
                "requires_authentication": True,
                "requires_user_interaction": True,  # v2 doesn't have UI, defaults to True
                "complexity": "low"
            }
        },
        {
            "name": "Empty CVSS vector",
            "cvss_vector": "",
            "expected": {
                "is_network_accessible": False,
                "requires_authentication": True,
                "requires_user_interaction": True,
                "complexity": "unknown"
            }
        }
    ]

    print("Running attack vector analysis test cases...")
    print("=" * 70)

    passed = 0
    failed = 0

    for i, test in enumerate(test_cases, 1):
        print(f"\nTest {i}/{len(test_cases)}: {test['name']}")
        print(f"  CVSS Vector: {test['cvss_vector']}")

        # Parse CVSS vector and analyze attack vector
        cvss_metrics = parse_cvss_vector(test['cvss_vector'])
        result = analyze_attack_vector(cvss_metrics)

        # Compare with expected results
        test_passed = True
        for key, expected_value in test['expected'].items():
            actual_value = result.get(key)
            if actual_value != expected_value:
                print(f"  ❌ FAILED: {key}")
                print(f"     Expected: {expected_value}")
                print(f"     Got: {actual_value}")
                test_passed = False
                failed += 1
                break

        if test_passed:
            print("  ✓ PASSED")
            passed += 1
        else:
            # Show full result for debugging
            print(f"     Full result: {json.dumps(result, indent=6)}")

    print("\n" + "=" * 70)
    print(f"Test Results: {passed} passed, {failed} failed out of {len(test_cases)} total")

    if failed > 0:
        print("\n❌ Some tests failed!")
        sys.exit(1)
    else:
        print("\n✅ All tests passed!")
        sys.exit(0)


def main():
    parser = argparse.ArgumentParser(
        description="Analyze CVE exploitability for OpenClaw/NanoClaw deployments",
        formatter_class=argparse.RawDescriptionHelpFormatter,
        epilog="""
Examples:
  # Analyze from JSON stdin
  echo '{"cve_id":"CVE-2026-27488","cvss_score":7.3,"type":"ssrf"}' | python utils/analyze_exploitability.py --json

  # Analyze with CVSS vector
  echo '{"cve_id":"CVE-2026-1234","cvss_score":9.8,"cvss_vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H"}' \
    | python utils/analyze_exploitability.py --json

  # Run test cases
  python utils/analyze_exploitability.py --test-cases

  # Parse CVSS vector only
  python utils/analyze_exploitability.py --parse-vector "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H"
"""
    )

    parser.add_argument(
        "--json",
        action="store_true",
        help="Read CVE data from stdin as JSON and output analysis"
    )

    parser.add_argument(
        "--parse-vector",
        type=str,
        metavar="VECTOR",
        help="Parse and display CVSS vector string"
    )

    parser.add_argument(
        "--test-cases",
        action="store_true",
        help="Run built-in test cases to verify analyzer logic"
    )

    parser.add_argument(
        "--check-exploits",
        action="store_true",
        help="Check references for publicly available exploits and adjust score accordingly"
    )

    args = parser.parse_args()

    # Handle --parse-vector
    if args.parse_vector:
        metrics = parse_cvss_vector(args.parse_vector)
        print(json.dumps(metrics, indent=2))
        sys.exit(0)

    # Handle --test-cases
    if args.test_cases:
        run_test_cases()
        sys.exit(0)

    # Handle --json (stdin)
    if args.json:
        try:
            cve_data = json.load(sys.stdin)
        except json.JSONDecodeError as e:
            print(f"Error: Invalid JSON input: {e}", file=sys.stderr)
            sys.exit(1)

        result = analyze_exploitability(cve_data, check_exploits=args.check_exploits)
        print(json.dumps(result, indent=2))
        sys.exit(0)

    # No action specified - show help
    parser.print_help()
    sys.exit(0)


if __name__ == "__main__":
    main()