import requests
import json
 
BASE_URL = "https://target-api.example.com/api/v1"
headers = {"Authorization": "Bearer <user_token>", "Content-Type": "application/json"}
 
# Fetch a resource and analyze all returned fields
endpoints_to_test = [
    ("GET", "/users/me", None),
    ("GET", "/users/me/orders", None),
    ("GET", "/products", None),
    ("GET", "/users/me/settings", None),
    ("GET", "/transactions", None),
]
 
for method, path, body in endpoints_to_test:
    resp = requests.request(method, f"{BASE_URL}{path}", headers=headers, json=body)
    if resp.status_code == 200:
        data = resp.json()
        # Recursively extract all field names
        def extract_fields(obj, prefix=""):
            fields = []
            if isinstance(obj, dict):
                for k, v in obj.items():
                    full_key = f"{prefix}.{k}" if prefix else k
                    fields.append(full_key)
                    fields.extend(extract_fields(v, full_key))
            elif isinstance(obj, list) and obj:
                fields.extend(extract_fields(obj[0], f"{prefix}[]"))
            return fields
 
        all_fields = extract_fields(data)
        print(f"\n{method} {path} - {len(all_fields)} fields returned:")
        for f in sorted(all_fields):
            print(f"  {f}")

import re
 
SENSITIVE_PATTERNS = {
    "email": r'[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}',
    "phone": r'(\+?1?\s?\(?\d{3}\)?[\s.-]?\d{3}[\s.-]?\d{4})',
    "ssn": r'\b\d{3}-\d{2}-\d{4}\b',
    "credit_card": r'\b(?:4[0-9]{12}(?:[0-9]{3})?|5[1-5][0-9]{14}|3[47][0-9]{13})\b',
    "password_hash": r'\$2[aby]?\$\d{2}\$[./A-Za-z0-9]{53}',
    "api_key": r'(?:api[_-]?key|apikey)["\s:=]+["\']?([a-zA-Z0-9_\-]{20,})',
    "internal_ip": r'\b(?:10\.\d{1,3}|172\.(?:1[6-9]|2\d|3[01])|192\.168)\.\d{1,3}\.\d{1,3}\b',
    "aws_key": r'AKIA[0-9A-Z]{16}',
    "jwt_token": r'eyJ[A-Za-z0-9_-]+\.eyJ[A-Za-z0-9_-]+\.[A-Za-z0-9_-]+',
    "uuid": r'[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}',
}
 
SENSITIVE_FIELD_NAMES = [
    "password", "password_hash", "secret", "token", "ssn", "social_security",
    "credit_card", "card_number", "cvv", "pin", "private_key", "api_key",
    "internal_id", "debug", "trace", "stack_trace", "created_by_ip",
    "last_login_ip", "salt", "session_id", "refresh_token", "mfa_secret",
    "date_of_birth", "bank_account", "routing_number", "tax_id"
]
 
def scan_response(endpoint, response_text):
    findings = []
    # Check for sensitive data patterns in values
    for pattern_name, pattern in SENSITIVE_PATTERNS.items():
        matches = re.findall(pattern, response_text)
        if matches:
            findings.append({
                "endpoint": endpoint,
                "type": "sensitive_value",
                "pattern": pattern_name,
                "count": len(matches),
                "sample": matches[0][:20] + "..." if len(matches[0]) > 20 else matches[0]
            })
 
    # Check for sensitive field names
    response_lower = response_text.lower()
    for field in SENSITIVE_FIELD_NAMES:
        if f'"{field}"' in response_lower or f"'{field}'" in response_lower:
            findings.append({
                "endpoint": endpoint,
                "type": "sensitive_field",
                "field_name": field
            })
 
    return findings
 
# Scan all endpoint responses
for method, path, body in endpoints_to_test:
    resp = requests.request(method, f"{BASE_URL}{path}", headers=headers, json=body)
    if resp.status_code == 200:
        findings = scan_response(f"{method} {path}", resp.text)
        for f in findings:
            print(f"[FINDING] {f['endpoint']}: {f['type']} - {f.get('pattern', f.get('field_name'))}")

# Fields the UI shows (observed from the frontend application)
ui_displayed_fields = {
    "/users/me": {"name", "email", "avatar_url", "role"},
    "/users/me/orders": {"order_id", "date", "status", "total"},
    "/products": {"id", "name", "price", "image_url", "description"},
}
 
# Fields the API actually returns
for method, path, body in endpoints_to_test:
    resp = requests.request(method, f"{BASE_URL}{path}", headers=headers, json=body)
    if resp.status_code == 200:
        data = resp.json()
        if isinstance(data, list):
            actual_fields = set(data[0].keys()) if data else set()
        elif isinstance(data, dict):
            # Handle paginated responses
            items_key = next((k for k in data if isinstance(data[k], list)), None)
            if items_key and data[items_key]:
                actual_fields = set(data[items_key][0].keys())
            else:
                actual_fields = set(data.keys())
        else:
            continue
 
        expected = ui_displayed_fields.get(path, set())
        excess = actual_fields - expected
        if excess:
            print(f"\n{method} {path} - EXCESS FIELDS (not shown in UI):")
            for field in sorted(excess):
                print(f"  - {field}")

# Many APIs embed full user objects in responses for orders, comments, etc.
endpoints_with_user_objects = [
    "/orders",          # Each order may include full seller/buyer profile
    "/comments",        # Comments may include full author profile
    "/reviews",         # Reviews may expose reviewer details
    "/transactions",    # Transactions may include counterparty info
    "/team/members",    # Team listing may expose excessive member data
]
 
for path in endpoints_with_user_objects:
    resp = requests.get(f"{BASE_URL}{path}", headers=headers)
    if resp.status_code == 200:
        text = resp.text
        # Check for user data leakage in nested objects
        user_fields_found = []
        for field in ["password_hash", "last_login_ip", "mfa_enabled", "phone_number",
                      "date_of_birth", "ssn", "internal_notes", "salary", "address"]:
            if f'"{field}"' in text:
                user_fields_found.append(field)
        if user_fields_found:
            print(f"[EXCESSIVE] {path} exposes user fields: {user_fields_found}")

# GraphQL allows clients to request any available field
GRAPHQL_URL = f"{BASE_URL}/graphql"
 
# Introspection query to discover all fields on User type
introspection = {
    "query": """
    {
      __type(name: "User") {
        fields {
          name
          type {
            name
            kind
          }
        }
      }
    }
    """
}
 
resp = requests.post(GRAPHQL_URL, headers=headers, json=introspection)
if resp.status_code == 200:
    fields = resp.json().get("data", {}).get("__type", {}).get("fields", [])
    print("Available User fields via GraphQL:")
    for f in fields:
        sensitivity = "SENSITIVE" if f["name"] in SENSITIVE_FIELD_NAMES else "normal"
        print(f"  {f['name']} ({f['type']['name']}) [{sensitivity}]")
 
# Try to query sensitive fields
sensitive_query = {
    "query": """
    query {
      users {
        id
        email
        passwordHash
        socialSecurityNumber
        internalNotes
        lastLoginIp
        mfaSecret
        apiKey
      }
    }
    """
}
resp = requests.post(GRAPHQL_URL, headers=headers, json=sensitive_query)
if resp.status_code == 200 and "errors" not in resp.json():
    print("[CRITICAL] GraphQL exposes sensitive user fields without restriction")

# Test for debug information in responses
debug_headers_to_check = [
    "X-Debug-Token", "X-Debug-Info", "Server", "X-Powered-By",
    "X-Request-Id", "X-Correlation-Id", "X-Backend-Server",
    "X-Runtime", "X-Version", "X-Build-Version"
]
 
resp = requests.get(f"{BASE_URL}/users/me", headers=headers)
for h in debug_headers_to_check:
    if h.lower() in {k.lower(): v for k, v in resp.headers.items()}:
        print(f"[INFO LEAK] Header {h}: {resp.headers.get(h)}")
 
# Test error responses for stack traces
error_payloads = [
    ("GET", "/users/invalid-id-format", None),
    ("POST", "/orders", {"invalid": "payload"}),
    ("GET", "/users/-1", None),
    ("GET", "/users/0", None),
]
 
for method, path, body in error_payloads:
    resp = requests.request(method, f"{BASE_URL}{path}", headers=headers, json=body)
    if resp.status_code >= 400:
        text = resp.text.lower()
        if any(kw in text for kw in ["stack trace", "traceback", "at com.", "at org.",
                                      "file \"", "line ", "exception", "sql", "query"]):
            print(f"[DEBUG LEAK] {method} {path} -> {resp.status_code}: Contains stack trace or query info")

## Finding: Excessive Data Exposure in Account and Transaction APIs
 
**ID**: API-DATA-001
**Severity**: High (CVSS 7.1)
**OWASP API**: API3:2023 - Broken Object Property Level Authorization
**Affected Endpoints**:
  - GET /api/v1/accounts
  - GET /api/v1/transactions
  - GET /api/v1/users/me
 
**Description**:
The API returns full database objects to the client, including sensitive fields
that are not displayed in the mobile application UI. The mobile app filters
these fields client-side, but they are fully accessible by intercepting the
API response. This exposes SSN fragments, internal risk scores, and KYC
verification data for any authenticated user.
 
**Excess Fields Discovered**:
- /accounts: routing_number, account_holder_ssn_last4, internal_risk_score,
  kyc_verification_status, linked_external_accounts (18 excess fields total)
- /transactions: merchant_id, terminal_id, authorization_code,
  processor_response (12 excess fields total)
- /users/me: last_login_ip, mfa_backup_codes_remaining, credit_score_band
 
**Impact**:
An authenticated user can extract sensitive financial data, internal risk
assessments, and PII for their own account that the application is not
intended to reveal. Combined with BOLA vulnerabilities, this data could
be extracted for all users.
 
**Remediation**:
1. Implement server-side response filtering using DTOs/view models that only include fields needed by the client
2. Use GraphQL field-level authorization or REST response schemas per endpoint per role
3. Remove sensitive fields from API responses at the serialization layer
4. Implement response schema validation in the API gateway to strip undocumented fields
5. Add automated tests that verify response schemas match documentation