# SSRF Analysis Report

## 1. Executive Summary

- **Analysis Status:** Complete
- **Key Outcome:** After systematic analysis of all network-accessible endpoints and code paths, **NO Server-Side Request Forgery (SSRF) vulnerabilities were identified** in the MedGuard application.
- **Purpose of this Document:** This report provides comprehensive documentation of the SSRF analysis methodology applied, the components analyzed, and the technical rationale for concluding that the application has no SSRF attack surface.

## 2. Dominant Vulnerability Patterns

### Pattern: No SSRF Attack Surface Exists

**Description:** The MedGuard application is an isolated, database-centric web application with no outbound HTTP request functionality. The application architecture does not include any of the common SSRF sink patterns:

- No HTTP client libraries (requests, urllib, httpx, aiohttp, etc.)
- No URL fetching or external resource loading
- No webhook/callback functionality
- No redirect following with user-controlled URLs
- No file fetching from remote sources
- No image/media processing from URLs
- No link preview or URL unfurling features
- No external API integrations

**Implication:** Without server-side HTTP client functionality or external resource fetching capabilities, there are no code paths where user input could influence outbound HTTP requests made by the server.

**Representative Findings:** N/A - No SSRF vulnerabilities found.

## 3. Strategic Intelligence for Exploitation

### Application Architecture

**HTTP Client Library Analysis:**
- **Libraries Found:** NONE
- **Imports Analyzed:** The application only imports Flask framework components, database ORM (SQLAlchemy), authentication (Flask-Login), and GraphQL (Flask-GraphQL, graphene)
- **Source:** `/app/app.py` lines 1-6

```python
from flask import Flask, request, jsonify, render_template, redirect, url_for
from flask_sqlalchemy import SQLAlchemy
from flask_login import LoginManager, UserMixin, login_user, logout_user, current_user, login_required
from flask_graphql import GraphQLView
import graphene
import os
```

**Request Architecture:**
- The application is entirely **inbound-focused** - it only receives HTTP requests and responds with data from the local SQLite database
- All data flows are: User Browser → Flask Application → SQLite Database
- No reverse flows exist where the server makes outbound HTTP requests based on user input

**Internal Services:**
- Database: In-process SQLite at `/app/instance/prescriptions.db`
- No external service dependencies
- No API integrations
- No third-party webhooks or callbacks

### Route and Endpoint Analysis

**Total Flask Routes:** 5 (all analyzed)

| Route | Method | User Input Parameters | External Requests? |
|-------|--------|----------------------|-------------------|
| `/` | GET | None | No - Internal redirect only |
| `/login` | GET/POST | username, password | No - Database query only |
| `/logout` | GET | None | No - Session termination only |
| `/add_prescription` | GET | None | No - Template rendering only |
| `/view_prescriptions` | GET | None | No - Template rendering only |
| `/api` | GET/POST | GraphQL queries | No - Database operations only |

**GraphQL Operations:** 2 (all analyzed)

| Operation | Type | User Input | External Requests? |
|-----------|------|-----------|-------------------|
| `getPrescriptions` | Query | userId (Int) | No - SQLAlchemy query only |
| `addPrescription` | Mutation | userId (Int), prescriptionDetails (String) | No - Database insert only |

### Redirect Functionality Analysis

**All redirects are hardcoded internal routes:**

```python
# Line 69: Home page redirect
return redirect(url_for('login'))

# Line 82: Post-login redirect  
return redirect(url_for('add_prescription'))

# Line 89: Logout redirect
return redirect(url_for('login'))
```

**Client-side redirect (login.html line 29):**
```javascript
window.location.href = "/add_prescription";
```

**Verdict:** No user input influences redirect destinations. All redirects use Flask's `url_for()` with hardcoded route names.

## 4. Methodology Applied

### 1) HTTP Client Usage Pattern Analysis

**Objective:** Identify all HTTP client libraries and trace data flow from user input to request construction.

**Technique:**
- Searched all Python imports for: requests, urllib, httpx, http.client, aiohttp, socket
- Analyzed all Flask routes for URL parameters, callback URLs, webhook URLs, or file paths
- Examined GraphQL resolvers for external HTTP requests

**Result:** **ZERO HTTP client libraries found.** The application does not make any outbound HTTP requests.

**Supporting Evidence:**
- No `requests` library in requirements.txt or imports
- No `urllib` or `http.client` imports
- No socket programming detected
- GraphQL resolvers only perform local SQLAlchemy queries

### 2) Protocol and Scheme Validation Analysis

**Objective:** Verify protocol allowlisting for any outbound requests.

**Result:** **NOT APPLICABLE** - No outbound request functionality exists to validate.

### 3) Hostname and IP Address Validation Analysis

**Objective:** Verify that requests to internal/private IP ranges are blocked.

**Result:** **NOT APPLICABLE** - No outbound request functionality exists to validate.

### 4) Port Restriction and Service Access Controls Analysis

**Objective:** Verify approved port restrictions and cloud metadata endpoint blocking.

**Result:** **NOT APPLICABLE** - No outbound request functionality exists to validate.

### 5) URL Parsing and Validation Bypass Analysis

**Objective:** Test for URL parsing inconsistencies and redirect following behavior.

**Result:** **NOT APPLICABLE** - No user-controlled URL parameters exist in the application.

**Note:** While redirects exist in the application, they are all hardcoded internal routes using Flask's `url_for()` function:
- No user input in redirect targets
- No external URL redirects
- No redirect following behavior

### 6) Request Modification and Headers Analysis

**Objective:** Verify sensitive header stripping in proxied requests.

**Result:** **NOT APPLICABLE** - No request proxying functionality exists.

### 7) Response Handling and Information Disclosure Analysis

**Objective:** Verify error messages don't leak internal network information.

**Result:** While error message handling was reviewed, no SSRF-related information disclosure was found because no external requests are made.

**Note:** The application does have other security issues (plaintext passwords, GraphQL injection, missing authentication on `/api`) but these are not SSRF vulnerabilities.

### Backward Taint Analysis

**SSRF Sinks from Pre-Reconnaissance:** **ZERO**

The pre-reconnaissance deliverable (Section 10) confirmed that no SSRF sinks exist in the application. This was validated through comprehensive code analysis.

**Taint Analysis Result:** No backward taint analysis was necessary because no SSRF sinks were identified to trace back from.

## 5. Secure by Design: Validated Components

The following components were analyzed and found to have no SSRF attack surface:

| Component/Flow | Endpoint/File Location | Architecture Details | Verdict |
|---|---|---|---|
| User Authentication | `/login` POST endpoint | Accepts username/password JSON, performs SQLAlchemy database query. No external requests. Code: `/app/app.py:71-83` | SAFE - No SSRF attack surface |
| GraphQL Query Resolver | `/api` POST (getPrescriptions) | Accepts userId parameter, performs SQLAlchemy `filter_by()` query. No external requests. Code: `/app/app.py:44-45` | SAFE - No SSRF attack surface |
| GraphQL Mutation Resolver | `/api` POST (addPrescription) | Accepts userId and prescriptionDetails, performs SQLAlchemy insert. No external requests. Code: `/app/app.py:54-58` | SAFE - No SSRF attack surface |
| Internal Redirects | `/`, `/logout` endpoints | Uses Flask `url_for()` with hardcoded route names. No user input in redirect targets. Code: `/app/app.py:69,89` | SAFE - No user-controlled redirects |
| Template Rendering | `/add_prescription`, `/view_prescriptions` | Renders Jinja2 templates with server-side data. No external resource fetching. Code: `/app/app.py:94-103` | SAFE - No SSRF attack surface |
| Database Operations | All SQLAlchemy queries | In-process SQLite database. No network connections. File: `/app/instance/prescriptions.db` | SAFE - No outbound requests |

## 6. Additional Security Observations (Non-SSRF)

While conducting SSRF analysis, the following security issues were observed (these are **NOT** SSRF vulnerabilities but are documented for completeness):

### 6.1 Missing Authentication on GraphQL Endpoint
- **Location:** `/app/app.py:65`
- **Issue:** The `/api` endpoint lacks `@login_required` decorator
- **Impact:** Unauthenticated access to GraphQL queries and mutations
- **Relevant Specialist:** Authorization Analysis Specialist

### 6.2 GraphQL Injection Vulnerability
- **Location:** `/app/templates/add_prescription.html:24`
- **Issue:** String interpolation in GraphQL query construction
- **Impact:** GraphQL injection via `prescriptionDetails` parameter
- **Relevant Specialist:** Injection Analysis Specialist

### 6.3 Hardcoded Secret Key
- **Location:** `/app/app.py:9`
- **Issue:** Flask secret key is hardcoded: `@#$%^R&GYUIUBJIU#@*DF&G*H`
- **Impact:** Session forgery, account takeover
- **Relevant Specialist:** Authentication Analysis Specialist

### 6.4 Plaintext Password Storage
- **Location:** `/app/app.py:76,112,116`
- **Issue:** Passwords stored and compared in plaintext
- **Impact:** Credential theft if database is compromised
- **Relevant Specialist:** Authentication Analysis Specialist

## 7. Conclusion

### Summary of Findings

After comprehensive analysis of all network-accessible endpoints, GraphQL operations, redirect functionality, and external dependencies, **ZERO Server-Side Request Forgery (SSRF) vulnerabilities were identified** in the MedGuard application.

### Technical Rationale

The MedGuard application is fundamentally immune to SSRF attacks because:

1. **No HTTP Client Libraries:** The application does not import or use any libraries capable of making outbound HTTP requests (requests, urllib, httpx, aiohttp, etc.)

2. **No URL Parameters:** No endpoints accept URL parameters, callback URLs, webhook URLs, or file paths that could be used to trigger outbound requests

3. **No External Resource Fetching:** The application does not fetch files, images, XML, or any other resources from external sources

4. **Hardcoded Internal Redirects:** All redirect functionality uses Flask's `url_for()` with hardcoded route names - no user input influences redirect destinations

5. **Database-Only Operations:** All GraphQL resolvers and route handlers only perform local SQLite database operations

6. **No External Dependencies:** The application has no integrations with external APIs, webhooks, or third-party services

### Attack Surface Assessment

**SSRF Attack Surface:** **NONE**

**Externally Exploitable SSRF Vulnerabilities:** **0**

**Risk Level:** **NO RISK** (for SSRF specifically)

### Recommendations

While the application has no SSRF vulnerabilities, the following security issues should be addressed:

1. Add `@login_required` decorator to `/api` GraphQL endpoint
2. Implement GraphQL query variables instead of string interpolation
3. Replace hardcoded secret key with environment variable
4. Implement password hashing (bcrypt, argon2)
5. Add CSRF protection
6. Enable HTTPS/TLS
7. Implement proper authorization checks in GraphQL resolvers

---

**Analysis Completed:** 2025-01-XX  
**Analyst:** SSRF Analysis Specialist  
**Confidence Level:** High - Comprehensive code analysis confirmed zero SSRF attack surface