# Injection Analysis Report (SQLi, Command Injection, LFI/RFI, SSTI, Path Traversal, Deserialization)

## 1. Executive Summary

- **Analysis Status:** Complete  
- **Key Outcome:** One critical Server-Side Template Injection (SSTI) vulnerability was identified in the `/total_loan_payments` endpoint. This finding has been passed to the exploitation phase via the machine-readable queue at `deliverables/injection_exploitation_queue.json`.  
- **SQL Injection Assessment:** All database operations use SQLAlchemy ORM with parameterized queries. No SQL injection vulnerabilities were found.
- **Command Injection Assessment:** No command execution modules are used in network-accessible code paths. No command injection vulnerabilities were found.
- **LFI/RFI/Path Traversal Assessment:** All template names are hardcoded. No file inclusion or path traversal vulnerabilities were found.
- **Deserialization Assessment:** No dangerous deserialization functions are used. No insecure deserialization vulnerabilities were found.
- **Purpose of this Document:** This report provides the strategic context, dominant patterns, and environmental intelligence necessary to effectively exploit the SSTI vulnerability listed in the queue. It is intended to be read alongside the JSON deliverable.  

## 2. Dominant Vulnerability Patterns

### Pattern 1: Secure-by-Default ORM Usage
- **Description:** The application consistently uses SQLAlchemy ORM methods (`filter_by()`, `query.get()`, attribute assignment) for all database operations. No raw SQL queries, string concatenation, or dynamic query construction was detected across the entire codebase. This architectural pattern provides robust protection against SQL injection attacks through automatic parameterization at the database driver level (PyMySQL).
- **Implication:** SQL injection attack surface is effectively eliminated. All user inputs that flow to database operations are automatically treated as data rather than executable SQL code, regardless of content. The separation of SQL structure from user-supplied values is maintained throughout the execution path from Flask → SQLAlchemy → PyMySQL → MySQL.
- **Representative:** N/A (This is a secure pattern, no vulnerability to reference)

### Pattern 2: Type Coercion as Input Validation
- **Description:** Several endpoints use Flask's `request.args.get(type=int)` or `request.args.get(type=float)` to enforce type constraints at the parameter extraction layer. This pattern acts as a first-line defense by rejecting non-numeric inputs before they reach application logic or template rendering. Examples include the `payment` and `term` parameters in `/total_loan_payments` endpoint.
- **Implication:** Type-based input validation provides strong protection against injection attacks for numeric parameters. String-based payloads (e.g., `{{7*7}}`, `'; DROP TABLE--`) fail type coercion and are rejected before reaching dangerous sinks. However, this pattern does NOT protect string parameters that accept arbitrary values.
- **Representative:** N/A (This is a secure pattern, no vulnerability to reference)

### Pattern 3: F-String Template Embedding (VULNERABLE)
- **Description:** The `/total_loan_payments` endpoint constructs a Jinja2 template using Python f-string interpolation at line 118-120: `f'{{ "loan_principal": "{principal}" }}'`. This pattern embeds user-controlled input directly into the template string BEFORE it is passed to `render_template_string()`. While the endpoint implements a character blacklist filter, it only blocks expression delimiters (`{{`, `}}`) and not statement delimiters (`{%`, `%}`).
- **Implication:** This pattern creates a Server-Side Template Injection vulnerability. An attacker can bypass the incomplete blacklist by using Jinja2 statement syntax (`{% ... %}`) instead of expression syntax (`{{ ... }}`). Once injected, Jinja2 statements execute with the full privileges of the Flask application, enabling Remote Code Execution (RCE), file system access, and configuration disclosure.
- **Representative:** INJ-VULN-001 (SSTI in `/total_loan_payments` - `principal` parameter)

### Pattern 4: Blacklist Filtering Anti-Pattern
- **Description:** The application attempts to sanitize the `principal` parameter using a character blacklist at lines 114-116 of routes.py. The blacklist blocks `{{`, `}}`, `[`, `]`, `_`, and `.` but does not block `{%`, `%}`, or many other Jinja2 syntax elements. This represents a fundamentally flawed security approach where the developer tries to enumerate "bad" inputs rather than defining "good" inputs.
- **Implication:** Blacklist filters are inherently incomplete and bypassable. In complex input spaces like template languages with multiple syntax forms (expressions, statements, comments, filters), it is virtually impossible to enumerate all dangerous patterns. The filter in this application prevents expression-based SSTI but fails to prevent statement-based SSTI.
- **Representative:** INJ-VULN-001 (The blacklist at routes.py:114-116 can be bypassed using `{% %}` syntax)

## 3. Strategic Intelligence for Exploitation

### Defensive Evasion (Input Validation Analysis)

**Character Blacklist in `/total_loan_payments` (routes.py:114-116):**
- **Blocks:** `{{`, `}}`, `[`, `]`, `_`, `.`
- **Does NOT Block:** `{%`, `%}`, `{#`, `#}`, `|`, `(`, `)`, `'`, `"`, `\`, and many other characters
- **Critical Bypass:** The blacklist focuses exclusively on Jinja2 **expression delimiters** (`{{ }}`) while completely ignoring **statement delimiters** (`{% %}`). This creates a trivial bypass opportunity.
- **Additional Constraints:** The blocking of `_` (underscore) and `.` (dot) makes Python object introspection more challenging but not impossible. Jinja2 provides alternative mechanisms such as filters, the `[]` operator (though `[]` is also blocked), and built-in template functions.
- **Recommendation:** Start exploitation with statement-based payloads using `{% %}` syntax. For object introspection, explore Jinja2 filter chains and built-in functions that don't require dots or underscores.

**Type Coercion Protection:**
- The `payment` and `term` parameters use strict type coercion (`type=float`, `type=int`) at the extraction layer (routes.py:106-107).
- These parameters are **not exploitable** for SSTI because non-numeric payloads are rejected before reaching the template renderer.
- Focus exploitation exclusively on the `principal` parameter which uses `type=str` and accepts arbitrary string input.

**Post-Render Validation (Too Late):**
- Lines 125-126 validate the rendered output: `re.match("^[0-9\.]*$", json.loads(rendered)['loan_principal'])`
- This validation occurs AFTER `render_template_string()` executes at line 122.
- **Exploitation Implication:** Any code execution or side effects from SSTI payloads will occur during rendering (line 122), before the validation check runs. However, payloads must ensure the output contains a numeric value to avoid triggering a 400 error response. Append numeric digits (e.g., `1234`) to payloads to satisfy this check.

### SSTI-Based Information Disclosure Potential

**Flask Configuration Object Access:**
- The Jinja2 template context includes Flask's `config` object, which contains sensitive application settings.
- **Accessible via:** `{% if config %}...{% endif %}` or iterating over config items
- **Leakable Secrets:**
  - Flask secret key: `'your_secret_key'` (hardcoded at __init__.py:9) - enables session forgery
  - Database connection string: `mysql+pymysql://root:loan_calculator@db/database` (hardcoded at __init__.py:12) - exposes MySQL root credentials
  - Other configuration values including DEBUG mode, SQLALCHEMY_DATABASE_URI, and environment variables

**Session Object Access:**
- The Jinja2 context includes the `session` object containing the current user's session data
- **Accessible via:** `{% if session %}...{% endif %}`
- **Leakable Data:** Current user's `user_id` from session cookie

**Request Object Access:**
- The `request` object is available in Jinja2 templates
- **Accessible via:** `{% if request %}...{% endif %}`
- **Leakable Data:** HTTP headers, cookies, query parameters, form data, client IP address

**Recommendation:** Use config/session/request object disclosure as initial reconnaissance within SSTI exploitation to gather intelligence before attempting RCE.

### File System Access Potential

**CTF Flag File:**
- According to the reconnaissance report, a CTF flag file exists at `/flag` (injected during Docker build)
- **Exploitation Path:** Jinja2 templates can access Python's file I/O functions through object introspection
- **Constraint:** Direct file access using `open('/flag')` requires bypassing the underscore and dot blocks
- **Bypass Strategy:** Explore Jinja2's template features that provide file access without explicit dots/underscores, or chain filters to reconstruct blocked characters

**Application Source Code:**
- Application code is located at `/app/website/app/` (based on full file paths in reconnaissance)
- Reading source files could reveal additional vulnerabilities or credentials
- Same bypass constraints apply as with flag file access

### Remote Code Execution Potential

**Python Object Introspection:**
- Jinja2 templates can access Python's object model through special attributes like `__class__`, `__base__`, `__subclasses__()`, `__globals__`, `__builtins__`
- **Primary Constraint:** The blacklist blocks `_` (underscore), making direct access to dunder attributes like `__class__` impossible
- **Bypass Strategies:**
  1. Use Jinja2 filters that don't require underscores
  2. Access objects that expose methods without underscores in their names
  3. Leverage Jinja2 built-in tests and filters for object traversal
  4. Use `{}` dict syntax or `()` tuple syntax as starting points instead of `[]` (which is blocked)

**Command Execution Modules:**
- The application itself doesn't import `os`, `subprocess`, or other command execution modules in routes.py
- However, these modules may be accessible through Python's object introspection from within Jinja2
- **Exploitation Path:** Navigate from basic objects (like `()`, `""`, or `{}`) to their parent classes, then to subclasses that provide access to dangerous modules like `os` or `subprocess`

**Exploitation Complexity:** The combination of blocking `_`, `.`, and `[]` significantly increases exploitation difficulty but does not eliminate the vulnerability. Creative use of Jinja2's filter system and built-in functions may still achieve RCE.

### Confirmed Technology Stack

**Application Framework:**
- Flask 3.0.3 (stable release, current as of 2024)
- Jinja2 template engine (Flask default, version not explicitly specified but likely 3.x)
- Python 3 (running in Debian Bullseye container)

**Database:**
- MySQL 5.7.15 (legacy version from 2016)
- Accessed exclusively via SQLAlchemy ORM with parameterized queries
- Connection credentials: `root:loan_calculator`

**WSGI Server:**
- Apache 2.4.65 with mod_wsgi-py3

**Session Management:**
- Flask default signed cookies using itsdangerous library
- Secret key: `'your_secret_key'` (hardcoded, enabling session forgery)

**Payload Targeting:** All SSTI payloads should be crafted for Python 3 + Jinja2 environment. Flask-specific objects (`config`, `session`, `request`) are available in template context.

## 4. Vectors Analyzed and Confirmed Secure

These input vectors were traced from source to sink and confirmed to have robust, context-appropriate defenses. They are **low-priority** for further injection testing.

| **Source (Parameter/Key)** | **Endpoint/File Location** | **Defense Mechanism Implemented** | **Verdict** |
|----------------------------|---------------------------|-----------------------------------|-------------|
| `username` | `POST /login` (routes.py:29) | SQLAlchemy ORM `filter_by()` with automatic parameter binding | SAFE (SQL Injection) |
| `password` | `POST /login` (routes.py:30) | SQLAlchemy ORM `filter_by()` with automatic parameter binding | SAFE (SQL Injection) |
| `name` | `POST /profile` (routes.py:70) | SQLAlchemy ORM attribute assignment with parameterized UPDATE | SAFE (SQL Injection) |
| `lastname` | `POST /profile` (routes.py:71) | SQLAlchemy ORM attribute assignment with parameterized UPDATE | SAFE (SQL Injection) |
| `email` | `POST /profile` (routes.py:72) | SQLAlchemy ORM attribute assignment with parameterized UPDATE | SAFE (SQL Injection) |
| `loan_amount` | `POST /profile` (routes.py:73) | Type coercion (`float()`) + SQLAlchemy ORM attribute assignment | SAFE (SQL Injection) |
| `loan_term_months` | `POST /profile` (routes.py:74) | Type coercion (`int()`) + SQLAlchemy ORM attribute assignment | SAFE (SQL Injection) |
| `monthly_payment` | `POST /profile` (routes.py:75) | Type coercion (`float()`) + SQLAlchemy ORM attribute assignment | SAFE (SQL Injection) |
| `payment` | `GET /total_loan_payments` (routes.py:106) | Type coercion (`type=float`) + passed as template variable (not embedded in template string) | SAFE (SSTI, SQL Injection) |
| `term` | `GET /total_loan_payments` (routes.py:107) | Type coercion (`type=int`) + passed as template variable (not embedded in template string) | SAFE (SSTI, SQL Injection) |

**Summary of Secure Patterns:**

1. **SQL Injection Protection:** All database operations use SQLAlchemy ORM methods exclusively. No raw SQL queries exist in the application. Parameter binding is automatic and consistent across all database interactions.

2. **Template Variable Protection:** The `payment` and `term` parameters in `/total_loan_payments` are passed to `render_template_string()` as template variables (secure method) rather than embedded in the template string via f-string interpolation (insecure method). This distinction is critical for SSTI prevention.

3. **Type Coercion Validation:** Numeric parameters use Flask's built-in type coercion (`type=int`, `type=float`) which rejects non-numeric inputs before they reach application logic. This provides strong first-line defense against string-based injection payloads.

## 5. Analysis Constraints and Blind Spots

### Constraints Encountered During Analysis

**No Dynamic Code Paths:**
- The application has a straightforward, synchronous request-response architecture with no complex asynchronous workflows, background jobs, or message queue processing.
- All injection sources identified in the reconnaissance deliverable were successfully traced from source to sink.
- No unresolved code paths or dynamic route construction mechanisms were encountered.

**Static Analysis Only:**
- This analysis is based entirely on white-box code review. Dynamic testing (fuzzing, payload injection) was not performed as per the methodology (analysis phase precedes exploitation phase).
- Edge cases in SQLAlchemy's ORM parameterization or Jinja2's sandboxing were not validated through live testing.

### Potential Blind Spots

**SQLAlchemy ORM Edge Cases:**
- While SQLAlchemy's parameterization is robust and well-documented, this analysis did not examine:
  - Custom SQL expressions using `text()` or `literal_column()` (none were found, but their absence was not exhaustively verified in all helper functions)
  - Raw SQL in database triggers, stored procedures, or views (database schema was not available for review)
  - SQLAlchemy version-specific vulnerabilities (Flask-SQLAlchemy 3.1.1 is current as of 2024, but zero-day vulnerabilities could exist)

**Jinja2 Template Security:**
- Jinja2's auto-escaping protects against XSS but does not prevent SSTI when `render_template_string()` is used with user input.
- The exact version of Jinja2 in use was not confirmed (likely 3.x based on Flask 3.0.3, but not verified).
- Custom Jinja2 extensions or filters (if any) were not analyzed, though none were detected in the application initialization code.

**Apache mod_wsgi Configuration:**
- The application runs under Apache 2.4.65 with mod_wsgi-py3.
- Potential security controls at the Apache layer (mod_security, request filtering) were not analyzed as part of this code review.
- Wildcard CORS policy (`Access-Control-Allow-Origin: *`) is configured at the Apache level, which could enable CSRF attacks but is outside the scope of injection vulnerability analysis.

**Environment Variables and Runtime Configuration:**
- While hardcoded credentials were identified in `__init__.py`, environment variables or runtime configuration files outside the application code were not analyzed.
- Docker container runtime configuration could potentially introduce additional input vectors (e.g., environment variables exposed to the application).

**Deserialization in Session Management:**
- Flask's signed cookie sessions use the `itsdangerous` library for serialization.
- This library is designed to be safe from deserialization attacks, but this analysis did not verify the specific version in use or examine potential vulnerabilities in the signature verification process.
- Session forgery is possible due to the hardcoded secret key (`'your_secret_key'`), but this is an authentication issue rather than an injection vulnerability.

### Out-of-Scope Elements

**Command Injection via SSTI:**
- While no direct command injection vulnerabilities exist in the application code, command execution can be achieved indirectly by exploiting the SSTI vulnerability in `/total_loan_payments`.
- The ultimate goal of SSTI exploitation often includes RCE, which effectively becomes command injection through a different attack vector.
- This will be explored in the exploitation phase.

**Second-Order Injection:**
- This analysis focused on first-order injection vulnerabilities where user input directly influences dangerous sinks.
- Second-order injection scenarios (where data is stored safely but later retrieved and used unsafely) were not systematically investigated, though the small size of the codebase makes such scenarios unlikely.

**NoSQL, LDAP, XPath, XML Injection:**
- The application uses only MySQL (relational database) with SQLAlchemy ORM.
- No LDAP, XML parsing, XPath queries, or NoSQL databases were detected, so these injection classes were not applicable.

---

## 6. Conclusion

This injection analysis phase identified **one critical vulnerability** (Server-Side Template Injection in `/total_loan_payments`) while confirming that **all SQL-facing operations are secure** due to consistent use of SQLAlchemy ORM parameterization.

**Key Findings:**
1. **SSTI (Critical):** The `principal` parameter can be exploited for RCE by bypassing the incomplete character blacklist using Jinja2 statement syntax (`{% %}`).
2. **SQL Injection (None):** All database operations are protected by SQLAlchemy ORM's automatic parameterization. No raw SQL or string concatenation was detected.
3. **Command Injection (None):** No direct command execution modules are used in network-accessible code. RCE can be achieved indirectly via SSTI exploitation.
4. **LFI/RFI/Path Traversal (None):** All template names are hardcoded. No user-controlled file path operations exist.
5. **Deserialization (None):** No dangerous deserialization functions are used. Session cookies use signed serialization via `itsdangerous` (safe).

The exploitation phase should prioritize weaponizing the SSTI vulnerability to:
- Disclose Flask configuration and database credentials
- Read the CTF flag file at `/flag`
- Achieve Remote Code Execution despite the character blacklist constraints
- Potentially pivot to database access using leaked credentials

**INJECTION ANALYSIS PHASE COMPLETE**