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88 lines
2.6 KiB
Markdown
88 lines
2.6 KiB
Markdown
# Second-Order SQL Injection - API Reference
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## Attack Overview
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Second-order SQL injection occurs when user-supplied data is stored in a database and later incorporated into SQL queries without sanitization. Unlike first-order SQLi, the injection payload is not executed at the point of input but at a secondary execution point.
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**Attack Flow:**
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1. Attacker submits payload via input form (e.g., username registration)
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2. Application safely stores the payload in database (parameterized INSERT)
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3. Application later retrieves the stored value
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4. Stored value is concatenated into a new SQL query without sanitization
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5. Injection executes at the secondary query point
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## SQL Injection Patterns
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| Pattern | Example | Risk |
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|---------|---------|------|
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| UNION SELECT | `' UNION SELECT password FROM users--` | Data exfiltration |
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| Tautology | `' OR 1=1--` | Authentication bypass |
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| Stacked queries | `'; DROP TABLE users--` | Data destruction |
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| Time-based blind | `'; WAITFOR DELAY '0:0:5'--` | Data extraction |
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| Error-based | `' AND CONVERT(int, @@version)--` | Information disclosure |
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## Code Sink Patterns (Vulnerable Code)
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### Python (dangerous)
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```python
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cursor.execute(f"SELECT * FROM orders WHERE user='{username}'")
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cursor.execute("SELECT * FROM orders WHERE user='%s'" % username)
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```
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### Python (safe - parameterized)
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```python
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cursor.execute("SELECT * FROM orders WHERE user=%s", (username,))
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```
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### PHP (dangerous)
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```php
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$query = "SELECT * FROM orders WHERE user='" . $username . "'";
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```
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## Database Dump Format
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The agent expects JSON format for database analysis:
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```json
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{
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"users": [
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{"id": 1, "username": "admin", "email": "admin@example.com"},
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{"id": 2, "username": "' UNION SELECT 1,2,3--", "email": "test@test.com"}
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],
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"comments": [
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{"id": 1, "body": "Normal comment"},
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{"id": 2, "body": "'; DROP TABLE users--"}
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]
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}
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```
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## Data Flow Tracing
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The agent correlates stored payloads with code sinks by matching table/column names referenced in source code queries against tables containing injection payloads.
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## Prevention
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- Use parameterized queries (prepared statements) everywhere
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- Apply output encoding when using stored data in queries
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- Implement stored procedure-based data access
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- Use an ORM that auto-parameterizes queries
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- Validate data on both input AND retrieval from database
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## Output Schema
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```json
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{
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"report": "second_order_sql_injection",
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"total_findings": 15,
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"stored_payloads": 5,
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"code_sinks": 8,
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"confirmed_attack_paths": 2,
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"findings": [{"type": "confirmed_attack_path", "severity": "critical"}]
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}
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```
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## CLI Usage
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```bash
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python agent.py --db-dump database.json --source /app/src --output report.json
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```
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