Getting Started with SQLScan — Install, Configure, RunSQLScan is a lightweight, open-source tool designed to detect SQL injection vulnerabilities quickly and reliably in web applications. This guide walks you through installing SQLScan, configuring it for your environment, and running scans effectively — including interpreting results and integrating SQLScan into CI/CD pipelines.
What SQLScan does and when to use it
SQLScan targets common SQL injection patterns by sending crafted payloads to web application inputs and analyzing responses for signs of injection (error messages, unexpected data, timing differences). Use SQLScan for:
- Routine security checks during development and testing.
- Scanning staging or pre-production systems before releases.
- Automated scans in continuous integration (CI) pipelines.
- Triage of reported vulnerabilities to confirm exploitability.
Prerequisites
- A machine running Linux, macOS, or Windows (Windows Subsystem for Linux recommended for Windows).
- Python 3.8+ and pip installed (if SQLScan is a Python tool).
- Basic familiarity with HTTP, URLs, and command-line usage.
- Permission to test the target application (only scan systems you own or have explicit authorization to test).
Installation
Below are two common installation methods: via pip (if SQLScan is published as a Python package) and from source.
Install via pip:
python3 -m pip install sqlscan Install from source:
git clone https://github.com/example/sqlscan.git cd sqlscan python3 -m pip install -r requirements.txt python3 setup.py install Verify the installation:
sqlscan --version You should see the tool version printed if installation succeeded.
Basic usage
Run a simple scan against a single URL:
sqlscan --url "https://example.com/search?q=test" Scan a list of URLs:
sqlscan --input urls.txt --output results.json Common options:
- –url: target URL to scan
- –input: file containing newline-separated URLs
- –output: file path to save results (JSON, XML, or HTML)
- –threads: number of concurrent workers
- –timeout: request timeout in seconds
- –user-agent: set custom User-Agent header
Configuration
SQLScan typically reads a configuration file or accepts command-line flags. Example configuration file (~/.sqlscan/config.yml):
threads: 10 timeout: 10 payloads_file: /usr/local/share/sqlscan/payloads.txt follow_redirects: false verify_ssl: true output_format: json rate_limit: 5 # requests per second Load a custom config:
sqlscan --config ~/.sqlscan/config.yml --input targets.txt Customizing payloads:
- SQLScan ships with a payloads list that includes boolean, error-based, UNION, and time-based payloads.
- Add or remove payloads in the payloads file to tune noise vs. coverage.
- Example payload (time-based): “‘; IF(1=1) WAITFOR DELAY ‘00:00:05’–”
Headers and authentication:
- Use –headers to pass custom headers or session cookies (for authenticated parts).
- For token-based auth: –header “Authorization: Bearer
”
Interpreting results
Output typically includes:
- URL tested
- Parameter name and original value
- Payload used
- Evidence (error messages, response differences, timing anomalies)
- Confidence score (low/medium/high)
- Recommended remediation (sanitization/parameterized queries)
Example JSON snippet:
{ "url": "https://example.com/search?q=test", "parameter": "q", "payload": "' OR '1'='1", "evidence": "SQL syntax error near '1'='1'", "confidence": "high", "recommendation": "Use parameterized queries and input validation." } Prioritize high-confidence findings and verify manually with controlled, safe tests before reporting.
Advanced features
Authentication flows:
- Use session cookies or OAuth tokens for scanning authenticated areas.
- Replay recorded HTTP sessions (HAR files) to scan complex flows.
Crawling and form submission:
- Enable crawler mode to discover parameters on multiple pages.
- Configure form fillers to submit login/search forms with test input.
Rate limiting and stealth:
- Use rate_limit and delay settings to avoid triggering WAFs or overwhelming services.
- Randomize User-Agent and request order to reduce pattern detection.
Plugins and extensibility:
- Write custom detection modules or payload generators if SQLScan supports a plugin API.
- Export findings to SIEMs or issue trackers via webhook integrations.
Integrating into CI/CD
Example GitHub Actions step:
- name: Run SQLScan uses: actions/checkout@v4 - name: Install SQLScan run: python3 -m pip install sqlscan - name: Run scan run: sqlscan --input urls.txt --output sqlscan-results.json --threads 4 - name: Upload results uses: actions/upload-artifact@v4 with: name: sqlscan-results path: sqlscan-results.json Fail builds conditionally:
- Parse results; fail when any high-confidence issue is found.
- Use threshold-based gating (e.g., fail if >2 medium/high issues).
Safe testing practices and legal considerations
- Only scan systems you own or have explicit permission to test.
- Prefer non-production environments for aggressive scans.
- Coordinate with ops teams and schedule scans during maintenance windows.
- Keep a record of scans (scope, time, and authorization) for accountability.
Troubleshooting
- “Connection timed out”: increase –timeout or check network/firewall.
- “403 Forbidden”: try authenticated session or adjust headers; ensure you have permission.
- False positives: manually reproduce with a browser or proxy (Burp/OWASP ZAP) and refine payloads.
Final notes
- Use SQLScan as part of a layered security approach: input validation, parameterized queries, least privilege, and monitoring.
- Regularly update payload lists and the tool itself to catch new variants.