Exploiting SQL Injection Vulnerabilities

When to Use

• Testing web application input parameters for SQL injection vulnerabilities during an authorized penetration test
• Validating that parameterized queries and input sanitization are properly implemented across all database interactions
• Demonstrating the business impact of a confirmed SQL injection vulnerability by extracting sensitive data
• Verifying that WAF rules and input validation controls effectively block SQL injection payloads
• Testing stored procedures, dynamic SQL, and ORM bypass scenarios in enterprise applications

Do not use against databases without written authorization, for extracting or exfiltrating actual customer data beyond what is needed for proof of concept, or against production databases where exploitation could corrupt data integrity.

Prerequisites

• Written authorization specifying the target application and permissible level of exploitation (detection only vs. full exploitation)
• Burp Suite Professional configured as an intercepting proxy to capture and modify HTTP requests
• sqlmap installed with current version for automated detection and exploitation
• Knowledge of the target database engine (MySQL, PostgreSQL, MSSQL, Oracle) or ability to fingerprint it
• Test accounts at various privilege levels to test injection in authenticated contexts

Workflow

Step 1: Injection Point Discovery

Identify parameters that interact with the database:

• Map all input vectors: Catalog every parameter in URLs (GET), request bodies (POST), HTTP headers (Cookie, Referer, User-Agent, X-Forwarded-For), and JSON/XML API payloads
• Error-based detection: Inject a single quote (') into each parameter and observe the response. SQL errors (e.g., "You have an error in your SQL syntax", "unterminated quoted string", "ORA-01756") confirm the parameter reaches the database unsanitized.
• Boolean-based detection: Inject ' AND 1=1-- (true condition) and ' AND 1=2-- (false condition). If the responses differ (different content length, different data returned, different HTTP status), the parameter is injectable.
• Time-based detection: Inject '; WAITFOR DELAY '0:0:5'-- (MSSQL), ' AND SLEEP(5)-- (MySQL), or '; SELECT pg_sleep(5)-- (PostgreSQL). A 5-second response delay confirms injection.
• Out-of-band detection: Use payloads that trigger DNS or HTTP requests to a Burp Collaborator domain to confirm injection in scenarios where responses are not directly observable.
• Second-order injection: Test for injection where input is stored and later used in a different SQL query (e.g., username stored at registration, used in a query on the profile page).

Step 2: Database Fingerprinting

Determine the database engine and version to select appropriate exploitation techniques:

• Error-based fingerprinting: Each database produces distinctive error messages. MySQL includes "MySQL", MSSQL mentions "SQL Server", PostgreSQL references "PG", Oracle contains "ORA-".
• Function-based fingerprinting: Inject database-specific functions:
  • MySQL: ' AND VERSION()-- or ' AND @@version--
  • MSSQL: ' AND @@version-- or ' AND DB_NAME()--
  • PostgreSQL: ' AND version()--
  • Oracle: ' AND banner FROM v$version--
• String concatenation differences: MySQL uses CONCAT('a','b') or 'a' 'b', MSSQL uses 'a'+'b', PostgreSQL uses 'a'||'b', Oracle uses 'a'||'b'
• Comment syntax: MySQL supports # and -- , MSSQL uses -- , PostgreSQL uses -- , Oracle uses --

Step 3: Manual Exploitation Techniques

Exploit confirmed injection points using technique-appropriate methods:

• UNION-based extraction: Determine the number of columns with ORDER BY incrementing (' ORDER BY 1--, ' ORDER BY 2--, etc. until an error occurs). Then construct UNION SELECT to extract data:

  ' UNION SELECT NULL,username,password,NULL FROM users--
  

• Error-based extraction (MySQL): Use EXTRACTVALUE or UPDATEXML to force data into error messages:

  ' AND EXTRACTVALUE(1,CONCAT(0x7e,(SELECT @@version),0x7e))--
  

• Blind boolean extraction: Extract data one character at a time by testing character values:

  ' AND SUBSTRING((SELECT password FROM users WHERE username='admin'),1,1)='a'--
  

• Time-based blind extraction: Same character-by-character approach using time delays:

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