Blind SQLi
Blind SQL Injection
Blind SQL injection (Blind SQLi) is a type of SQL injection attack where the attacker can exploit the database, but the application does not display the output. Instead, the attacker must "infer" data by sending payloads and observing the application's behavior or responses.
A simple example:
A vulnearble webapp uses an API for its search to return the number of results found.
A user searches for a product, and the application returns with "X products found" without displaying product details.
The application uses the SQL query
SELECT COUNT(*) FROM products WHERE product_name LIKE '%{searchTerm}%'
.An attacker could exploit this by injecting SQL conditions into the
{searchTerm}
.For exmaple, searching for
laptop' AND 1=1-- -
returns "1 product found" and searching forlaptop' AND 1=2-- -
returns "0 products found", this behavior can be an indicator of a potential Blind SQLi vulnerability.
Blind SQLi is more time-consuming than regular SQLi but is just as dangerous. It can lead to:
Sensitive data exposure
Data manipulation
Authentication bypass
Potential discovery of hidden data
Other learning resources:
OWASP: https://owasp.org/www-community/attacks/Blind_SQL_Injection
SQLmap's guide on Blind SQLi: http://sqlmap.org/
PenTestMonkey's Cheat Sheet: http://pentestmonkey.net/cheat-sheet/sql-injection/mysql-sql-injection-cheat-sheet
Writeups:
Checklist:
Test for true/false conditions:
Can you get a "true" condition? E.g.,
' AND 1=1-- -
Can you get a "false" condition? E.g.,
' AND 1=2-- -
Time-based Blind SQLi:
Introduce artificial delays using functions like
SLEEP()
orBENCHMARK()
Measure response times
Error-based Blind SQLi:
Test a divide by zero payload
Can we trigger an error message?
Can we use
CAST()
to trigger an error and view the data?
Content-based Blind SQLi:
Check for changes in page content based on payloads
Out-of-band (OAST):
Can we trigger a DNS query?
Can we append some data to the subdomain of the URL to exfiltrate information?
Binary search based extraction:
Exploit faster by dividing data and querying
Backend specifics:
Are you dealing with MySQL, MSSQL, Oracle, PostgreSQL, SQLite?
Adjust your payloads accordingly
Test with automated tools:
SQLmap with
--technique=B
flag
Encoding and obfuscation:
Test with URL encoding, hex encoding, or other methods to bypass filters
Bypassing filters:
Use comments, spaces, or alternative syntax
Exploitation:
Extract database version, e.g.,
AND (SELECT SUBSTRING(version(),1,1))='5'
Fetch data character by character
Extract data from information_schema
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