UNION SELECT SQL Injection: A Hands-On Guide

SQL injection is one of the most widely known and exploited vulnerabilities in web applications. At its core, it allows an attacker to interfere with the queries that an application makes to its database. When input from a user is directly inserted into a SQL statement without proper validation or sanitization, the attacker can manipulate the query’s behavior to access or alter data that should not be available.

This vulnerability is especially dangerous because it can often be exploited to gain complete access to a system’s underlying database. Through SQL injection, attackers can retrieve sensitive data such as usernames, passwords, emails, credit card numbers, and even server configuration files. In more severe cases, attackers can write to the database or execute commands on the underlying operating system, depending on permissions.

What makes SQL injection especially challenging for developers is its subtlety. An application might seem to work correctly under normal use, while still being open to abuse by maliciously crafted inputs.

Basic Structure of SQL Injection

To understand the essence of SQL injection, it’s important to first consider how SQL statements are constructed. A common query used in login authentication might look like this:

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SELECT * FROM users WHERE username = ‘admin’ AND password = ‘1234’;

 

If an application builds this query by directly inserting user input into the SQL string, then someone could input:

• username: ‘ OR ‘1’=’1

• password: ‘ OR ‘1’=’1

The resulting SQL statement would be:

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SELECT * FROM users WHERE username = ” OR ‘1’=’1′ AND password = ” OR ‘1’=’1′;

 

Since ‘1’=’1′ always evaluates to true, this query would return all records in the users table, effectively bypassing authentication.

This is the basic principle behind SQL injection. The attacker finds a way to introduce malicious input into an SQL statement and thereby alters the logic of the original query.

What is UNION SELECT?

The UNION operator in SQL is used to combine the results of two or more SELECT queries into a single result set. Each SELECT statement within the UNION must have the same number of columns, and the columns must have compatible data types.

In the context of SQL injection, the UNION operator can be used to retrieve additional data by appending extra SELECT statements to an original query. This makes it a powerful and versatile technique for data exfiltration.

Let’s assume a vulnerable web application has this query:

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SELECT id, name FROM products WHERE category = ‘laptops’;

 

If the application fails to sanitize the input, an attacker might manipulate it like this:

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category=laptops’ UNION SELECT username, password FROM users —

 

Resulting in:

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SELECT id, name FROM products WHERE category = ‘laptops’

UNION SELECT username, password FROM users–‘;

 

The database now combines the product data with sensitive user credentials in a single result set. If the web page displays the result, the attacker will see usernames and passwords in place of product names.

Why UNION SELECT is Popular Among Attackers

Among the various forms of SQL injection, the UNION SELECT method is one of the most straightforward and effective ways to extract data. It’s often used during the early stages of an attack to verify the vulnerability and map out the database structure.

There are several reasons why UNION SELECT is favored:

• It can be easily tested in a web browser or proxy tool like Burp Suite.

• It allows attackers to extract structured and readable results.

• It provides access to multiple tables without needing multiple requests.

• It doesn’t rely on error messages, especially when used with content-based inference.

The attacker simply needs to know how many columns the original query is using and which ones are being displayed on the page.

Preparing a Safe Environment for Testing

To practice and learn how UNION SELECT works in SQL injection, it’s best to use a local testing environment. Never attempt these techniques on live websites or without permission, as that is illegal and unethical.

A common setup involves using:

• XAMPP or MAMP to create a local web server.

• DVWA (Damn Vulnerable Web Application) or bWAPP for vulnerable web applications.

• A browser and a web proxy such as Burp Suite or OWASP ZAP to intercept and modify HTTP requests.

After setting up the environment, you should create some dummy tables, such as users, products, and orders, with sample data. This lets you simulate realistic SQL injection scenarios.

Finding Vulnerable Parameters

Before using UNION SELECT, the attacker must first identify a vulnerable input field. This could be a search box, a login form, a product filter, or any place where user input is included in a database query.

To test whether an input is vulnerable, try submitting a single quote:

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‘

 

If the application returns an SQL error, that is a strong indication that the input is unsanitized and vulnerable. A message like:

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You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version…

 

Suggests that the input is being interpreted directly within the SQL statement.

Once you find a parameter that causes an error, the next step is to test if you can use the UNION SELECT operator.

Determining the Number of Columns

The UNION SELECT statement requires that all SELECT statements return the same number of columns. If they don’t, the database will throw an error. This is why one of the first steps in a UNION SELECT injection is determining the number of columns returned by the original query.

A common method is to use the ORDER BY clause to incrementally guess the number of columns:

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?id=1 ORDER BY 1

?id=1 ORDER BY 2

?id=1 ORDER BY 3

 

Eventually, when the query breaks and returns an error, you have exceeded the column count. For example, if ORDER BY 4 causes an error, the query has three columns.

An alternative method is to incrementally add NULL values to a UNION SELECT query:

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?id=1 UNION SELECT NULL

?id=1 UNION SELECT NULL, NULL

?id=1 UNION SELECT NULL, NULL, NULL

 

When the application responds without error, you have found the correct number of columns.

Identifying Displayed Columns

Even after identifying how many columns are involved, not all columns may be visible on the page. It’s crucial to know which columns are rendered in the HTML output.

To determine this, you can substitute each NULL with a string or number that will show up on the page:

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?id=1 UNION SELECT ‘A’, NULL, NULL

?id=1 UNION SELECT NULL, ‘B’, NULL

?id=1 UNION SELECT NULL, NULL, ‘C’

 

Whichever value that appears on the page indicates which column is visible. This is useful because you will use that column to display sensitive data from other tables.

Extracting Data from Other Tables

Once you know the number of columns and which are displayed, you can begin injecting real data from other tables. For example, if column 2 is visible, you might use:

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?id=1 UNION SELECT NULL, username, NULL FROM users

 

This will cause the application to display usernames from the users table in the second column’s place on the page. You can repeat this process to extract other fields, such as email addresses or hashed passwords.

Depending on the application’s layout, you might need to use data formatting functions or convert values to string types to avoid data type mismatches.

Enumerating the Database Structure

After retrieving useful data, attackers often move on to discover the database’s structure. Many relational database management systems include built-in schemas that provide metadata about tables and columns.

In MySQL, the information_schema database can be queried:

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?id=1 UNION SELECT NULL, table_name, NULL FROM information_schema.tables

?id=1 UNION SELECT NULL, column_name, NULL FROM information_schema.columns WHERE table_name=’users’

 

These queries allow attackers to list all tables and their respective columns. This helps them plan further data extraction in a structured manner.

Dealing with Data Type Mismatches

UNION SELECT queries will fail if the data types between the original query and the injected query don’t match. For example, if the original query expects an integer in a column, inserting a string may trigger an error.

In such cases, casting values can solve the problem:

• In MySQL: CAST(column_name AS CHAR)

• In PostgreSQL: column_name::text

This technique ensures that values fit into the expected format and prevents errors from halting the injection.

Avoiding Detection and Bypassing Filters

Many modern web applications use input filters or web application firewalls to detect and block SQL injection attempts. However, attackers may employ several techniques to bypass these filters:

• Use URL encoding for special characters (%27 for ‘)

• Split keywords with comments (UN/**/ION/**/SELECT)

• Use lowercase or mixed-case versions of keywords.

• Bypass blacklists by using alternative syntax (UNION ALL SELECT instead of UNION SELECT)

While ethical hackers use these methods to test and strengthen defenses, attackers may use them for malicious purposes. This highlights the need for strong, defense-in-depth protections against SQL injection.

In this first part of the series, we covered the core principles of SQL injection and the specific use of the UNION SELECT technique. You learned how attackers detect vulnerabilities, determine column counts, identify displayed columns, and extract data from the database. These steps form the foundation of a hands-on SQL injection methodology.

In the next part of the series, we will move deeper into advanced use cases, including extracting multi-table data, exploiting blind injection scenarios with UNION SELECT, and bypassing common defensive mechanisms through crafted payloads.

 Advanced Data Extraction, Bypasses, and Real-World Exploitation

Deep Dive into Column and Data Type Matching

As introduced in Part 1, for a UNION SELECT injection to succeed, each SELECT statement must have the same number of columns, and the data types of the corresponding columns must match. In real-world environments, achieving this can be more complicated than simply matching column count. Databases may have complex schemas, and different columns may accept only specific data types.

When constructing payloads, it’s critical to understand the structure of the original query and to identify the expected data types. For instance, if the original query includes a numeric column followed by two string columns, your UNION SELECT must respect this structure. A payload such as:

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?id=5 UNION SELECT 1, ‘admin’, ‘secret’

 

Is more likely to succeed than:

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?id=5 UNION SELECT ‘one’, 2, ‘three’

 

When the original query expects numerical input in the first column.

If data type mismatches cause errors, the use of conversion functions becomes necessary. In MySQL, values can be cast using CAST() or CONVERT():

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?id=5 UNION SELECT CAST(username AS CHAR), NULL, NULL FROM users

 

This ensures that numeric placeholders or incompatible fields are properly adapted to the expected format, which prevents query failure and helps extract information smoothly.

Extracting Multiple Columns from Sensitive Tables

After determining the correct number and data types of columns, you can extract complete records by using real column names from tables like users or employees.

Assume you have identified that three columns are displayed, and column positions 1, 2, and 3 are visible on the page. You can then extract meaningful data like this:

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?id=5 UNION SELECT username, email, password FROM users

 

The output, if unfiltered, may show usernames, email addresses, and password hashes directly on the web page. Some developers try to hide such sensitive columns, but any column mapped to a visible output can leak information.

If the column count of the original query is higher than that of the users table, you can use NULLs or dummy data to balance the remaining columns:

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?id=5 UNION SELECT username, email, password, NULL, NULL FROM users

 

This technique becomes invaluable in applications where the query spans many columns due to complex table joins or multiple fields in a view.

Exploiting UNION SELECT in Search-Based Interfaces

Search fields are commonly vulnerable to UNION-based SQL injection. When users enter terms in search forms, the backend may use SQL queries to retrieve matching records from a database. If the application inserts the input directly into the query string, it becomes possible to inject a UNION clause into the search input.

Example:

A search form executes the following query:

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SELECT product_name, description FROM products WHERE description LIKE ‘%user_input%’

 

An attacker can input:

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%’ UNION SELECT username, password FROM users —

 

This results in:

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SELECT product_name, description FROM products WHERE description LIKE% ‘%%%’

UNION SELECT username, password FROM users–‘

 

Assuming the column count and data types match, the attacker could receive usernames and passwords embedded in the product search results.

To exploit this fully, the attacker must analyze the page layout and inject values that align with how the output is rendered, making the data extraction more readable.

Using Information Schema for Structured Enumeration

A powerful tactic used during UNION SELECT exploitation is querying the database’s metadata to discover all tables and columns. In MySQL, this is done via the information_schema database.

Start by extracting all table names:

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?id=1 UNION SELECT table_name, NULL, NULL FROM information_schema.tables

 

Next, for a specific table, such as users, enumerate its columns:

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?id=1 UNION SELECT column_name, NULL, NULL FROM information_schema.columns WHERE table_name=’users’

 

This lets attackers know exactly which fields are available, aiding in precise data targeting. With this information, attackers can proceed to dump records from identified tables using a refined UNION SELECT query:

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?id=1 UNION SELECT username, email, password FROM users

 

This step is often repeated across other interesting tables like credit_cards, admin_logs, or employee_records.

Extracting Data from Multiple Tables in One Query

Sometimes attackers want to retrieve data from more than one table within a single UNION SELECT query. This is only possible when the structure and column count of the involved tables are compatible.

For example, if both the users and orders tables have columns with compatible data types and you know which are visible on the page, you can write:

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?id=1 UNION SELECT username, email, NULL FROM users

UNION SELECT customer_name, order_email, NULL FROM orders

 

This merges results from both tables into a unified output. However, most real-world applications will limit or sanitize the query string, preventing such complex multi-select behavior unless additional bypass techniques are used.

Practical Bypass Techniques

Web applications often implement filters to defend against SQL injection. Common protections include input sanitization, blacklisting keywords, encoding characters, and limiting input length. However, experienced attackers use creative bypasses.

Some practical bypass techniques include:

• Inline comments: Obfuscate keywords using comments
  UN/**/ION/**/SELECT

• String concatenation: Break the payload into parts
  ‘UN’+’ION’+’ SELECT’

• Alternative keywords: Use UNION ALL SELECT or database-specific functions

• Encoding: Use hex or URL encoding
  %55%4e%49%4f%4e is the hex for UNION

• Case variations: Bypass filters that are case-sensitive
  union Select or UnIoN SeLeCt

These techniques help attackers craft payloads that slip past naive input filters and continue the injection process.

Exploiting Error-Based Behavior to Refine UNION SELECT

Although UNION SELECT is a data retrieval method rather than an error-based injection type, combining it with error messages can improve accuracy. Attackers often test how many columns they need by sending deliberately malformed UNION queries and observing database responses.

Error messages like:

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All queries combined using a UNION, INTERSECT, or EXCEPT operator must have an equal number of expressions.

 

or

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Operand should contain 3 column(s)

 

Indicate exactly how many columns the original query uses. These messages are useful for debugging failed payloads.

However, developers sometimes disable error messages in production, in which case attackers must rely on inference-based approaches or errorless blind techniques, which we will explore in Part 3.

Real-World Scenario: Extracting Admin Credentials

Consider a situation where a web application lists product reviews. Each review includes a product name and a short text. The URL to view a review looks like this:

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https://example.com/review.php?id=12

 

Upon testing, injecting a single quote triggers a SQL syntax error. This suggests the query might be:

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SELECT name, content FROM reviews WHERE id = ‘[user_input]’

 

The attacker uses ORDER BY tests and finds the query has two columns. The next step is to identify visible columns using:

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?id=12 UNION SELECT 1,2

 

If the number 2 appears in the output, the attacker replaces it with sensitive fields from the admin table:

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?id=12 UNION SELECT 1, password FROM admin

 

This displays the admin’s password hash in place of a product review, possibly leading to privilege escalation.

Impact of Successful UNION SELECT Exploitation

A successful UNION SELECT injection can have devastating consequences for the targeted organization. Data exposure through this method can lead to:

• Leakage of user credentials, possibly in plaintext or as unsalted hashes.

• Exposure of personal identifiable information (PII).

• Theft of credit card numbers or financial transactions.

• Compromise of admin accounts and privilege escalation.

• Regulatory fines due to non-compliance with data protection laws.

These impacts underline the critical importance of both understanding and defending against this form of attack.

Defensive Measures Against UNION SELECT Injection

Organizations must take proactive steps to defend their applications from SQL injection in general, and UNION-based attacks in particular.

Recommended practices include:

• Parameterized queries: Use prepared statements with bound parameters.

• Input validation: Only allow expected input formats, especially for numeric IDs.

• Escaping inputs: Sanitize inputs where necessary using database-specific escape functions.

• Least privilege: Limit the permissions of the database user connected to the application.

• Disable detailed errors: In production, suppress SQL error messages to avoid leaking hints to attackers.

• Web Application Firewalls (WAFs): Use WAFs that detect and block malicious patterns.

Even though attackers continue to evolve their methods, these practices provide solid defense-in-depth.

 

This second installment provided a detailed look at how UNION SELECT is used for structured data extraction, bypassing filters, and dealing with real-world challenges like data type mismatches and output formatting. We covered how to extract multiple columns from sensitive tables, enumerate schema metadata, and work around common defensive mechanisms.

In Part 3, we’ll explore how UNION SELECT applies to blind injection situations, how to infer data without direct output, and how timing and content-based inference can still make UNION SELECT viable under limited feedback conditions.

 Blind SQL Injection with UNION SELECT and Inference Techniques

Understanding Blind SQL Injection

Not all SQL injection vulnerabilities reveal their data directly. In many secure or production environments, detailed error messages are suppressed, and application output does not visibly display database contents. This scenario is known as blind SQL injection.

Blind SQL injection occurs when the attacker can send payloads to the application and observe changes in behavior or response time, but does not directly see the results of injected queries. This makes extracting data more challenging, but UNION SELECT injection can still be employed with inference-based techniques.

Blind injection is broadly categorized into:

• Boolean-based (content-based) blind injection: The attacker sends queries that evaluate to true or false and infers information based on differences in the application’s responses.

• Time-based blind injection: The attacker sends queries that delay the response conditionally, allowing them to infer data based on timing differences.

The following sections explore how UNION SELECT is used in blind SQL injection scenarios.

UNION SELECT in Boolean-Based Blind SQL Injection

In boolean-based blind injection, the attacker crafts payloads that cause the original query to return different outputs depending on whether a condition is true or false. Although no data is directly returned, the attacker detects differences in the page content, such as variations in text length, the presence or absence of an element, or even HTTP response codes.

For example, consider the vulnerable parameter:

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?id=10

 

The attacker can try a payload like:

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?id=10 UNION SELECT NULL, NULL WHERE (SELECT SUBSTRING(password,1,1) FROM users WHERE username=’admin’) = ‘a’ —

 

If the first character of the admin’s password is a, the UNION SELECT returns a valid result, and the page might render normally. If not, the query returns no results, causing a different page behavior.

By iteratively changing the character tested in the payload and observing the page’s behavior, the attacker can reconstruct the password one character at a time.

This method requires careful crafting of UNION SELECT clauses and precise observation of subtle changes in the application’s response.

Using Conditional Logic within UNION SELECT

To perform blind enumeration, attackers embed conditional SQL functions inside UNION SELECT statements. Typical SQL functions used in blind injection include:

• SUBSTRING() or MID() to extract portions of strings.

• ASCII() to convert characters into ASCII codes for easier comparison.

• IF() or CASE statements to test conditions.

Example payload to check the ASCII value of the first character of a password:

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?id=10 UNION SELECT NULL, IF(ASCII(SUBSTRING((SELECT password FROM users WHERE username=’admin’),1,1))=97, ‘true’, ‘false’) —

 

If the response changes, indicating ‘true’, the attacker knows the first character’s ASCII code is 97 (a). This process is repeated for each character in the password until the full string is revealed.

Automating Blind UNION SELECT Extraction

Manually extracting data via blind injection can be slow and tedious, especially when each character requires a separate request. Therefore, automated tools exist to speed up the process.

Tools such as SQLMap incorporate UNION SELECT blind injection techniques that automate character-by-character extraction by injecting payloads similar to those described above, parsing the web response, and iterating through possible values.

Although automation is common, understanding the underlying methodology is crucial for security professionals to recognize attack patterns and create effective defenses.

Time-Based Blind Injection with UNION SELECT

In time-based blind injection, attackers use SQL commands that delay the database response if a certain condition is true. The application itself does not return data directly, but the attacker measures how long it takes to receive a response.

An example using MySQL’s SLEEP() function:

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?id=10 UNION SELECT NULL, IF(SUBSTRING((SELECT password FROM users WHERE username=’admin’),1,1)=’a’, SLEEP(5), NULL) —

 

If the first character of the admin password is a, the query causes a 5-second delay before responding. Otherwise, it responds immediately.

By sending multiple requests while incrementing the position and testing various characters, the attacker can extract the entire password over time.

Time-based blind injection is slower but effective when no visible output changes exist.

Challenges and Limitations of Blind UNION SELECT Injection

Blind injection is inherently slower and more difficult than traditional UNION SELECT attacks. It requires:

• Multiple HTTP requests (sometimes hundreds or thousands).

• Careful observation of subtle differences in page behavior or response times.

• Overcoming potential rate limiting and logging by the target server.

Moreover, complex queries and web application firewalls can interfere with injection payloads, making the attack less reliable.

Despite these challenges, blind UNION SELECT injection remains a powerful technique in a penetration tester’s arsenal.

Practical Example: Blind Extraction of a User Email

Suppose an attacker suspects that the email of the user admin is stored in the database but cannot be retrieved directly. They may attempt:

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?id=10 UNION SELECT NULL, IF(SUBSTRING((SELECT email FROM users WHERE username=’admin’),1,1)=’a’, ‘X’, ‘Y’) —

 

If the page returns ‘X’, the first character is ‘a; otherwise, it’s something else.

This method is repeated for each character position and each letter or number, eventually revealing the entire email.

When output differences are subtle, attackers may rely on other indicators, such as changes in HTML element count, page length, or HTTP status.

Defensive Techniques Against Blind UNION SELECT Injection

While blind injection is less obvious, defensive strategies remain largely the same:

• Use parameterized queries or stored procedures that separate code from data.

• Implement strict input validation and sanitization.

• Limit database user permissions to reduce impact.

• Monitor unusual request patterns that may indicate brute-force blind injection.

• Deploy Web Application Firewalls configured to detect injection payloads and anomalous behavior.

• Use error suppression to prevent accidental leakage.

Because blind injection depends heavily on side-channel information, defenders should monitor timing anomalies and response discrepancies that could signal an ongoing attack.

 

Blind SQL injection complicates data extraction because attackers do not see immediate query results. Nevertheless, UNION SELECT remains a valuable technique when combined with inference and conditional logic, allowing attackers to reconstruct data bit by bit.

In this part, we covered how attackers use boolean- and time-based blind SQL injection with UNION SELECT, leveraging functions like SUBSTRING, ASCII, and conditional IF statements. These methods require patience and automation but are effective against well-secured applications.

The final part of this series will discuss real-world case studies, advanced evasion techniques, and recommendations for securing applications against UNION SELECT SQL injection.

 Advanced Evasion Techniques, Real-World Case Studies, and Defense Strategies

Advanced Evasion Techniques for UNION SELECT Injection

Attackers often encounter defensive mechanisms like input validation, filtering, Web Application Firewalls (WAFs), and Intrusion Detection Systems (IDSs). To bypass these protections and successfully exploit UNION SELECT injection vulnerabilities, they employ advanced evasion methods.

Obfuscation Using Comments and Whitespace

One common evasion technique is inserting inline comments and excessive whitespace to confuse pattern matching:

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?id=1 UNION/**/SELECT/**/username, password/**/FROM/**/users–

 

This breaks keyword patterns such as UNION SELECT so that simple filters or signatures do not detect them.

Using Case Variations and Alternative Keywords

Filters that are case-sensitive can be bypassed by mixing uppercase and lowercase letters:

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?id=1 uNiOn sEleCt username, password FROM users–

 

Similarly, alternative SQL syntax or synonyms can be used:

• UNION ALL SELECT instead of UNION SELECT

• Using database-specific functions or casting

Encoding and Double-Encoding Payloads

Attackers sometimes URL-encode or double-encode characters to bypass input filters:

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?id=1%20UNION%20SELECT%20username,password%20FROM%20users–

 

Or even double encode:

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?id=1%2520UNION%2520SELECT%2520username,password%2520FROM%2520users–

 

When decoded multiple times by the server, the payload executes as intended.

Stacked Queries and Multi-Statement Injection

If the database and application permit, attackers might use stacked queries, sending multiple SQL statements separated by semicolons:

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?id=1; DROP TABLE users; —

 

Although this is not strictly UNION SELECT injection, it often complements UNION attacks. Defenses that do not prevent multiple queries are vulnerable to this attack.

Using Logical Operators to Bypass Filters

Sometimes blacklists target specific keywords. Attackers use logical operators like OR 1=1 combined with UNION to bypass filters:

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?id=1 UNION SELECT username, password FROM users WHERE 1=1–

 

Or inject boolean conditions inside the UNION SELECT to bypass pattern matching.

Real-World Case Studies of UNION SELECT SQL Injection

Case Study 1: E-Commerce Site Data Breach

In one high-profile breach, attackers exploited a UNION SELECT vulnerability in an e-commerce platform’s product search page. The search input was vulnerable because it directly embedded user input in a SQL query without parameterization.

Attackers enumerated the database schema by querying information_schema.tables and information_schema.columns via UNION SELECT. After discovering the user’s table and its columns, they extracted usernames, emails, and password hashes. This led to credential stuffing attacks against customer accounts, causing financial losses and reputational damage.

Case Study 2: University Portal Compromise

A university’s student information system was vulnerable through a poorly sanitized student ID parameter. The attacker exploited UNION SELECT injection to retrieve sensitive student records, including grades and personal details. The attacker used advanced evasion techniques, such as comment obfuscation and encoding, to bypass the institution’s weak WAF.

This breach prompted the university to implement parameterized queries, strict input validation, and enhanced monitoring.

Case Study 3: Content Management System Exploit

A popular open-source content management system was found to have a UNION SELECT vulnerability in its article retrieval module. Attackers used it to dump administrator credentials and site configuration data.

Because the site returned error messages, the attacker used error-based UNION SELECT injections to fine-tune payloads and extract data rapidly. The developers released a patch fixing the vulnerability by moving to prepared statements and removing direct string concatenation of SQL queries.

Comprehensive Defense Strategies Against UNION SELECT Injection

Defending against UNION SELECT SQL injection requires a multi-layered approach combining secure coding practices, infrastructure controls, and monitoring.

Use Parameterized Queries and Prepared Statements

The most effective defense is to avoid constructing SQL queries by concatenating user input. Instead, use parameterized queries where input is passed separately from the query structure. This prevents user data from being interpreted as SQL code.

Example in PHP with PDO:

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$stmt = $pdo->prepare(‘SELECT name, description FROM products WHERE id = ?’);

$stmt->execute([$userInput]);

 

Implement Strict Input Validation and Whitelisting

Validate all user inputs against expected formats. For numeric IDs, enforce that inputs contain only digits. For text fields, limit length and reject suspicious characters.

Whitelisting acceptable input patterns reduces the attack surface drastically.

Least Privilege Principle for Database Users

Limit database user permissions so that even if an injection occurs, the damage is minimized. For example, the web application’s database user should not have permissions to DROP tables or access sensitive administrative data unless necessary.

Error Handling and Logging

Disable detailed SQL error messages on production servers to avoid providing attackers with clues. Instead, log errors internally for troubleshooting.

Proper logging helps detect suspicious activity indicative of injection attempts.

Web Application Firewalls and Intrusion Detection

Deploy WAFs capable of detecting SQL injection payloads, including encoded and obfuscated variants. WAFs should be kept up to date and fine-tuned to avoid false positives.

Intrusion detection systems can monitor traffic and alert administrators about abnormal query patterns.

Regular Security Testing and Code Audits

Periodic penetration testing and code reviews help identify injection vulnerabilities early. Automated static code analysis tools can highlight risky code constructs.

Educate developers about secure database interaction and injection risks.

Final Thoughts

This final part of the series covered sophisticated evasion tactics attackers use to exploit UNION SELECT injection vulnerabilities despite defensive measures. We examined real-world examples where these attacks caused significant data breaches, emphasizing the severity of this threat.

Finally, we reviewed comprehensive defense techniques ranging from secure coding and input validation to infrastructure-level protections and ongoing security maintenance.

SQL injection, particularly UNION SELECT injection, remains a prevalent and dangerous threat vector due to its potential to expose sensitive data. Organizations must adopt a layered security strategy and stay vigilant against evolving attack methods to protect their applications and users.

 

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