Beyond SQL: Exploring Injection Attacks in the NoSQL World

Introduction

NoSQL databases have transformed how modern applications handle large volumes of data. From social platforms to e-commerce backends, tools like MongoDB and CouchDB offer the flexibility and speed developers crave. But with that freedom comes a quiet, often underestimated threat: NoSQL injection.

Table of Contents

NoSQL injection is similar to the better-known SQL injection, but instead of attacking traditional databases, it targets systems using NoSQL technologies. The danger? A single poorly handled input field could give attackers a way in no complex tools required.

In 2021, a serious example surfaced in “Rocket Chat” “https://www.rocket.chat/”, a widely used open-source messaging platform for businesses. Security researchers discovered that attackers could exploit unfiltered user input in database queries, allowing them to perform NoSQL injection attacks. This enabled the attackers to manipulate “MongoDB” queries and escalate their privileges to take control of admin accounts. From there, they could execute code on the server itself a complete system compromise. All this started with something as simple as entering crafted data into a login field.

In this blog, we’ll break down what NoSQL injection is, how it works, how attackers exploit it, and most importantly, how you can protect your applications from falling victim to it.

What is NoSQL? How is it different from traditional SQL databases?

NoSQL databases are non-relational systems designed to handle diverse data types structured, semi-structured, or unstructured. Unlike traditional SQL databases, which rely on rigid table-based schemas, NoSQL uses flexible data models like key-value pairs, documents, graphs, or wide-column stores. This makes them ideal for applications with rapidly changing requirements, large-scale data, or real-time demands. NoSQL databases offer schema flexibility, high-speed performance, and are commonly used in modern applications such as social networks, analytics engines, and IoT platforms where speed and scalability matter more than a strict relational structure.

NoSQL databases include:

MongoDB
Redis
Elasticsearch
Apache CouchDB
Cloudflare KV or Amazon DynamoDB
Firebase
Apache Cassandra and Apache HBase.
Neo4j and Amazon Neptune

What is NoSQL Injection? How is it different from SQL Injection?

NoSQL injection is kind of like SQL injection’s modern cousin. It happens when user input is plugged directly into a database query without proper checks, giving attackers a chance to mess with how the query behaves. But instead of targeting old-school relational databases, this kind of attack goes after newer, more flexible ones like MongoDB, Redis, and CouchDB. These databases are fast and developer-friendly, but if input isn’t handled safely, they can become a serious security risk.

NoSQL Injection may allow an attacker to:

Bypass authentication
Edit/Delete existing data records
Extract sensitive data
Create new entries
Cause a Denial of Service (DoS) attack.
Perform Code/command execution.

The difference between NoSQL injection and SQL injection lies in the query syntax. SQL query usually works on truthy statements; if the query is executed and returns True, we’ll get the desired data. Let’s take an example:

This will return user data if the username and password combination is correct.

In NoSQL, the same data will be obtained by the following query:

And the HTTP request will be as below:

NoSQL databases often use code written directly in the application’s programming language, or in formats like JSON, XML, or LINQ to handle data. Because of this, harmful input can sometimes slip through without being caught by standard security checks. Unlike traditional SQL injection, which runs inside the database itself, NoSQL injection can happen either in the application or in the database, depending on how the system handles queries. These attacks usually work by tricking the app into accepting and running dangerous code when it builds or processes a NoSQL query.

How NoSQL Injection Works? Examples.

To check for NoSQL Injection, we have to find an insertion point to break the query. To detect injection points, we can look for inputs that are directly used in query construction, like login forms, search fields, or API filters. We can do it by either breaking the current syntax or adding an operator and observing the response for any changes. We can use NoSQL-specific syntax and operators such as $ne, $gt, or $regex to manipulate queries and bypass expected logic.

NoSQL can happen in 2 ways:

NoSQL Syntax Injection– NoSQL injection vulnerabilities can be found by submitting crafted inputs or special characters to break the query logic. If the application reacts with errors or unusual behaviour, it may indicate weak input validation.
- For example, an application has a feature that filters product listings by category. The backend MongoDB query looks like this:

Normal input can be here any category name line, “electronics”, “toys”, etc. And malicious input can be any fuzzy string like ‘”`{, ;$Foo}, $Foo \xYZ etc. These fuzz strings might generate syntax errors or any error that exposes internal query structures.

Let’s understand this with an example.

A website lets users look up profiles using a simple URL like:

Internally, the server uses a MongoDB $where query like this:

If the input isn’t sanitised, attackers can inject additional JavaScript logic to extract data about the admin user. We can try different payloads here to extract data/password related to the admin.

For example, check if the first character of the password is ‘a’ with this payload:

This will go in the query as:

If true, the result confirms that the first character is ‘a. If false, we can keep guessing b by providing different characters.

To check if the password is longer than 8 characters:

This will go in the query as:

This will be used to guess password length before brute forcing character-by-character.

Like this, we can try to get the password of the admin account or any other field available in the same database.

NoSQL Operator Injection– NoSQL databases use special operators to set rules for what data should be returned in a query. Some examples are:

$where – Matches documents that satisfy a JavaScript expression.
db.users.find({ $where: “this.age < 30” })
$ne – Matches all values that are not equal to a specified value.
db.users.find({ status: { $ne: “active” } })
$in – Matches all the values specified in an array.
db.users.find({ role: { $in: [“admin”, “editor”] } })
$regex – Selects documents where values match a specified regular expression.
db.users.find({ name: { $regex: “^A” } })
$eq: Matches values that are equal to a specified value.
db.users.find({ age: { $eq: 25 } })
$gt: Matches values that are greater than a specified value.
db.users.find({ age: { $gt: 40 } })

We can try to inject a malicious payload with different operators to bypass any logic or for data exfiltration.

For example, a login form checks username and password like this:

With normal input where Username: [email protected] and Password: hacker001, the query will be like this:

With malicious input where:

Username: [email protected]
Password: { “$ne”: null }

the query will be like this:

This will result in successful login into User1’s account as the Password is not equal to null, which is true.

How to Detect NoSQL Injection?

Test Category	What to Do	Example Input / Payload	What to Look For
🔍Basic Input Fuzzing	Submit special characters and malformed data to break query parsing	“, }, ], {, \’, \n, null, malformed JSON	Errors, crashes, or leaked query structures
🧪Operator Injection	Inject NoSQL operators to manipulate logic	{ “password”: { “$ne”: null } }	Bypass auth, see more results, logic manipulation
🔁Boolean Logic Injection	Use always-true conditions to bypass logic	{ “username”: { “$gt”: “” }, “password”: { “$gt”: “” } }	Unintended access, successful login without valid credentials
🔄$or / $and Injection	Insert $or or $and operators to force multiple query branches	{ “$or”: [ {}, { “admin”: true } ] }	Bypass access controls or filters
🔍$regex Injection	Use regular expressions to match everything or brute-force patterns	{ “username”: “admin”, “password”: { “$regex”: “.*” } }	Match any value, bypass credentials
🧱Structure Tampering	Inject parts of JSON to modify query layout or add fields	john”, “role”:”admin	Unexpected data exposure or permission escalation
❌Malformed Syntax	Break JSON or query format using extra brackets or quotes	“}” or “]	JSON parse errors, app behaviour change
🧾Error Message Analysis	Intentionally break input to trigger detailed server errors	“}” or invalid types	Stack traces, query fragments, database version leaks
🔁Data Type Coercion	Stack traces, query fragments, and database version leaks	“username”: [“admin”] or “username”: {}	Unexpected query matching or app crashes
🌐API/Query Parameter Fuzzing	Test REST API endpoints or query parameters with injection payloads	/products?filter={“$ne”:null}	Filter bypass, over-exposed data
🔧Automated Tooling	Use tools for active scanning and fuzzing	Tools: NoSQLMap, Burp Suite, OWASP ZAP, Ffuf	Auto-detected injection points and proof-of-concept payloads

Common Attack Vectors and Real-Life Examples

Here are some common attack vectors for NoSQL Injection:

Authentication Bypass: This happens when attackers find a way to log into an account without knowing the correct password. They do this by tricking the system into thinking the login is valid using special inputs. The problem usually happens when the system doesn’t properly check what users are sending in. With this trick, attackers can break into accounts, including admin accounts, and access private information or control the system.
Example: An attacker tries to log in as “admin” and uses a special input to avoid entering the correct password.
- Example Payload: { “username”: “admin”, “password”: { “$ne”: null } }
Conditional Query Manipulation: In this type of attack, the attacker changes how the database search works by using special commands like $gt, $lt, or $regex. These commands change the way the data is filtered, letting the attacker see more data than they should. This works when the system accepts user input directly in a database search without checking it properly, leading to unexpected results or even security problems.
Example: An attacker uses a trick to show the system all products with a price above zero, even if that shouldn’t be allowed.
- Example Payload: { “price”: { “$gt”: 0 } }
Data Exposure / Leakage: Data exposure happens when attackers change the query in a way that makes the system show private or restricted data. This can include things like customer records, admin information, or other sensitive content. It usually happens when the app trusts user input too much and doesn’t check it carefully. If successful, the attacker can see data that should be hidden or protected, which could lead to major privacy or security issues.
Example: An attacker changes a filter, so the system shows all categories, even ones that are supposed to be hidden or private.
- Example Payload: { “category”: { “$ne”: null } }
Privilege Escalation: Privilege escalation is when a normal user tricks the system into thinking they are an admin or someone with more power. This lets them do things they shouldn’t be allowed to, like change settings or access secure areas. This can happen if the system doesn’t properly check what permissions a user should have. It can lead to serious issues, including complete system takeover or leaking sensitive data.
Example: A regular user sends a request pretending to be an admin by changing their user role in the input.
- Example Payload: “}”, “role”:”admin
Blind Injection via Timing: In this type of attack, the attacker doesn’t see any direct output from the system but watches how long it takes the system to respond. They use this timing information to guess what’s going on in the background. For example, if the system responds slower when certain data is true, the attacker can figure out details without seeing the actual data. This is often used to discover hidden information in a slow and sneaky way.
Example: The attacker uses a pattern that causes a delay, helping them figure out if a certain condition is true in the database.
- Example Payload: { “$regex”: “.*” }
Denial of Service (DoS): In a DoS attack, the attacker sends a request that uses up a lot of the system’s power, like CPU or memory. The goal is to slow down or crash the app so that real users can’t use it. This might include huge pattern searches or massive lists that the system must sort through. It’s not about stealing data, it is about causing trouble by making the system stop working properly or go offline.
Example: The attacker uses an input that loops forever or creates a huge search, causing the server to slow down or crash.
- Example Payload: 0; while(true){}
Data Integrity Attacks: These attacks are about changing or messing up the data stored in the system. Attackers may change important values like user roles, status flags, or other critical data by sending smartly crafted input. This can lead to fake admin accounts, broken business logic, or even corrupted databases. If the system trusts user input without checking it, attackers can do real damage to the data’s accuracy and trustworthiness.
Example: An attacker updates their own profile to say they’re an admin, even though they’re just a regular user.
- Example Payload: { “$set”: { “isAdmin”: true } }
Cross-Site Scripting (XSS) via Injection: XSS happens when attackers put JavaScript code into fields like comments or search boxes. If the app stores that input and show it later a web page without cleaning it, the script will run in other users’ browsers. This can let the attacker steal login info, mess with the page, or trick users into doing things. It’s especially dangerous if the app doesn’t properly clean or encode user inputs before showing them on screen.
Example: The attacker puts a script in a comment field, and when someone else views that comment, the script runs in their browser.
- Example Payload: { “comment”: “<script>alert(‘XSS’);</script>” }
Command Injection: Command injection happens when attackers can send inputs that make the server run system-level commands like commands you’d run in a terminal. This can happen if the app takes user input and passes it to a system command without checking it. If successful, the attacker can control the server, run code, steal files, or even fully take over the machine. This is one of the most serious security risks, especially if it leads to remote code execution.
Example: The attacker uses an input that runs a command to list all files on the server.
- Example Payload: db.eval(“function() { require(‘child_process’).exec(‘ls’) }”)

Let’s discuss some real-life attacks caused by NoSQL Injection:

Rocket Chat Remote Code Execution (2021): In 2021, security researchers discovered two NoSQL injection vulnerabilities in Rocket Chat, an open-source enterprise messaging platform. These flaws allowed unauthenticated attackers to hijack user accounts, escalate privileges, and ultimately execute arbitrary commands on the host server. The vulnerabilities were traced back to insecure MongoDB queries in the platform’s web interface.
MongoDB Ransomware Attacks (2017–2018): In early 2017, a wave of ransomware attacks targeted unsecured MongoDB instances. Attackers exploited default configurations that left databases exposed to the internet without authentication. Once accessed, attackers deleted the data and demanded ransom payments in exchange for restoring access. This led to the loss of data from thousands of MongoDB installations worldwide.
Cockpit CMS Remote Code Execution via NoSQL Injection (2021): Cockpit CMS, an open-source content management system, had critical NoSQL injection vulnerabilities in its “MongoLite” database implementation. These flaws allowed unauthenticated attackers to exploit the authentication and password reset functions to perform remote code execution on the server. The vulnerabilities were assigned CVE-2020-35846 and CVE-2020-35847, both with a CVSS rating of 9.8, indicating their severity.

Prevention and Mitigation Techniques

Like all input validation-related security issues, to avoid NoSQL injections, we must always treat user inputs as untrusted data. We try the following prevention and mitigation techniques against NoSQL Injection:

Input Validation: Ensure all user inputs are validated against a strict schema.
Parameterised Queries: Use parameterised queries to prevent direct insertion of user inputs into queries.
Least Privilege: Limit database user permissions to the minimum necessary for application functionality.
Error Handling: Implement proper error handling to avoid exposing database errors to end-users.
Regular Audits: Conduct regular security audits and penetration testing to identify and fix vulnerabilities.

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Beyond SQL: Exploring Injection Attacks in the NoSQL World

Introduction

What is NoSQL? How is it different from traditional SQL databases?

What is NoSQL Injection? How is it different from SQL Injection?

How NoSQL Injection Works? Examples.

How to Detect NoSQL Injection?

Common Attack Vectors and Real-Life Examples

Prevention and Mitigation Techniques

Reference Links

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