Preventing SQL/NoSQL Injection Attacks in MongoDB

MongoDB applications face serious security risks when user input goes unvalidated. NoSQL injection attacks can silently breach your database, exposing sensitive data and compromising system integrity. This guide demonstrates proven defensive strategies to sanitize input, secure database queries, and build robust protection against injection-based threats.

What is NoSQL Injection?

NoSQL injection occurs when attackers exploit insufficiently validated user input to manipulate database query logic. By injecting malicious payloads, attackers can bypass authentication mechanisms, extract unauthorized data, or circumvent application security controls.

Unlike SQL injection, which exploits vulnerabilities in string-based query construction, NoSQL injection takes advantage of flexible data structures and dynamic queries. This is especially dangerous when applications accept loosely typed input such as interface{} or map[string]interface{} without proper validation.

Why MongoDB is Different

MongoDB queries are built using BSON (Binary JSON) objects—structured key-value pairs—instead of raw strings. This design avoids many traditional injection risks because queries aren’t assembled through string concatenation.

However, if user input is embedded directly into these BSON objects without proper validation, attackers can inject MongoDB operators like $ne, $gt, or $or to change the logic of the query.

Example: operator injection in Go

filter := bson.M{"name": inputName}
collection.Find(ctx, filter)

If inputName is a plain string like "Joe", it's safe. But if your code allows map[string]interface{} or raw JSON, an attacker could inject operator objects like:

{ "$ne": null }

This payload transforms the query logic, matching  any document where the name exits rather than filtering for a specific value—effectively circumventing the application’s intended access controls..

Recognizing Unsafe Patterns and Common Pitfalls

1. Implicit trust in request bodies

Direct parsing of request bodies into BSON maps creates an injection pathway where attackers can embed malicious query operators and complex logical constructs directly into database operations.

// Unsafe
var filter bson.M
_ = json.NewDecoder(req.Body).Decode(&filter)

Instead, parse only known fields and types:

type QueryInput struct {
    Name string json:"name" validate:"required"
}

2. Accepting loose types

Injection vulnerabilities frequently arise when APIs accept overly permissive data types like interface{} or generic maps. These flexible structures can harbor embedded MongoDB operators or malicious object constructs that bypass intended query logic.

Minimize use of loose tying unless absolutely essential and implement strict validation when unavoidable. Instead, define explicit data structures that match your expected input format and constraint acceptable values.

3. JSON in query strings or query operators

APIs exposing dynamic filtering capabilities through URL query parameters or search endpoints present attractive attack surfaces. Attackers frequently target these interfaces by embedding JSON-encoded operators and conditional logic directly into query strings. This transforms legitimate filter parameters into malicious database operations:

GET /search?filter={"price":{"$gt":0}}

Without rigorous input validation, this approach enables attackers to manipulate query structures and circumvent security controls, potentially exposing unauthorized data or escalating privileges beyond intended access levels.

Mitigation:

• Implement field and operator allowlists to restrict query parameters to predefined, safe values.
• Explicitly wrap all user-provided values in $eq operators when constructing database filters to prevent injection of alternative operators.

4. Expanding logical queries with injection

Applications that permit user control over logical operators such as $or create opportunities for query expansion attacks. Attackers can inject additional conditional expressions into these operators, fundamentally altering query semantics and potentially bypassing authentication checks or data access restrictions. 

filter := bson.M{
  "$or": []bson.M{
    {"role": "user"},
    {"active": true},
  },
}

If user input directly manipulates the $or clause, attackers can inject unauthorized condition:

{ "$or": [ {"role": "user"}, {"active": true}, {"isAdmin": true} ] }

This modified query could bypass role-based access controls, potentially exposing administrative data or granting elevated privileges to unauthorized users. Prevent dynamic modification of logical operators by implementing strict input validation and avoiding direct user control over query structure. 

GET /search?filter={"price":{"$gt":0}}

Without rigorous input validation, this approach enables attackers to manipulate  query structures and bypass security controls, potentially exposing unauthorized data. 

Mitigation:

• Implement allowlists for permitted fields and operators, rejecting any query parameters outside these predefined boundaries.
• Enforce explicit equality matching by wrapping all user input in $eq operators to prevent substitution of comparison or logical operators.

JavaScript Execution Features

MongoDB provides several server-side JavaScript execution capabilities that introduce potential security risks, including:

• $where.
• mapReduce.
• $function.
• $accumulator.

These features create significant security exposure and should be avoided unless critical business requirements demand their use. To prevent exploitation, disable scripting in the MongoDB configuration:

For mongod:

--noscripting

Or via config file:

security:
  javascriptEnabled: false

Apply the same configuration to r mongos in a sharded deployment.

MongoDB’s native query operators provide comprehensive functionality that eliminates the need for JavaScript execution in virtually all use cases. Completely avoid $where clauses unless you maintain absolute control over input validation and execution context.

How to Prevent NoSQL Injection

1. Validate input rigorously

Implement strict type validation that accepts only expected primitive data types like strings, integers, or booleans. Reject any nested objects, arrays, or unrecognized  field names that could contain embedded operations or malicious constructs.

type LoginInput struct {
    Username string json:"username" validate:"required,alphanum"
    Password string json:"password" validate:"required,min=8"
}

2. Don’t trust query structure from users

Construct all database queries using predefined, application-controlled field mappings and query templates. Prohibit user input from influencing query architecture, logical operators, or conditional structures that could subvert intended data access patterns.

filter := bson.M{
    "username": input.Username,
    "password": input.Password,
}

Avoid:

// Dangerous: allows injection of operators
_ = json.NewDecoder(req.Body).Decode(&filter)

Most MongoDB drivers provide strongly-typed query builders that enforce structured query construction and prevent accidental injection vulnerabilities. Leverage these native interfaces rather than exposing raw query maps or BSON objects through application endpoints.

filter := bson.M{
    "username": input.Username,
    "password": input.Password,
}

Avoid:

// Dangerous: allows injection of operators
_ = json.NewDecoder(req.Body).Decode(&filter)

3. Block injection of MongoDB operators

Prevent user-controlled input from functioning as query operators or logical constructs. Treat all user data as literal values rather than executable query components.

Instead of:

filter := bson.M{
    "status": input.Status,
}

Use:

filter := bson.M{
    "status": bson.M{"$eq": input.Status},
}

This approach enforces strict equality matching and prevents execution of injected operators such as $ne, $in, or $regex or other logical modifiers that could bypass intended query logic.

4. Use least privilege for database users

Configure application database connections with user accounts that possess only the minimum permissions required for the intended operations. Avoid using admin-level credentials from application configurations to prevent potential damage from successful injection attacks.

5. Monitor and test

Implement comprehensive logging to detect unusual query patterns and establish regular security testing protocols. Validate endpoint security by attempting injection attacks using malformed payloads such as:

{ "$ne": null }

Verify that the application rejects it.

Test cases to consider:

• Objects instead of strings: { "username": { "$ne": null } }
• Arrays instead of scalars: { "roles": [ { "$gt": "" } ] }
• Operators as query values: { "field": { "$regex": ".*" } }

Summary Checklist

• Input validation: Enforce strict data types, validate formats, and reject unexpected fields.
• Query construction: Build all queries using predefined schemas and application-controlled templates
• Operator protection: Block MongoDB operators in user input by wrapping values in $eq or using typed APIs.
• Server-side JavaScript: Eliminate $where clauses and disable JavaScript execution in production configurations.
• DB access control: Configure application connections with minimal required permissions, avoiding administrative credentials.
• Testing and monitoring: Conduct regular injection testing and implement logging for anomalous query patterns.

Final Thoughts

NoSQL injection vulnerabilities are entirely preventable through disciplined secure coding practices. Implementing rigorous input validation, structured query construction, and defense-in-depth security controls enables developers to maintain application flexibility and performance while eliminating injection attack vectors.

Success requires understanding your application's complete data flow—from initial request parsing through final query execution. Establish a zero-trust approach to all input sources, implement validation at system boundaries, and prioritize defensive programming principles throughout your entire technology stack.