Nosql Injection in Buffalo with Dynamodb

Buffalo is a convention-driven web framework for Go, and when it interacts with Amazon DynamoDB it can expose a NoSQL injection risk if user input is used to construct DynamoDB expressions without validation or escaping. NoSQL injection in this context occurs when attacker-controlled data modifies the structure or behavior of DynamoDB queries, such as filter expressions, key condition expressions, or projection expressions. Because DynamoDB uses a JSON-like syntax for expressions and does not use traditional SQL parameterization, concatenating user input into these expressions can allow an attacker to change the logical intent of the query.

For example, consider a search endpoint in Buffalo that builds a FilterExpression from a query parameter like username. If the handler does not treat the input as untrusted, an attacker could provide a value such as admin' OR '1'='1 that changes the filter logic. In DynamoDB this might translate to a malformed expression that bypasses intended filtering, potentially returning other users' data or enumerating sensitive records. The risk is compounded when the application uses expression attribute values incorrectly or omits them entirely, effectively injecting raw user input into the expression.

DynamoDB-specific constructs such as attribute_exists, begins_with, and comparison operators can be manipulated. An attacker might supply a payload that changes a key condition expression on a partition key or sort key, leading to unauthorized data access. Because Buffalo applications often map HTTP parameters directly to DynamoDB API calls, the framework does not inherently protect against this class of injection. The combination of Buffalo’s flexible request handling and DynamoDB’s expression syntax creates a clear path for NoSQL injection when developers treat user input as safe.

Additionally, the use of the AWS SDK for Go with DynamoDB requires careful handling of expression attribute names and values. If attribute names are constructed dynamically using user input, an attacker can inject reserved words or change the semantics of the query. For instance, supplying a crafted input for a sort key can lead to scanning across partitions or reading unintended items. The NoSQL injection risk in Buffalo + DynamoDB is therefore rooted in missing input validation, improper expression building, and a lack of separation between data and expression structure.

To prevent NoSQL injection in Buffalo when working with DynamoDB, always use expression attribute values and expression attribute names rather than string concatenation for user input. The AWS SDK for Go provides awsmiddleware.BuildContent and expression builders that help keep data and expression boundaries clear. Below are concrete code examples demonstrating a secure approach in a Buffalo application.

Secure FilterExpression with Expression Attribute Values

Instead of embedding user input directly, bind it as an expression attribute value. This ensures the input is treated as data, not expression logic.

import (
	"github.com/gobuffalo/buffalo"
	"github.com/aws/aws-sdk-go/service/dynamodb"
	"github.com/aws/aws-sdk-go/service/dynamodb/dynamodbattribute"
)

func showUser(c buffalo.Context) error {
	username := c.Param("username")
	svc := dynamodb.New(session.New())

	input := &dynamodb.QueryInput{
		TableName: aws.String("Users"),
		KeyConditionExpression: aws.String("pk = :uname"),
		ExpressionAttributeValues: map[string]*dynamodb.AttributeValue{
			":uname": {S: aws.String(username)},
		},
	}

	result, err := svc.Query(input)
	if err != nil {
		return c.Error(500, err)
	}

	var users []map[string]interface{}
	dynamodbattribute.UnmarshalListOfMaps(result.Items, &users)
	return c.Render(200, r.JSON(users))
}

Expression Attribute Names for Dynamic Field Names

When field names are derived from user input, use expression attribute names to avoid injection via reserved keywords.

func filterByCustomAttr(c buffalo.Context) error {
	fieldKey := c.Param("field")
	svc := dynamodb.New(session.New())

	input := &dynamodb.ScanInput{
		TableName: aws.String("Products"),
		FilterExpression: aws.String("#fld = :val"),
		ExpressionAttributeNames: map[string]*string{
			"#fld": aws.String(fieldKey),
		},
		ExpressionAttributeValues: map[string]*dynamodb.AttributeValue{
			":val": {BOOL: aws.Bool(true)},
		},
	}

	result, err := svc.Scan(input)
	if err != nil {
		return c.Error(500, err)
	}

	var products []map[string]interface{}
	dynamodbattribute.UnmarshalListOfMaps(result.Items, &products)
	return c.Render(200, r.JSON(products))
}

Validate and Restrict Input Patterns

Apply strict allow-lists for known-safe values (e.g., sort keys, attribute names) and reject unexpected patterns before they reach DynamoDB. For path-based identifiers, use regex validation to ensure they conform to expected formats.

import "regexp"

func isValidUsername(username string) bool {
	re := regexp.MustCompile(`^[a-zA-Z0-9_]{3,32}$`)
	return re.MatchString(username)
}

func safeHandler(c buffalo.Context) error {
	username := c.Param("username")
	if !isValidUsername(username) {
		return c.Error(400, errors.New("invalid username"))
	}
	// proceed with parameterized query as shown earlier
	return nil
}

Paginate and Limit Result Sets

Use DynamoDB’s native pagination controls and limit the number of scanned items to reduce exposure. Combine this with explicit attribute projections to minimize data leakage.

input.Limit = aws.Int64(50)
input.Select = dynamodb.SelectCount

By combining parameterized expressions, strict input validation, and careful use of expression attribute names, Buffalo applications can effectively mitigate NoSQL injection risks when operating against DynamoDB.