Type Confusion in Buffalo with Dynamodb

Type confusion in a Buffalo application that uses DynamoDB can occur when application code deserializes DynamoDB item data into a Go type without enforcing strict type constraints. DynamoDB stores data as loosely-typed attribute-value pairs (e.g., S for string, N for number, BOOL for boolean), and if a developer maps these directly to interface{} or a loosely-typed struct, an attacker can supply a numeric value where a string is expected, or a boolean where a struct is expected. This mismatch can cause the application to behave incorrectly, leading to logic bypasses, unexpected type assertions, or runtime panics that may be exploitable.

Consider a Buffalo handler that retrieves a user record from DynamoDB and asserts a field as a string without validating the underlying type:

import (
	"github.com/gobuffalo/buffalo"
	"github.com/aws/aws-sdk-go/service/dynamodb"
)
unc showUser(c buffalo.Context) error {
	input := &dynamodb.GetItemInput{
		TableName: aws.String("users"),
		Key: map[string]*dynamodb.AttributeValue{
			"user_id": {S: aws.String(c.Param("user_id"))},
		},
	}
	out, err := db.GetItem(input)
	if err != nil {
		return c.Error(500, err)
	}
	// Risky type assertion without validation
	email, ok := out.Item["email"].S
	if !ok {
		// If the attribute is not a string (e.g., it was sent as N or BOOL),
		// the assertion silently fails and email becomes nil, potentially causing
		// downstream logic errors or panics when used as a string.
		return c.Error(500, errors.New("invalid email type"))
	}
	c.Session().Set("email", email)
	return c.Render(200, r.String(email))
}

If an attacker can manipulate the DynamoDB item (e.g., through misconfigured permissions or a compromised upstream process) to store {"email": {"N": "1"}} instead of {"email": {"S": "user@example.com"}}, the type assertion out.Item["email"].S will fail. In some cases, a developer might use a more permissive assertion like val := out.Item["email"] and later switch on the underlying type, which can lead to inconsistent behavior across different inputs. This is a classic type confusion: the program assumes a type that DynamoDB does not guarantee, enabling edge-case logic deviations that may be leveraged for privilege escalation or data exposure in broader attack chains.

Type confusion becomes more critical when the affected field participates in authorization checks (e.g., tenant ID, role, or scope). An attacker might coerce a numeric ID into a string context, bypassing equality checks that rely on strict type matching. Because Buffalo does not enforce schema types at the framework level, developers must validate and sanitize all DynamoDB inputs explicitly, especially when mapping to interface{} or when using type switches to handle polymorphic data.

To prevent type confusion, always validate and convert DynamoDB attribute values to the expected Go types before use. Use helper functions that check the attribute type and return a typed value or an error. Below is a safe pattern for extracting and validating a string field from a DynamoDB item in a Buffalo handler:

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

func getStringAttribute(item map[string]*dynamodb.AttributeValue, key string) (string, error) {
	attr, ok := item[key]
	if !ok {
		return "", errors.New("missing attribute: " + key)
	}
	if attr.S == nil {
		return "", errors.New("attribute is not a string: " + key)
	}
	return *attr.S, nil
}

func showUser(c buffalo.Context) error {
	input := &dynamodb.GetItemInput{
		TableName: aws.String("users"),
		Key: map[string]*dynamodb.AttributeValue{
			"user_id": {S: aws.String(c.Param("user_id"))},
		},
	}
	out, err := db.GetItem(input)
	if err != nil {
		return c.Error(500, err)
	}

	email, err := getStringAttribute(out.Item, "email")
	if err != nil {
		return c.Error(400, err)
	}
	c.Session().Set("email", email)
	return c.Render(200, r.String(email))
}

For numeric fields, use a similar helper that ensures the attribute is of type N and parses it safely:

import (
	"errors"
	"strconv"
	"github.com/aws/aws-sdk-go/service/dynamodb"
)

func getNumberAttribute(item map[string]*dynamodb.AttributeValue, key string) (int64, error) {
	attr, ok := item[key]
	if !ok {
		return 0, errors.New("missing attribute: " + key)
	}
	if attr.N == nil {
		return 0, errors.New("attribute is not a number: " + key)
	}
	return strconv.ParseInt(*attr.N, 10, 64)
}

When modeling domain objects, prefer unmarshaling into typed structs with explicit tags and validate each field. For example:

type User struct {
	ID    string `dynamodbav:"user_id"`
	Email string `dynamodbav:"email"`
	Role  string `dynamodbav:"role"`
}

func getUser(input *dynamodb.GetItemInput) (*User, error) {
	out, err := db.GetItem(input)
	if err != nil {
		return nil, err
	}
	var user User
	err = attributevalue.UnmarshalMap(out.Item, &user)
	if err != nil {
		return nil, err
	}
	// Additional validation: ensure email is not empty and role is one of the allowed values
	if user.Email == "" || (user.Role != "admin" && user.Role != "user") {
		return nil, errors.New("invalid user data")
	}
	return &user, nil
}

By consistently validating attribute types and avoiding unchecked interface{} handling, you eliminate the conditions that enable type confusion. Combine this with runtime security checks from middleBrick — which scans endpoints including those backed by DynamoDB for input validation issues, data exposure, and unsafe consumption patterns — to ensure your API surface remains robust against malformed or malicious payloads.