Broken Access Control in Fiber with Dynamodb

Broken Access Control occurs when API endpoints fail to enforce proper authorization checks, allowing one user to access or modify resources belonging to another. In a Fiber-based application using Amazon DynamoDB as the data store, the risk is elevated when route handlers rely on client-supplied identifiers (such as a user ID or record ID) without verifying that the authenticated subject has the right to access that specific DynamoDB item.

Consider a typical pattern where a Fiber route uses a URL parameter like /users/:userID/profile. If the handler directly uses userID from the params to build a DynamoDB Key and fetch a profile, it may return the data without confirming the requesting user is the same as userID. Because the scan tests unauthenticated attack surfaces, middleBrick can expose this by manipulating the parameter and observing whether the endpoint returns another user’s data, indicating an Insecure Direct Object Reference (IDOR) — a classic Broken Access Control finding.

DynamoDB itself does not enforce object-level ownership; it only enforces permissions at the table or index level via IAM policies. Therefore, if the application layer does not embed the requester’s identity into the query key (e.g., using a composite primary key like PK = USER#userID and SK = PROFILE), there is no guarantee that a query for a given key belongs to the caller. A misconfigured IAM policy that is too permissive can further amplify the issue by allowing broad read or write access, which middleBrick flags under BOLA/IDOR and Property Authorization checks.

Another common vector in Fiber apps is when endpoints accept an ID in the body or query string to perform update or delete operations on DynamoDB items. If the handler does not re-check ownership — for example, by ensuring the authenticated subject matches the partition key in the request — an attacker can change any record simply by guessing or enumerating IDs. middleBrick’s BOLA/IDOR and BFLA/Privilege Escalation checks are designed to detect such patterns by probing endpoints with modified identifiers and inspecting whether authorization is consistently enforced across the unauthenticated surface.

Input Validation issues can also contribute to Broken Access Control. If an ID parameter is not strictly validated, an attacker might supply unexpected values that cause the application to fetch or modify unintended items. For instance, omitting type checks could allow an ID meant for one logical partition to be interpreted as another, leading to horizontal privilege escalation across user boundaries. middleBrick’s Input Validation and Data Exposure checks highlight these risks by fuzzing parameters and examining whether responses disclose data that should be restricted.

Finally, because DynamoDB is often used at scale with fine-grained access patterns, inconsistent authorization logic can span multiple endpoints, creating a systemic vulnerability. middleBrick’s per-category breakdown connects findings like IDOR, Property Authorization, and Unsafe Consumption to provide prioritized remediation guidance, helping developers understand how to align their DynamoDB access patterns with least-privilege principles defined in frameworks such as OWASP API Top 10.

To fix Broken Access Control when using DynamoDB with Fiber, ensure that every data access operation includes a server-side ownership check that ties the request to the authenticated subject. Below are concrete code examples that demonstrate a secure approach using the AWS SDK for Go with Fiber.

Secure route pattern with ownership check

Instead of trusting a client-supplied ID, derive the key from the authenticated user’s identity. This example assumes you have a JWT payload with a UserID claim and a DynamoDB table where the partition key is PK of the form USER#userID.

// Example: Fiber handler with ownership enforced
package main

import (
	"context"
	"github.com/gofiber/fiber/v2"
	"github.com/aws/aws-sdk-go-v2/service/dynamodb"
	"github.com/aws/aws-sdk-go-v2/service/dynamodb/types"
	"github.com/aws/aws-sdk-go-v2/feature/dynamodb/attributevalue"
)

type Profile struct {
	PK       string `json:"pk"`
	SK       string `json:"sk"`
	UserID   string `json:"user_id"`
	Name     string `json:"name""
	Email    string `json:"email"`
}

// getProfileHandler fetches the profile for the authenticated user only.
func getProfileHandler(db *dynamodb.Client) fiber.Handler {
	return func(c *fiber.Ctx) error {
		// Assume user identity is resolved from JWT or session
		userID := c.Locals("userID").(string)
		if userID == "" {
			return c.Status(fiber.StatusUnauthorized).JSON(fiber.Map{"error": "missing user identity"})
		}

		pk := "USER#" + userID
		key, err := attributevalue.MarshalMap(map[string]string{"PK": pk, "SK": "PROFILE"})
		if err != nil {
			return c.Status(fiber.StatusInternalServerError).JSON(fiber.Map{"error": "failed to build key"})
		}

		out, err := db.GetItem(c.Context(), &dynamodb.GetItemInput{
			TableName: aws.String("profiles"),
			Key:       key,
		})
		if err != nil {
			return c.Status(fiber.StatusInternalServerError).JSON(fiber.Map{"error": "database error"})
		}
		if out.Item == nil {
			return c.Status(fiber.StatusNotFound).JSON(fiber.Map{"error": "not found"})
		}

		var profile Profile
		if err := attributevalue.UnmarshalMap(out.Item, &profile); err != nil {
			return c.Status(fiber.StatusInternalServerError).JSON(fiber.Map{"error": "failed to decode"})
		}
		return c.JSON(profile)
	}
}

In this pattern, the handler never uses a client-provided user identifier to construct the DynamoDB key. Instead, the user ID comes from the authenticated context (e.g., JWT claims), and the key is built server-side, ensuring that users can only access their own items.

Updating another user’s data is blocked

An endpoint that accepts an ID in the URL or body must validate that the ID matches the authenticated subject before performing any DynamoDB operation. The following example shows a safe update pattern.

// Example: Safe update with ownership verification
func updateProfileHandler(db *dynamodb.Client) fiber.Handler {
	return func(c *fiber.Ctx) error {
		userID := c.Locals("userID").(string)
		var req struct {
			Name  string `json:"name"`
			Email string `json:"email"`
		}
		if err := c.BodyParser(&req); err != nil {
			return c.Status(fiber.StatusBadRequest).JSON(fiber.Map{"error": "invalid body"})
		}

		// Build key from authenticated user, not from request data
		pk := "USER#" + userID
		key, err := attributevalue.MarshalMap(map[string]string{"PK": pk, "SK": "PROFILE"})
		if err != nil {
			return c.Status(fiber.StatusBadRequest).JSON(fiber.Map{"error": "invalid user identifier"})
		}

		// Update only the attributes provided, ensuring no privilege escalation
		updateInput := &dynamodb.UpdateItemInput{
			TableName: aws.String("profiles"),
			Key:       key,
			UpdateExpression: aws.String("set #n = :name, email = :email"),
			ExpressionAttributeNames: map[string]string{"#n": "Name"},
			ExpressionAttributeValues: map[string]types.AttributeValue{
				":name":  &types.AttributeValueMemberS{Value: req.Name},
				":email": &types.AttributeValueMemberS{Value: req.Email},
			},
		}
		if _, err := db.UpdateItem(c.Context(), updateInput); err != nil {
			return c.Status(fiber.StatusInternalServerError).JSON(fiber.Map{"error": "update failed"})
		}
		return c.SendStatus(fiber.StatusOK)
	}
}

These examples enforce that all DynamoDB operations are scoped to the authenticated user’s partition key, mitigating IDOR and privilege escalation risks. middleBrick’s scans can validate that such checks exist by analyzing both the OpenAPI spec and runtime behavior, ensuring that endpoints do not allow unauthorized item access.

Additionally, apply least-privilege IAM policies for the service role used by Fiber, granting only the necessary DynamoDB actions (e.g., dynamodb:GetItem, dynamodb:UpdateItem) on the specific table and key patterns. Avoid wildcard permissions that would allow broad access across items or tables, which middleBrick flags under Permission checks.