Broken Authentication in Fiber with Dynamodb

Broken Authentication in a Fiber application that uses Dynamodb typically arises from a mismatch between session handling practices and how identity data is stored and retrieved. When authentication state is managed server-side (for example in a Redis cache or database) but the lookup key is derived from user input without strict validation, attackers can manipulate identifiers to reference arbitrary Dynamodb records.

In a typical setup, a login route might validate credentials against a Dynamodb table where the partition key is a user ID or email. If the application uses a predictable or user-supplied value to form the key, such as userID from a JWT or query parameter without verifying ownership, an attacker can perform IDOR-like behavior across users. For instance, an attacker who knows another user’s email might directly query the same Dynamodb table with that email, bypassing session checks if the endpoint does not re-validate the session context.

Another common pattern involves storing sensitive authentication artifacts, such as password reset tokens or MFA secrets, as item attributes in Dynamodb. If these items are not properly isolated per user or lack sufficient access controls at the application layer, an authenticated user who can list or query items might enumerate other users’ tokens. This can lead to account takeover when combined with weak token entropy or missing rate limiting on token verification endpoints.

Middleware that attaches a user identity to the request context based on a token or session ID can also introduce risk if the mapping to Dynamodb keys is implicit. For example, trusting a decoded JWT’s sub field to build a Dynamodb key without server-side session validation allows an attacker who obtains or guesses a valid token to assume another identity. Additionally, if the application exposes administrative endpoints that query Dynamodb with insufficient permission checks, the combination of weak authorization and a globally accessible data store can amplify the impact of Broken Authentication.

These risks are detectable by middleBrick’s authentication and BOLA/IDOR checks, which correlate runtime behavior with OpenAPI/Swagger definitions and Dynamodb access patterns. The scanner flags endpoints where authentication state is not re-validated against the data store and where identity-based access controls are implicit rather than explicit.

To remediate Broken Authentication when using Dynamodb with Fiber, enforce strict ownership checks and avoid relying on client-supplied identifiers for data access. Use server-generated user identifiers or verified attributes, and ensure every Dynamodb query is backed by proper session or token validation.

Example: secure login and token-based authentication with explicit key construction.

// Assume a users table with partition key `email`
// and a sessions table with partition key `session_id`

import "github.com/gofiber/fiber/v2"
import "github.com/aws/aws-sdk-go-v2/service/dynamodb"
import "github.com/aws/aws-sdk-go-v2/feature/dynamodb/attributevalue"
import "github.com/google/uuid"

// After validating credentials, create a session stored in Dynamodb
func handleLogin(c *fiber.Ctx) error {
    var creds struct {
        Email    string `json:"email"`
        Password string `json:"password"`
    }
    if err := c.BodyParser(&creds); err != nil {
        return c.Status(fiber.StatusBadRequest).JSON(fiber.Map{"error": "invalid request"})
    }

    // Verify credentials against the users table using the email as partition key
    user, err := getUserByEmail(creds.Email)
    if err != nil || !checkPassword(creds.Password, user.PasswordHash) {
        return c.Status(fiber.StatusUnauthorized).JSON(fiber.Map{"error": "invalid credentials"})
    }

    sessionID := uuid.NewString()
    _, err = svc.PutItem(c.Context, &dynamodb.PutItemInput{
        TableName: aws.String("sessions"),
        Item: map[string]types.AttributeValue{
            "session_id": &types.AttributeValueMemberS{Value: sessionID},
            "user_email": &types.AttributeValueMemberS{Value: creds.Email},
        },
    })
    if err != nil {
        return c.Status(fiber.StatusInternalServerError).JSON(fiber.Map{"error": "unable to create session"})
    }

    c.Cookie(&fiber.Cookie{
        Name:     "session_id",
        Value:    sessionID,
        HTTPOnly: true,
        Secure:   true,
    })
    return c.JSON(fiber.Map{"status": "ok"})
}

// Verify session on each request by looking up the session in Dynamodb
func verifySession(c *fiber.Ctx) (string, error) {
    cookie, err := c.Cookies("session_id")
    if err != nil {
        return "", err
    }
    var session struct {
        SessionID string
        UserEmail string
    }
    err = attributevalue.UnmarshalMap(getItemBySessionID(cookie).Item, &session)
    if err != nil {
        return "", err
    }
    // Ensure the session exists and is tied to the authenticated user context
    return session.UserEmail, nil
}

// Example of a protected endpoint that re-validates identity against Dynamodb
func getUserData(c *fiber.Ctx) error {
    userEmail, err := verifySession(c)
    if err != nil {
        return c.Status(fiber.StatusUnauthorized).JSON(fiber.Map{"error": "invalid session"})
    }

    // Use the verified email to fetch user-specific data
    user, err := getUserByEmail(userEmail)
    if err != nil {
        return c.Status(fiber.StatusInternalServerError).JSON(fiber.Map{"error": "unable to load user"})
    }
    return c.JSON(user)
}

// Helper to fetch a user by email (partition key) — this should be called after session validation
func getUserByEmail(email string) (*types.MapOutput, error) {
    // Implementation that calls GetItem with Key built from verified email
    // Avoid using user-supplied values directly as keys without verification
    return nil, nil
}

Additional remediation steps include enforcing least-privilege IAM roles for the Dynamodb client, enabling encryption at rest, and applying fine-grained access policies. For API security posture, middleBrick’s continuous monitoring (Pro plan) can track changes in authentication-related endpoints and alert on deviations. The GitHub Action can fail builds when a scan detects missing ownership checks, while the MCP Server allows developers to validate API contracts and security findings directly from their IDE.