Bola Idor in Fiber with Dynamodb

Broken Object Level Authorization (BOLA) occurs when an API exposes object identifiers and fails to enforce that the requesting user is authorized to access a specific resource. In a Fiber application using Amazon DynamoDB as the persistence layer, this typically manifests when endpoint paths contain a record ID (e.g., /users/:id) but the server-side handler does not verify that the authenticated actor owns or is permitted to view that item.

Consider a typical route defined with Fiber that retrieves a user profile by ID without checking ownership:

app.Get('/users/:id', func(c *fiber.Ctx) error {
    id := c.Params('id')
    var user User
    err := dynamo.GetItem(&dynamodb.GetItemInput{
        TableName: aws.String("Users"),
        Key: map[string]awsmiddleware.RequestAttribute{
            "id": {S: aws.String(id)},
        },
    }, &user)
    if err != nil {
        return c.Status(fiber.StatusInternalServerError).JSON(fiber.Map{"error": err.Error()})
    }
    return c.JSON(user)
})

If the API relies solely on the ID provided by the client and does not confirm that the requesting user matches the retrieved user’s owner, an authenticated attacker can enumerate or manipulate IDs to access other users’ data. This is a classic BOLA/IDOR scenario: authorization is missing at the object level, even though the endpoint is protected by some form of authentication.

DynamoDB’s key-based model can inadvertently encourage this mistake. Because the primary key (partition key, or partition+sort key) directly maps to the ID in the route, developers might assume that retrieving by that key is sufficient for authorization. However, authorization is orthogonal to retrieval: you must implement checks that confirm the requester’s permission to that specific item. Additional risk vectors include horizontal privilege escalation (a user accessing another user’s same-type objects) and vertical escalation (an administrative role being impersonated via tampered identifiers).

Insecure use of DynamoDB conditional expressions or lack of ownership attributes exacerbates the issue. For example, if the table lacks a partition key that aligns with the user’s identity (e.g., a composite key like USER#123#profile), it becomes harder to enforce row-level constraints in the query itself, pushing authorization logic into application code where it can be omitted. Attack patterns such as ID enumeration, known as User Enumeration, often accompany BOLA and can reveal valid IDs through timing differences or error messages.

To summarize, BOLA in Fiber with DynamoDB emerges when route parameters are used as DynamoDB keys without verifying that the authenticated subject has the right to access that key. The vulnerability is not in DynamoDB itself but in the missing authorization checks in the Fiber handler, combined with a data model that makes object identification straightforward for attackers.

Remediation centers on ensuring that every data access includes an ownership or authorization check tied to the authenticated subject. Below are DynamoDB-specific patterns for Fiber that enforce BOLA protections.

1. Enforce ownership via the primary key

Design your DynamoDB table so that the partition key includes the user identifier. This enables efficient queries that are naturally scoped to the user, reducing the need for additional filtering. Then, in the handler, derive the key from the session or token rather than trusting the client-supplied ID.

app.Get('/my/profile', func(c *fiber.Ctx) error {
    // Assume user identity is resolved from a JWT or session
    userID := c.Locals("userID").(string)
    key := map[string]awsmiddleware.RequestAttribute{
        "pk": {S: aws.String("USER#" + userID)},
        "sk": {S: aws.String("PROFILE")},
    }
    var profile Profile
    err := dynamo.GetItem(&dynamodb.GetItemInput{
        TableName:           aws.String("UserData"),
        Key:                 key,
        ConsistentRead:      aws.Bool(true),
    }, &profile)
    if err != nil {
        return c.Status(fiber.StatusInternalServerError).JSON(fiber.Map{"error": err.Error()})
    }
    return c.JSON(profile)
})

By deriving the key from the authenticated user ID (from JWT claims or session), you ensure that users cannot tamper with the identifier to access other objects.

2. Verify ownership when IDs are client-supplied

If your use case requires accepting an ID, perform a conditional read that confirms ownership. For example, store a GSI (Global Secondary Index) that maps owner IDs, and include a condition on the requester’s subject in the query.

type Document struct {
    PK    string `json:"pk"`
    Owner string `json:"owner"`
    Data  string `json:"data"`
}

app.Get('/documents/:docID', func(c *fiber.Ctx) error {
    docID := c.Params('docID')
    userID := c.Locals("userID").(string)

    input := &dynamodb.GetItemInput{
        TableName: aws.String("Documents"),
        Key: map[string]awsmiddleware.RequestAttribute{
            "pk": {S: aws.String("DOC#" + docID)},
        },
    }
    var doc Document
    if err := dynamo.GetItem(input, &doc); err != nil {
        return c.Status(fiber.StatusInternalServerError).JSON(fiber.Map{"error": err.Error()})
    }
    if doc.Owner != userID {
        return c.Status(fiber.StatusForbidden).JSON(fiber.Map{"error": "access denied"})
    }
    return c.JSON(doc)
})

This pattern ensures that even if the client provides the document ID, the server verifies that the authenticated user is the owner stored in DynamoDB.

3. Use composite keys and conditional expressions

Leverage a composite primary key (partition + sort) to encode ownership and object type. Then, use a condition expression to assert ownership on writes or sensitive reads. Below is a safe update example:

updateInput := &dynamodb.UpdateItemInput{
    TableName: aws.String("UserData"),
    Key: map[string]awsmiddleware.RequestAttribute{
        "pk": {S: aws.String("USER#" + userID)},
        "sk": {S: aws.String("PROFILE")},
    },
    UpdateExpression: aws.String("set displayName = :val"),
    ConditionExpression: aws.String("attribute_exists(pk) AND attribute_exists(sk)"),
    ExpressionAttributeValues: map[string]awsmiddleware.RequestAttribute{
        ":val": {S: aws.String(c.Query().Get("displayName"))},
    },
}
_, err = dynamo.UpdateItem(updateInput)
if err != nil {
    return c.Status(fiber.StatusBadRequest).JSON(fiber.Map{"error": "conditional check failed"})
}

The condition expression here ensures you are updating an item that exists under the authenticated user’s key scope, adding a layer of defense against mis-scoped updates.

4. Prefer server-side pagination with filter on server

If listing resources that belong to a user, avoid returning all IDs to the client for selection. Instead, query with a key condition on the partition key that includes the user identifier, and apply any additional filters server-side.

queryInput := &dynamodb.QueryInput{
    TableName: aws.String("UserData"),
    KeyConditionExpression: aws.String("pk = :pk"),
    ExpressionAttributeValues: map[string]awsmiddleware.RequestAttribute{
        ":pk": {S: aws.String("USER#" + userID)},
    },
}
result, err := dynamo.Query(queryInput)
if err != nil {
    return c.Status(fiber.StatusInternalServerError).JSON(fiber.Map{"error": err.Error()})
}
// process result.Items on the server, do not rely on client-provided filters for ownership

These patterns align with the principle that authorization must be enforced on the server, using the data model to your advantage rather than relying on obscurity of IDs.