Information Disclosure in Buffalo with Dynamodb

Information disclosure occurs when an API unintentionally exposes data that should remain restricted. In Buffalo applications using Amazon DynamoDB as the persistence layer, this typically arises from insufficient authorization checks on data access patterns and unsafe data handling in API responses.

Buffalo applications often interact with DynamoDB via the AWS SDK for Go. If route handlers construct DynamoDB requests using user-supplied identifiers without validating that the authenticated subject owns the corresponding item, an attacker can manipulate identifiers to access other users' records. This is a classic Broken Object Level Authorization (BOLA) / Insecure Direct Object Reference (IDOR) pattern. For example, an endpoint like /users/:userID/profile that directly substitutes :userID into a DynamoDB GetItem key without verifying that the authenticated user matches :userID enables horizontal privilege escalation.

DynamoDB-specific configurations can inadvertently contribute to disclosure. A table with a simple partition key design might store multiple tenants' data under the same partition key value if tenant identifiers are not enforced at query time. If a query uses a filter expression to narrow results but relies on the client to specify the tenant ID, an attacker supplying a different tenant ID in the request could see cross-tenant data if the filter is misapplied or if the application mistakenly treats a missing result as an absence of data rather than an authorization failure. Sensitive attributes like internal status flags or debugging fields may be included in the DynamoDB item attributes; if the application serializes the entire item into JSON for the API response, those fields can leak to clients.

The risk is compounded when the Buffalo app uses DynamoDB Scan operations for convenience rather than targeted Query operations. Scans read every item in a table or secondary index and can expose large volumes of data if pagination and filtering are not strictly enforced. Insecure defaults in the SDK, such as returning all item attributes, may lead to accidental exposure of fields that should be omitted, such as password hashes, API keys, or personal identifiable information (PII). Responses that include raw DynamoDB attribute value notation, such as S for string or N for number, can also leak schema details to attackers, aiding further reconnaissance.

Common attack patterns observed in real assessments include tampering URL path or query parameters to increment IDs, cycling through UUIDs, or leveraging predictable string identifiers to enumerate valid resources. If the API does not implement rate limiting or robust authentication checks on these endpoints, the attack surface is expanded. MiddleBrick scans detect these issues by comparing the unauthenticated attack surface against expected authorization boundaries and flagging endpoints where data exposure is evident in the response payloads.

Remediation focuses on enforcing ownership checks, tightening query patterns, and ensuring responses expose only intended data. Always validate the authenticated subject against the resource identifier before constructing any DynamoDB request. Use parameterized queries with condition expressions rather than client-supplied filters to enforce tenant and ownership boundaries server-side.

Below is a concrete example of a secure Buffalo handler using the AWS SDK for Go v2. The handler retrieves a profile for the authenticated user by deriving the user ID from the session, ensuring no user-controlled ID is used directly.

import (
    "context"
    "net/http"
    "github.com/aws/aws-sdk-go-v2/aws"
    "github.com/aws/aws-sdk-go-v2/service/dynamodb"
    "github.com/aws/aws-sdk-go-v2/service/dynamodb/types"
)

func ProfileHandler(db *dynamodb.Client) http.HandlerFunc {
    return func(w http.ResponseWriter, r *http.Request) {
        // Assume sessionUser is derived from authenticated session, not from URL
        sessionUser := r.Context().Value("user").(string)
        pk := "USER#" + sessionUser

        out, err := db.GetItem(r.Context(), &dynamodb.GetItemInput{
            TableName: aws.String("AppTable"),
            Key: map[string]types.AttributeValue{
                "PK": &types.AttributeValueMemberS{Value: pk},
                "SK": &types.AttributeValueMemberS{Value: "PROFILE"},
            },
            // Explicitly limit returned attributes to avoid exposing sensitive fields
            ProjectionExpression: aws.String("username,email,displayName"),
        })
        if err != nil {
            http.Error(w, "Unable to load profile", http.StatusInternalServerError)
            return
        }
        if out.Item == nil {
            http.Error(w, "Not found", http.StatusNotFound)
            return
        }
        // Serialize only safe fields
        type SafeProfile struct {
            Username    string `json:"username"`
            Email       string `json:"email"`
            DisplayName string `json:"displayName"`
        }
        var resp SafeProfile
        if v, ok := out.Item["username"].(*types.AttributeValueMemberS); ok {
            resp.Username = v.Value
        }
        if v, ok := out.Item["email"].(*types.AttributeValueMemberS); ok {
            resp.Email = v.Value
        }
        if v, ok := out.Item["displayName"].(*types.AttributeValueMemberS); ok {
            resp.DisplayName = v.Value
        }
        // Encode and write response
    }
}

For listing items, prefer Query with a partition key that includes tenant context, and apply a FilterExpression as a final safeguard, not as the primary access control.

listInput := &dynamodb.QueryInput{
    TableName: aws.String("AppTable"),
    KeyConditionExpression: aws.String("PK = :pk"),
    FilterExpression:      aws.String("tenantId = :tid"),
    ExpressionAttributeValues: map[string]types.AttributeValue{
        ":pk":  &types.AttributeValueMemberS{Value: "USER#alice"},
        ":tid": &types.AttributeValueMemberS{Value: "tenant123"},
    },
    ProjectionExpression: aws.String("id,status,createdAt"),
}

Avoid Scan operations unless absolutely necessary; if used, restrict TotalSegments and apply aggressive filtering. Never return raw DynamoDB attribute descriptors in API responses; map to a defined DTO (Data Transfer Object) that includes only fields intended for the client. This approach aligns with findings tracked by MiddleBrick scans, where the tool surfaces data exposure risks and provides remediation guidance tied to frameworks such as OWASP API Top 10 and compliance mappings.