Identification Failures in Gin with Dynamodb

Identification failures occur when an API incorrectly identifies or infers a user or resource identity, leading to unauthorized access across different tenant boundaries. In Go APIs built with Gin, this often maps to the BOLA/IDOR category in middleBrick’s checks. When a Gin service uses Amazon DynamoDB as the data store, the risk intensifies if request parameters (such as an ID from the URL) are used directly to form DynamoDB queries without confirming that the resource belongs to the requesting user or tenant.

Consider a Gin endpoint defined as GET /users/:user_id/profile. If the handler extracts user_id from the URL and passes it straight to a DynamoDB GetItem or Query without verifying that the authenticated principal owns that user_id, the API may return another user’s profile. This is an Identification Failure because the identifier provided by the client is not cross-checked against the authenticated subject’s permissions or tenant context.

DynamoDB amplifies this when the primary key design uses a simple attribute like user_id as the partition key. A request that omits proper authorization checks can inadvertently or maliciously target any valid partition key value. Since DynamoDB does not enforce ownership semantics at the database level, the application must enforce this. MiddleBrick’s BOLA/IDOR check is designed to detect such missing authorization by correlating runtime requests with the OpenAPI specification and observing whether authorization checks precede data access patterns.

Insecure implementations might also use DynamoDB Scan with a filter on attributes like owner, which is both inefficient and unsafe if the filter value comes from user input without strict validation. An attacker could manipulate the filter to access other users’ data if input validation is weak, another vector flagged under Input Validation and Property Authorization checks in middleBrick. Similarly, if the API uses dynamic naming for DynamoDB tables (e.g., users_{tenant_id}) and derives the table name from an unverified parameter, it may lead to unintended data access or SSRF-like behaviors when combined with other weaknesses.

middleBrick’s OpenAPI/Swagger analysis helps surface these risks by resolving $ref definitions and comparing declared parameters with required security schemes. If the spec describes an user_id path parameter but does not enforce a security requirement that ties it to the authenticated identity, the scan will highlight a potential Identification Failure. This is especially important for DynamoDB because the database schema itself does not encode relationships or ownership; those must be encoded in the application design and verified during runtime testing.

Remediation focuses on ensuring that every DynamoDB operation validates the authenticated subject against the target resource. Below are concrete, realistic code examples for a Gin handler that safely retrieves a user profile from DynamoDB.

First, define a secure handler that extracts the authenticated user from the Gin context (e.g., via JWT claims) and uses it to scope the DynamoDB request. Never trust URL parameters alone.

// models/profile.go
package models

type Profile struct {
	UserID   string `json:"user_id"`
	Name     string `json:"name"`
	Email    string `json:"email"`
	Bio      string `json:"bio,omitempty"`
}

// handlers/profile.go
package handlers

import (
	"context"
	"net/http"
	"yourproject/models"

	"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"
	"github.com/gin-gonic/gin"
)

// GetProfileForCurrentUser retrieves a profile only if the authenticated user owns it.
func GetProfileForCurrentUser(client *dynamodb.Client) gin.HandlerFunc {
	return func(c *gin.Context) {
		// Assume authentication middleware has set this in context
		currentUser, exists := c.Get("user")
		if !exists {
			c.JSON(http.StatusUnauthorized, gin.H{"error": "unauthorized"})
			return
		}
		claims := currentUser.(models.Claims)
		requestedUserID := c.Param("user_id")

		// Enforce ownership: the requested ID must match the authenticated user’s ID
		if requestedUserID != claims.UserID {
			c.JSON(http.StatusForbidden, gin.H{"error": "access denied"})
			return
		}

		// Safe DynamoDB GetItem scoped to the authenticated user’s partition key
		resp, err := client.GetItem(c.Request.Context(), &dynamodb.GetItemInput{
			TableName: aws.String("profiles"),
			Key: map[string]types.AttributeValue{
				"user_id": &types.AttributeValueMemberS{Value: requestedUserID},
			},
		})
		if err != nil {
			c.JSON(http.StatusInternalServerError, gin.H{"error": "database error"})
			return
		}
		if resp.Item == nil {
			c.JSON(http.StatusNotFound, gin.H{"error": "not found"})
			return
		}

		var profile models.Profile
		if err := mapDynamoItemToProfile(resp.Item, &profile); err != nil {
			c.JSON(http.StatusInternalServerError, gin.H{"error": "mapping error"})
			return
		}
		c.JSON(http.StatusOK, profile)
	}
}

// mapDynamoItemToProfile converts a DynamoDB attribute map to a Profile.
func mapDynamoItemToProfile(item map[string]types.AttributeValue, profile *models.Profile) error {
	if v, ok := item["user_id"].(*types.AttributeValueMemberS); ok {
		profile.UserID = v.Value
	}
	if v, ok := item["name"].(*types.AttributeValueMemberS); ok {
		profile.Name = v.Value
	}
	if v, ok := item["email"].(*types.AttributeValueMemberS); ok {
		profile.Email = v.Value
	}
	if v, ok := item["bio"].(*types.AttributeValueMemberS); ok {
		profile.Bio = v.Value
	}
	return nil
}

This pattern ensures that the user_id from the URL is compared to the authenticated identity before any DynamoDB call. For multi-tenant designs, use a composite key such as tenant_id#user_id as the partition key and validate both tenant and user claims.

Additionally, avoid using DynamoDB Scan for ownership checks; prefer query patterns with an index on owner if necessary, but always filter on server-side attributes that are derived from authenticated context rather than raw user input. middleBrick’s CLI can be used to scan your Gin endpoints from the terminal with middlebrick scan <url>, while the GitHub Action can enforce a minimum score in CI/CD pipelines to prevent regressions.