Injection Flaws in Fiber with Dynamodb

Injection flaws in a Fiber service that uses DynamoDB typically arise when input from HTTP requests is directly interpolated into DynamoDB operations, such as constructing ExpressionAttributeValues or passing raw user input into KeyConditionExpression or FilterExpression. Unlike SQL, DynamoDB does not support string interpolation in expressions, but unsafe usage patterns—such as concatenating request parameters into query keys or conditionals—can lead to unexpected behavior, privilege escalation, or exposure of unintended data.

With DynamoDB, injection-like issues are often misuse of the SDK rather than classic query injection, but they can still lead to security outcomes such as reading or modifying other users’ items (BOLA/IDOR) or bypassing intended access controls. In a Fiber application, routes may directly bind parameters from ctx.Params or ctx.Query into DynamoDB API calls without validation or normalization, creating an unauthenticated attack surface that middleBrick tests as part of its BOLA/IDOR and Input Validation checks.

For example, a vulnerable endpoint might use the request parameter userID to build a GetItem key without verifying that the caller is authorized for that ID. Because DynamoDB operations are typed, passing unexpected input types or malformed expressions can cause runtime errors or inconsistent filtering, which may be leveraged in combination with other weaknesses (e.g., missing rate limiting) to probe the API surface. middleBrick’s unauthenticated scanning detects these patterns by analyzing the OpenAPI spec and runtime behavior, identifying endpoints where user-controlled input reaches DynamoDB operations without authorization checks.

Real-world related attack patterns include insecure direct object references and over-privileged IAM roles assigned to the service, which can amplify the impact of injection-like misuse. While DynamoDB’s expression syntax does not allow arbitrary code execution, incorrect usage can lead to data exposure or privilege escalation consistent with OWASP API Top 10 categories such as Broken Object Level Authorization and Injection. middleBrick’s LLM/AI Security checks do not apply to DynamoDB itself, but they do help identify adjacent risks like prompt injection when endpoints also integrate language models.

Specific DynamoDB conditions that can become problematic in Fiber include failing to validate partition key and sort key types, not using ExpressionAttributeNames to prevent reserved keyword conflicts, and constructing expressions with unchecked string concatenation. These issues are detectable through spec analysis and runtime testing, and they map to compliance frameworks such as OWASP API Top 10 and SOC2. By scanning your Fiber endpoints with middleBrick, you can identify these injection-like risks before they are exploited in production.

To remediate injection-like issues in a Fiber service using DynamoDB, validate and sanitize all inputs before they reach DynamoDB operations, and use the SDK’s built-in expression constructs rather than string building. Prefer prepared statements and strongly typed parameters, and apply least-privilege IAM policies to limit the scope of each operation.

Below are concrete, working code examples for Fiber handlers that safely interact with DynamoDB using the AWS SDK for Go (v2). These examples emphasize input validation, use of expression attribute names and values, and proper error handling that avoids leaking sensitive information.

Example 1: Safe GetItem by user ID with ownership check

Ensure the requesting user is authorized for the target ID, and use ExpressionAttributeValues to avoid injection-like issues. Do not concatenate user input into the key.

// Assuming: type UserItem struct { UserID string `json:"userID"; dynamodbav:"userID" }
func GetUserItem(c *fiber.Ctx) error {
    userID := c.Params("userID")
    if userID == "" {
        return c.Status(fiber.StatusBadRequest).JSON(fiber.Map{"error": "userID is required"})
    }
    // In a real app, compare against authenticated user identity instead of trusting the client
    if !isValidUserID(userID) {
        return c.Status(fiber.StatusForbidden).JSON(fiber.Map{"error": "access denied"})
    }
    input := &dynamodb.GetItemInput{
        TableName: aws.String("UserItems"),
        Key: map[string]types.AttributeValue{
            "PK": &types.AttributeValueMemberS{Value: "USER#" + userID},
            "SK": &types.AttributeValueMemberS{Value: "METADATA"},
        },
    }
    result, err := dbClient.GetItem(context.TODO(), input)
    if err != nil {
        // Log detailed error internally, return generic message externally
        return c.Status(fiber.StatusInternalServerError).JSON(fiber.Map{"error": "unable to fetch item"})
    }
    var item UserItem
    if err := attributevalue.UnmarshalMap(result.Item, &item); err != nil {
        return c.Status(fiber.StatusInternalServerError).JSON(fiber.Map{"error": "data error"})
    }
    return c.JSON(item)
}

func isValidUserID(id string) bool {
    // Basic pattern validation; tighten as needed
    return len(id) > 0 && len(id) <= 64
}

Example 2: Query with ExpressionAttributeNames and ExpressionAttributeValues

Use expression attribute names for reserved keywords and expression attribute values for all user input. Avoid building expression strings via concatenation.

func QueryUserItems(c *fiber.Ctx) error {
    userID := c.Params("userID")
    if userID == "" {
        return c.Status(fiber.StatusBadRequest).JSON(fiber.Map{"error": "userID is required"})
    }
    input := &dynamodb.QueryInput{
        TableName:              aws.String("UserItems"),
        KeyConditionExpression: aws.String("#pk = :pkVal"),
        ExpressionAttributeNames: map[string]string{
            "#pk": "PK", // avoid collisions with reserved words
        },
        ExpressionAttributeValues: map[string]types.AttributeValue{
            ":pkVal": &types.AttributeValueMemberS{Value: "USER#" + userID},
        },
    }
    result, err := dbClient.Query(context.TODO(), input)
    if err != nil {
        return c.Status(fiber.StatusInternalServerError).JSON(fiber.Map{"error": "query failed"})
    }
    var items []UserItem
    for _, raw := range result.Items {
        var item UserItem
        if err := attributevalue.UnmarshalMap(raw, &item); err != nil {
            continue // skip malformed items or handle specifically
        }
        items = append(items, item)
    }
    return c.JSON(fiber.Map{"items": items})
}

General remediation practices

• Validate and sanitize all inputs: enforce type, length, and pattern constraints before using them in DynamoDB calls.
• Use ExpressionAttributeNames for field names and ExpressionAttributeValues for values; never interpolate user input into expression strings.
• Apply least-privilege IAM policies so that the service identity can only perform required actions on specific resources.
• Leverage middleBrick’s CLI to scan from terminal (middlebrick scan <url>) and its GitHub Action to add API security checks to your CI/CD pipeline, failing builds if risk scores exceed your threshold.
• For continuous monitoring, consider the Pro plan which offers scheduled scans and alerts, helping you catch regressions before they reach production.