Vulnerable Components in Fiber with Dynamodb

When building APIs with Fiber and DynamoDB, several architectural patterns common in Go applications can unintentionally expose attack surfaces. One frequent pattern is constructing DynamoDB key expressions directly from user-supplied route parameters without validation. For example, a handler that uses path parameters as partition key values can become susceptible to IDOR if the caller is not verified against the intended resource ownership.

Consider a user profile endpoint defined as GET /users/:userID. If the handler builds a DynamoDB query using :userID as the partition key without confirming the requesting identity matches that ID, an attacker can enumerate arbitrary user IDs and access profiles they should not see. This maps directly to the BOLA/IDOR checks that middleBrick runs as one of its 12 parallel security validations, highlighting how a simple routing choice can create an authorization bypass.

Additionally, query construction that concatenates strings to form filter expressions can lead to injection-style issues when input is not strictly typed or constrained. A handler that appends raw query parameters into a FilterExpression can inadvertently expose unexpected attributes or cause evaluation errors that change behavior in unsafe ways. This is especially risky when combined with DynamoDB’s pagination and projection behavior, where missing validation on limit or exclusive start key parameters can lead to data exposure beyond intended pages.

DynamoDB’s attribute type flexibility can also interact poorly with unchecked JSON input. If a Fiber handler deserializes request bodies into interface{} and then passes values directly to DynamoDB expression attribute values, type mismatches between `{"S": "value"}` and `{"N": "123"}` can cause runtime errors or inconsistent state. Such inconsistencies can be leveraged to probe schema details or trigger unhandled errors that leak stack traces, supporting findings related to Input Validation and Data Exposure that middleBrick reports with severity and remediation guidance.

Another subtle issue arises when using DynamoDB conditional writes without fully validating the condition expressions. A handler that applies optimistic concurrency control using a version attribute must ensure the version value is sourced from trusted state rather than user input. If an attacker can control the version attribute supplied to Expected, they may bypass checks and force writes that should be rejected, aligning with BFLA/Privilege Escalation patterns that middleBrick tests through active probes.

Finally, the combination of unauthenticated endpoints and overly permissive IAM policies attached to the Lambda or service executing the Fiber app can amplify DynamoDB-related risks. If the runtime credentials allow broad table access and the API does not enforce authentication, middleBrick’s Unauthenticated LLM endpoint detection and Authorization checks can surface excessive permissions and missing enforcement points, producing actionable findings tied to OWASP API Top 10 and compliance frameworks like SOC2 and PCI-DSS.

To harden Fiber services that interact with DynamoDB, start by validating and scoping all input used in key and filter construction. Use strongly typed structures instead of interface{} where possible, and enforce allowlists for known attribute values. The following example demonstrates a safer pattern for retrieving a user profile by ID while ensuring the requester context is considered.

package main

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

type UserProfile struct {
    UserID string `json:"userID"`
    Name   string `json:"name"`
    Email  string `json:"email"`
}

func GetUserProfile(ddbClient *dynamodb.Client, tableName string) fiber.Handler {
    return func(c *fiber.Ctx) error {
        userID := c.Params("userID")
        if userID == "" {
            return c.Status(http.StatusBadRequest).JSON(fiber.Map{"error": "userID is required"})
        }
        // Enforce ownership if authentication is available, omitted here for brevity
        input := &dynamodb.GetItemInput{
            TableName: &tableName,
            Key: map[string]types.AttributeValue{
                "userID": &types.AttributeValueMemberS{Value: userID},
            },
        }
        out, err := ddbClient.GetItem(c.Context(), input)
        if err != nil {
            return c.Status(http.StatusInternalServerError).JSON(fiber.Map{"error": "unable to fetch profile"})
        }
        if out.Item == nil {\n            return c.Status(http.StatusNotFound).JSON(fiber.Map{"error": "not found"})
        }
        var profile UserProfile
        // deserialize out.Item into profile, handling type assertions safely
        // ...
        return c.JSON(profile)
    }
}

This pattern avoids string concatenation for key construction and uses explicit parameter mapping to reduce injection risks. For queries that involve filtering, prefer expression attribute values over inline string assembly to prevent type confusion.

When implementing conditional writes, bind expected values from verified state rather than raw user input. The following snippet shows a version check that uses a value read from the database, not supplied by the client.

package main

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

func UpdateProfileWithVersion(ddbClient *dynamodb.Client, tableName string) error {
    // Assume currentItem was fetched and version extracted
    currentItem := map[string]types.AttributeValue{
        "userID": &types.AttributeValueMemberS{Value: "u-123"},
        "version": &types.AttributeValueMemberN{Value: "2"},
    }
    input := &dynamodb.UpdateItemInput{
        TableName: &tableName,
        Key: map[string]types.AttributeValue{
            "userID": &types.AttributeValueMemberS{Value: "u-123"},
        },
        UpdateExpression: aws.String("set #nm = :nm, #v = :v"),
        ConditionExpression: aws.String("attribute_exists(#v) AND #v = :expectedVersion"),
        ExpressionAttributeNames: map[string]string{
            "#nm": "name",
            "#v":  "version",
        },
        ExpressionAttributeValues: map[string]types.AttributeValue{
            ":nm": &types.AttributeValueMemberS{Value: "new name"},
            ":v":  &types.AttributeValueMemberN{Value: "3"},
            ":expectedVersion": &types.AttributeValueMemberN{Value: "2"},
        },
    }
    _, err := ddbClient.UpdateItem(c.Context(), input)
    return err
}

Additionally, enforce least-privilege IAM for the runtime identity used by Fiber. Scope table access to specific actions and resources, and avoid wildcards in condition keys. These steps reduce the impact of any misconfiguration and align with the remediation guidance provided by middleBrick’s Pro plan continuous monitoring, which can track configuration drift over time.