Double Free in Fiber with Dynamodb

A Double Free occurs when a program attempts to free the same memory region more than once. In the context of a Fiber application interfacing with DynamoDB, this typically arises from improper management of request-scoped objects or SDK resources across concurrent requests. Fiber is a fast, unopinionated web framework written in Go, and DynamoDB is a fully managed NoSQL database service. The combination can expose memory safety issues when developers inadvertently share references to request-bound resources or when SDK client configurations are reused incorrectly across goroutines.

Consider a handler that initializes a DynamoDB client per request rather than reusing a shared client. If the client or associated session objects are explicitly released (e.g., via custom cleanup logic or deferred functions that call close or similar teardown routines) and then the same reference is invoked again within the same request lifecycle—perhaps due to middleware retries or sub-handler calls—the runtime may attempt to free the underlying C memory allocations twice. This can corrupt the heap and lead to undefined behavior, including crashes or potential code execution paths. The concurrency model of Fiber, where each request runs in its own goroutine, can amplify the risk if synchronization around resource lifecycle is insufficient.

Moreover, when integrating with DynamoDB, developers might use low-level SDK operations that return internal buffers or byte slices. If these are passed through multiple processing layers and explicitly deallocated in one layer while another layer still holds a reference, a Double Free can occur. For example, unmarshalling a DynamoDB attribute into a struct and then manually managing the backing byte arrays with custom free logic can trigger this flaw. The unauthenticated attack surface of a Fiber service interacting with DynamoDB often includes misconfigured endpoints or overly permissive CORS settings, which an attacker could leverage to induce repeated or malformed requests that increase the likelihood of hitting such a memory management bug.

Even when using the official AWS SDK for Go (v2), which manages memory automatically, Double Free risks can still emerge through misuse of context cancellation and request retries. If a developer hooks into the request lifecycle with custom middleware that cancels and re-spawns DynamoDB operations without properly isolating state, the underlying HTTP transport might attempt to release network buffers multiple times. This is especially relevant when the SDK is configured with custom retry modes or when response payloads are read into pre-allocated buffers that are returned to a pool and then freed again inadvertently.

To detect such issues, scanning a Fiber endpoint that interacts with DynamoDB using a black-box approach can reveal patterns like missing idempotency tokens, inconsistent error handling around retries, or exposed internal structures in error messages. These indicators do not confirm a Double Free, but they highlight configuration choices that could enable memory corruption when combined with specific runtime conditions. The scanner checks, including Input Validation, Property Authorization, and Unsafe Consumption, help surface risky request handling practices that may contribute to memory safety issues in this stack.

To mitigate Double Free risks in a Fiber application using DynamoDB, focus on correct client lifecycle management and avoiding manual memory handling. The safest approach is to create a single, shared DynamoDB client at application startup and reuse it across all requests. This eliminates repeated allocations and deallocations that can trigger Double Free scenarios. Below is a concrete example of initializing the AWS SDK for Go (v2) with DynamoDB in a Fiber app.

// main.go
package main

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

func main() {
    // Initialize a shared DynamoDB client once
    cfg, err := config.LoadDefaultConfig(context.TODO(), config.WithRegion("us-west-2"))
    if err != nil {
        panic("unable to load SDK config")
    }
    client := dynamodb.NewFromConfig(cfg)

    app := fiber.New()

    app.Get("/items/:id", func(c *fiber.Ctx) error {
        // Use the shared client for each request
        id := c.Params("id")
        input := &dynamodb.GetItemInput{
            TableName: aws.String("ItemsTable"),
            Key: map[string]aws.AttributeValue{
                "Id": &aws.StringAttributeValue{Value: id},
            },
        }
        resp, err := client.GetItem(c.Context(), input)
        if err != nil {
            return c.Status(fiber.StatusInternalServerError).JSON(fiber.Map{
                "error": err.Error(),
            })
        }
        return c.JSON(resp)
    })

    app.Listen(":3000")
}

This pattern ensures that the SDK’s internal buffers and HTTP transports are allocated once and safely reused. Avoid creating per-request clients or calling close-like operations on the client or its underlying HTTP transport, as this can introduce the conditions for a Double Free.

Additionally, review any custom middleware that manipulates request contexts or retries logic. Ensure that retries do not cause the same request body or context to be reused after it has been released. For example, when implementing retry logic, always create a new context derived from the original rather than reusing a canceled context that might free underlying resources prematurely.

For DynamoDB-specific operations, prefer high-level SDK constructs that abstract away buffer management. If you must work with raw byte slices or custom allocators, ensure that ownership semantics are clear and that no explicit free routines are invoked on objects that may still be referenced elsewhere in the request pipeline. The scanner’s checks on Input Validation and Unsafe Consumption can help identify places where such risky patterns might exist in your Fiber endpoints.

Finally, leverage the CLI tool to scan your endpoints regularly: middlebrick scan <your-fiber-endpoint-url>. The tool can flag insecure configurations, missing validation, and patterns that may lead to memory handling issues, including those related to DynamoDB integrations. Upgrading to the Pro plan enables continuous monitoring and CI/CD integration to catch regressions before they reach production.