Heap Overflow in Fiber with Api Keys

A heap-based buffer overflow in a Fiber application that handles API keys can occur when untrusted input is copied into fixed-size buffers on the heap without proper bounds checking. In Go, this pattern often arises when using byte slices or strings derived from request headers, query parameters, or environment variables that contain an API key. If the application allocates a small backing array or struct field to hold the key and then writes user-controlled data beyond that allocation, adjacent heap metadata can be corrupted. This can lead to arbitrary code execution, denial of service, or information disclosure, depending on how the corrupted memory is later interpreted.

Consider a handler that reads an API key from a header and stores it in a fixed-size structure:

type KeyStore struct {
    key [32]byte
}

func (ks *KeyStore) SetKey(input string) {
    copy(ks.key[:], input) // No length check
}

If the input string is longer than 32 bytes, copy will write past the end of the fixed-size array, corrupting heap memory. In a Fiber app, this might be triggered by an attacker-supplied Authorization header containing a long key. Because Fiber is a fast, minimalist web framework, developers may skip validation in favor of performance, increasing the likelihood of such unsafe patterns. The vulnerability is not in Fiber itself but in how the application manages memory when processing API keys, and it is especially dangerous when keys are used for authentication or signing operations.

An attacker who triggers this overflow may be able to overwrite function pointers, return addresses, or other critical data, potentially leading to unauthorized access to other endpoints or leakage of sensitive key material. Because API keys are high-value secrets, exploiting a heap overflow to extract or modify them can have severe security implications. This scenario aligns with common weaknesses listed in the OWASP API Security Top 10, particularly when insecure defaults or missing input validation allow oversized payloads to reach low-level memory operations.

Additionally, if the Fiber application logs or echoes API keys without sanitization, the overflow may facilitate data exposure by placing tainted data into logs or responses. The interplay between high-throughput frameworks like Fiber and low-level memory handling in Go makes it essential to validate and bound all external input, especially secrets such as API keys.

To prevent heap overflow when handling API keys in Fiber, enforce strict length limits and use safe copying functions. Replace fixed-size arrays with slices that grow to fit the input, or validate length before copying. Below is a secure version of the earlier example:

type KeyStore struct {
    key []byte
}

func (ks *KeyStore) SetKey(input string) error {
    if len(input) > 256 {
        return errors.New("api key too long")
    }
    ks.key = make([]byte, len(input))
    copy(ks.key, input)
    return nil
}

This approach ensures that the underlying slice is allocated with the exact required capacity, avoiding overflow. In a Fiber route, apply validation before storing or using the key:

func validateAPIKey(c *fiber.Ctx) error {
    key := c.Get("Authorization")
    if key == "" {
        return c.Status(fiber.StatusUnauthorized).SendString("missing key")
    }
    if len(key) > 256 {
        return c.Status(fiber.StatusBadRequest).SendString("invalid key length")
    }
    // Further checks, e.g., format or prefix validation
    return c.Next()
}

app.Get("/secure", validateAPIKey, func(c *fiber.Ctx) error {
    // Safe to use key within validated bounds
    return c.SendString("access granted")
})

For production usage, consider integrating the middleBrick scanner to detect unsafe memory handling patterns and other API security issues. The CLI tool allows you to run middlebrick scan <url> from your terminal to identify vulnerable endpoints, while the GitHub Action can enforce security gates in CI/CD pipelines. These features complement secure coding practices by providing continuous visibility into risks associated with API key handling and other attack surfaces.

Additionally, store keys securely using environment variables or secret managers, and avoid echoing them in responses or logs. Combine runtime validation with infrastructure-level protections to reduce the chance of memory corruption vulnerabilities affecting authentication workflows.