Race Condition in Fiber

Race conditions in Fiber applications occur when multiple concurrent requests manipulate shared state without proper synchronization. These timing-dependent bugs can lead to data corruption, privilege escalation, and authentication bypass vulnerabilities that are notoriously difficult to reproduce and debug.

In Fiber, race conditions commonly manifest in endpoint handlers that perform sequential operations on shared resources. Consider a banking application where a user's account balance is checked before performing a transfer:

app.Get("/transfer", func(c *fiber.Ctx) error {
    userID := c.Query("user_id")
    amount := c.Query("amount")
    
    // Race condition: balance check and update not atomic
    balance := getBalanceFromDB(userID)
    if balance >= amount {
        updateBalance(userID, balance - amount)
        return c.SendString("Transfer successful")
    }
    return c.SendString("Insufficient funds")
})

Two concurrent requests can both read the same balance before either completes the update, allowing an attacker to transfer more funds than available. This pattern appears frequently in Fiber applications handling inventory management, payment processing, and user state modifications.

Another Fiber-specific race condition occurs in middleware that maintains request-scoped state across asynchronous operations. When using Fiber's context with goroutines:

app.Post("/process", func(c *fiber.Ctx) error {
    userID := c.Locals("user_id").(string)
    
    // Race condition: goroutine captures context reference
    go func() {
        // This goroutine might execute after the response is sent
        logTransaction(userID, "processed")
    }()
    
    return c.SendString("Processing started")
})

The goroutine may access stale or modified context data, leading to incorrect logging, authorization bypass, or data leakage between users.

Detecting race conditions in Fiber requires both static analysis and runtime testing. middleBrick's black-box scanning approach is particularly effective for identifying these vulnerabilities without requiring source code access.

middleBrick tests for race conditions by sending concurrent requests to the same endpoint with varying parameters. For the transfer endpoint example, it would:

• Send multiple concurrent requests with the same user ID and amount
• Verify that the final state matches expected atomic behavior
• Check for inconsistent responses that indicate timing-dependent bugs
• Analyze response times for patterns suggesting non-atomic operations

The scanner specifically looks for Fiber's common patterns including:

// Non-atomic operations middleBrick flags
func updateProfile(c *fiber.Ctx) error {
    userID := c.Locals("user_id").(string)
    profile := new(Profile)
    
    // Two separate DB operations = race condition window
    db.First(&profile, "user_id = ?", userID)
    profile.Email = c.FormValue("email")
    db.Save(&profile) // Another goroutine could modify profile here
    
    return c.JSON(fiber.Map{"status": "updated"})
}

middleBrick's LLM security module also detects race conditions in AI-powered Fiber applications where concurrent requests might manipulate model state or prompt context:

app.Post("/chat", func(c *fiber.Ctx) error {
    // Race condition: shared prompt context
    systemPrompt := getSystemPrompt()
    userMessage := c.FormValue("message")
    
    // Multiple requests could interleave here
    response := generateResponse(systemPrompt + "\n" + userMessage)
    return c.JSON(fiber.Map{"response": response})
})

The scanner identifies these patterns and provides specific remediation guidance for Fiber applications, including recommendations for using database transactions, mutex locks, or atomic operations.

Fixing race conditions in Fiber requires understanding Go's concurrency model and Fiber's request lifecycle. The most effective approach is using database transactions to ensure atomic operations:

app.Post("/transfer", func(c *fiber.Ctx) error {
    userID := c.Query("user_id")
    amount := c.Query("amount")
    
    tx := db.Begin()
    defer tx.Rollback()
    
    var account Account
    tx.First(&account, "user_id = ?", userID)
    
    if account.Balance >= amount {
        account.Balance -= amount
        tx.Save(&account)
        tx.Commit()
        return c.SendString("Transfer successful")
    }
    
    return c.SendString("Insufficient funds")
})

For in-memory state synchronization, Fiber applications should use Go's sync package:

import "sync"

var inventoryMutex sync.RWMutex
var inventory = make(map[string]int)

app.Post("/purchase", func(c *fiber.Ctx) error {
    itemID := c.Query("item_id")
    quantity := c.Query("quantity")
    
    inventoryMutex.Lock()
    defer inventoryMutex.Unlock()
    
    if inventory[itemID] >= quantity {
        inventory[itemID] -= quantity
        return c.JSON(fiber.Map{"status": "purchased"})
    }
    
    return c.JSON(fiber.Map{"status": "out of stock"})
})

For goroutine-based operations in Fiber middleware, use channels or context cancellation to prevent race conditions:

app.Post("/process", func(c *fiber.Ctx) error {
    userID := c.Locals("user_id").(string)
    
    // Use channel to synchronize goroutine completion
    done := make(chan bool)
    
    go func() {
        logTransaction(userID, "processed")
        done <- true
    }()
    
    // Wait for goroutine or timeout
    select {
    case <-done:
        return c.SendString("Processing completed")
    case <-time.After(5 * time.Second):
        return c.SendString("Processing timeout")
    }
})

middleBrick's CLI tool can verify these fixes by running the same concurrent tests against your remediated endpoints:

middlebrick scan https://your-api.com/transfer \
  --concurrent-requests 10 \
  --test-parameters "user_id=123&amount=100"

The scanner will confirm whether race conditions have been eliminated and provide a updated security score reflecting the improved atomicity of your operations.