Cache Poisoning in Buffalo (Go)

Cache poisoning in a Buffalo application written in Go occurs when an attacker manipulates cache keys or cache-stored responses so that malicious or incorrect data is served to users. Because Buffalo is a convention-driven MVC framework for Go, it often uses URL paths, query parameters, and headers to construct cache keys in middleware or in application code. If these keys are derived from user-controlled input without normalization or strict validation, an attacker can force distinct requests to share the same cache entry, effectively poisoning the cache.

Consider a Buffalo action that caches a rendered fragment based on a query parameter without sanitizing it:

app.GET("/items", func(c buffalo.Context) error {
    category := c.Param("category")
    cacheKey := "items:" + category
    var cached string
    if app.Cache.Get(cacheKey, &cached); cached != "" {
        return c.Render(200, r.HTML(cached))
    }
    // render items...
    rendered := "
...
"
    app.Cache.Set(cacheKey, rendered, &cache.CacheOptions{ExpiresIn: 60})
    return c.Render(200, r.HTML(rendered))
})

An attacker can request /items?category=foo and then /items?category=foo%2C%20%3Cscript%3Eevil%3C%2Fscript%3E. If the cache key is built naively, the framework may treat these as the same entry in some cache backends, or a cache shared across users, leading to stored XSS via cache poisoning. Similarly, cache poisoning can occur via HTTP headers such as Accept-Language or Host if they are included in the cache key without canonicalization. Inconsistent normalization across instances in a cluster can amplify the impact, causing poisoned entries to spread.

Another scenario involves response cacheability headers set by Buffalo handlers or proxies. If a handler serving authenticated or private data fails to differentiate by session or token when constructing cache keys, private responses may be cached and subsequently served to other users through a poisoned cache key path. Because Buffalo does not automatically segregate cache entries by session, developers must explicitly include user roles or tenant identifiers in the cache key when needed. The framework’s flexibility with custom middleware means cache key construction logic can be spread across files; without centralized control, inconsistencies become likely.

To detect such issues, scans that compare OpenAPI specs with runtime behavior are valuable. For example, if the spec indicates that category is user-controlled but the cache implementation does not treat it as part of a varying key, a finding can be surfaced. Tools that perform black-box testing can probe endpoints with crafted headers and parameters to observe whether different users receive the same cached response, indicating potential poisoning. Continuous monitoring and CI/CD integration help catch regressions early, especially when new query parameters or headers are introduced that affect caching behavior.

Remediation focuses on ensuring cache keys are deterministic, scoped, and free of attacker-controlled injection vectors. In Buffalo, canonicalize inputs used in cache keys by trimming whitespace, enforcing a strict character set, and normalizing case. For the category example, explicitly validate the value against an allowlist and avoid concatenating raw user input into the key:

app.GET("/items", func(c buffalo.Context) error {
    category := c.Param("category")
    if !regexp.MustCompile(`^[a-z0-9-]+$`).MatchString(category) {
        return c.Error(400, errors.New("invalid category"))
    }
    userID := c.Session().Get("user_id")
    cacheKey := fmt.Sprintf("items:cat=%s:user=%v", category, userID)
    var cached string
    if app.Cache.Get(cacheKey, &cached); cached != "" {
        return c.Render(200, r.HTML(cached))
    }
    rendered := "
...
"
    app.Cache.Set(cacheKey, rendered, &cache.CacheOptions{ExpiresIn: 60})
    return c.Render(200, r.HTML(rendered))
})

Include tenant or role identifiers in the key when serving data that differs by context. If you use a shared cache backend, scope keys with a namespace or prefix that reflects the handler and the canonicalized parameters. Avoid relying on headers like Host or Accept-Language in cache keys unless you explicitly normalize and validate them.

Another important practice is to set appropriate cache control headers for private data. In Buffalo, you can set Cache-Control: no-store for responses containing sensitive information:

app.GET("/account", func(c buffalo.Context) error {
    // ... fetch private data
    c.Response().Header().Set("Cache-Control", "no-store")
    return c.Render(200, r.HTML(renderPrivateData))
})

Use the Buffalo middleware stack to centralize cache-related logic. For example, a custom middleware can sanitize and validate inputs before they reach action handlers, reducing inconsistencies across routes. With the CLI, you can run middlebrick scan <url> to validate that your deployed endpoints do not exhibit cache poisoning indicators. If you integrate the GitHub Action, you can fail builds when risky patterns are detected in code or configuration. For teams needing deeper analysis across many services, the Pro plan provides continuous monitoring and alerts when endpoints deviate from expected cache behavior.