Vulnerable Components in Fiber with Firestore

When building HTTP APIs with Go Fiber and Firestore, the application surface spans both runtime request handling and cloud data-plane operations. A typical handler retrieves a document using a value taken directly from the URL, for example an :id parameter, without validating ownership or context. Because Firestore rules are not a substitute for application-level authorization, this pattern can expose Document reads or writes that should be gated behind authentication or tenant boundaries, leading to Insecure Direct Object References (IDOR) or BOLA (Broken Level Authorization).

Firestore-specific risks in this stack include over-permissive rules and unbounded queries. If rules allow read access based only on document existence or a simple field claim, and the Fiber handler does not re-assert the requester’s tenant or user ID, an attacker can enumerate valid document IDs and access data belonging to other users. This often maps to OWASP API Top 10 #1 (Broken Object Level Authorization) and can be surfaced by middleBrick as a BOLA/IDOR finding.

Another vector arises from unsafe query construction where user input is used directly in Firestore field filters. If a handler builds a query using user-controlled keys without allowlisting fields, an attacker may supply operators or malformed paths that change query semantics or trigger excessive document reads, contributing to data exposure or elevated impact. Firestore indexes are global; malformed compound queries can consume unnecessary resources and amplify denial-of-service risk. middleBrick’s Property Authorization and Input Validation checks highlight these issues by correlating the OpenAPI schema with runtime query patterns and flagged Firestore operations.

LLM/AI Security considerations appear when development workflows or generated documentation embed Firestore credentials or endpoint details into prompts. middleBrick’s LLM/AI Security checks detect system prompt leakage patterns and active prompt injection probes, ensuring that secrets stored in Firestore documents or environment configuration are not inadvertently exposed through AI tooling. This is particularly relevant when teams use AI assistants to scaffold handlers that reference Firestore collections without scrubbing sensitive context.

Finally, Data Exposure and Encryption checks verify that sensitive Firestore documents are not returned in full to clients and that transport encryption is enforced by the service. A handler that returns entire Firestore documents without masking fields such as email, UID, or internal status codes increases the impact of any IDOR flaw. middleBrick correlates these findings with the OpenAPI spec and runtime calls, providing prioritized remediation steps aligned with compliance frameworks such as OWASP API Top 10 and SOC2.

Remediation centers on strict authorization, bounded queries, and input validation before any Firestore interaction. In Fiber, apply middleware that resolves the authenticated user or tenant and ensure every Firestore path includes this context. For example, instead of querying a users collection with an uncontrolled ID, bind the document path to the tenant and user ID:

// tenantID from verified middleware context, userID from JWT
userRef := client.Collection("tenants").Doc(tenantID).Collection("users").Doc(userID)
ctx := context.Background()
doc, err := userRef.Get(ctx)
if err != nil {
    c.Status(404).JSON([])
    return
}
if !doc.Exists() {
    c.Status(404).JSON([])
    return
}
// Explicitly return only safe fields
c.JSON([
    "uid": doc.Get("uid"),
    "email": doc.Get("email"),
])

To prevent IDOR/BOLA, always include the tenant scope in collection group queries. This ensures a user cannot accidentally or maliciously read another tenant’s documents:

tenantID := c.Locals("tenant_id").(string)
iter := client.Collection("tenants").Doc(tenantID).Collection("items").Where("status", "==", "active").Documents(ctx)
defer iter.Stop()
for {
    doc, err := iter.Next())
    if err == iterator.Done {
        break
    }
    if err != nil {
        c.Status(500).JSON(&{"error": "failed to list items"})
        return
    }
    // safe projection
    c.JSON = append(c.JSON, map[string]interface{}{
        "item_id": doc.Ref.ID,
        "name":   doc.Get("name"),
    })
}

Validate and allowlist all user input used in Firestore field paths or filter keys. Do not concatenate raw parameters into field names; use a map of allowed keys to Firestore field names:

allowedSortFields := map[string]string{
    "createdAt": "created_at",
    "name":      "name",
}
sortBy, ok := allowedSortFields[query.Get("sortBy")]
if !ok {
    sortBy = "created_at"
}
_, err := client.Collection("items").OrderBy(sortBy, firestore.Asc).Limit(50).Documents(ctx).GetAll()
if err != nil {
    c.Status(500).JSON(&{"error": "cannot retrieve items"})
    return
}

Apply Firestore security rules as a defense-in-depth layer, but do not rely on them for authorization in Fiber. Rules should enforce tenant isolation and condition-based writes, while the application continues to validate identities and perform per-request checks. Use Firestore’s built-in request.auth to tie rules to UID, and ensure your Fiber middleware supplies the same UID context for server-side operations.

middleBrick’s scans help identify missing tenant scoping, unsafe query patterns, and overly permissive rules. With the Pro plan, you can enable continuous monitoring so new endpoints or Firestore rule changes are evaluated automatically, and the GitHub Action can fail builds when a risk score drops below your configured threshold.