Ssrf Server Side in Buffalo with Mongodb

Server-side request forgery (SSRF) in a Buffalo application that uses MongoDB can arise when user-controlled input is used to construct both HTTP requests and MongoDB operations. For example, a developer might accept a URL from an API client, fetch remote metadata, and then store or query data in MongoDB based on that remote response. If the URL is not strictly validated and the MongoDB queries embed values derived from the fetched remote content, an attacker can influence internal service calls and potentially manipulate database operations.

Consider a scenario where an endpoint accepts a remote configuration URL, retrieves settings, and upserts them into a MongoDB collection keyed by a user identifier. If the remote URL is attacker-controlled and the fetched JSON is merged into database update operations without strict schema enforcement, SSRF can be coupled with injection-like behavior against MongoDB. The risk is not direct NoSQL injection through query syntax, but rather data-driven manipulation of what is stored or queried, especially when field names or values originate from external sources.

Buffalo’s request handling pipeline can inadvertently pass through headers, query parameters, or body fields into HTTP clients and MongoDB drivers if validation is incomplete. For instance, using a user-supplied hostname in an HTTP client call that later determines which collection or document to update can expose internal services. Attackers may leverage internal endpoints that are not publicly routable, and if the MongoDB operations depend on the results of those internal calls, unauthorized data access or modification may follow.

Real-world patterns include fetching an OpenID provider configuration over HTTPS and using embedded claims to select a MongoDB tenant identifier. If the provider URL is not restricted and the claims are trusted without verification, an attacker can direct the server to interact with arbitrary tenant collections. Additionally, if the application retries or logs failed requests using data from the remote response, sensitive information may be exposed through logs or secondary channels.

To detect such issues, middleBrick scans an API’s unauthenticated surface and can surface SSRF indicators alongside MongoDB interaction patterns. When paired with OpenAPI/Swagger spec analysis (with full $ref resolution), the scanner cross-references runtime behavior against declared schemas to highlight discrepancies. This is valuable for Buffalo applications where specification-driven design may not fully account for dynamic data flows between HTTP and database layers.

Remediation centers on strict input validation, schema enforcement, and separation of data paths. Never use raw user input to determine MongoDB collections, documents, or update fields. Use parameterized queries and avoid constructing queries by string interpolation, even with trusted sources.

Example: safely resolving a tenant identifier without reflecting untrusted data into database operations.

// Safe: tenantID is validated against a known list, never derived from remote content.
package actions

import (
	"context"
	"github.com/gobuffalo/buffalo"
	"go.mongodb.org/mongo-driver/bson"
	"go.mongodb.org/mongo-driver/mongo"
)

func GetTenantConfig(c buffalo.Context) error {
	tenantID := c.Param("tenant_id")
	// Validate against an allowlist or lookup via authenticated session.
	if !isValidTenant(tenantID) {
		return c.Error(400, "invalid tenant")
	}

	client := c.Value("mongoClient").(*mongo.Client)
	collection := client.Database("main").Collection("tenant_configs")

	// Use a static collection name; do not inject tenantID into collection.
	var cfg bson.M
	if err := collection.FindOne(c.Request().Context(), bson.M{"id": tenantID}).Decode(&cfg); err != nil {
		if err == mongo.ErrNoDocuments {
			return c.Error(404, "not found")
		}
		return c.Error(500, "database error")
	}

	c.Set("config", cfg)
	return c.Render(200, r.JSON(cfg))
}

func isValidTenant(id string) bool {
	allowed := map[string]bool{"tenant_a": true, "tenant_b": true, "tenant_c": true}
	return allowed[id]
}

Example: performing an upsert with a fixed schema and no external field names.

// Safe: fields are hardcoded; values are validated before use.
func UpsertProfile(c buffalo.Context) error {
	userID := c.Param("user_id")
	var payload struct {
		DisplayName string `json:"display_name"`
		Email       string `json:"email"`
	}
	if err := c.Bind(&payload); err != nil {
		return c.Error(400, "invalid body")
	}

	// Validate format before database interaction.
	if payload.DisplayName == "" || !isValidEmail(payload.Email) {
		return c.Error(400, "validation failed")
	}

	client := c.Value("mongoClient").(*mongo.Client)
	collection := client.Database("main").Collection("profiles")

	// Use defined field names; do not construct keys from input.
	filter := bson.M{"user_id": userID}
	update := bson.M{
		"$set": bson.M{
			"display_name": payload.DisplayName,
			"email":        payload.Email,
			"updated_at":   timeNow(),
		},
	}
	opts := options.Update().SetUpsert(true)
	if _, err := collection.UpdateOne(c.Request().Context(), filter, update, opts); err != nil {
		return c.Error(500, "database error")
	}

	return c.Render(200, r.JSON(map[string]string{"status": "ok"}))
}

func isValidEmail(email string) bool {
	// Simple example; use a robust validator in production.
	return strings.Contains(email, "@")
}

Additional measures: enforce allowlists for hostnames and paths when making HTTP requests, disable redirects to internal services, and avoid using remote data to decide local database operations. middleBrick’s LLM/AI Security checks can also help detect prompt injection or excessive agency patterns if your API interacts with language models that could influence MongoDB behavior.