Server Side Template Injection in Buffalo with Mongodb

Server Side Template Injection (SSTI) in the Buffalo framework when interacting with MongoDB occurs when user-controlled input is passed into server-side templates that also influence MongoDB queries. Buffalo uses Go’s html/template and text/template packages; if templates render user input without proper escaping or validation, attackers can inject template logic. When those templates or their parameters affect how queries are built— for example, injecting field names, collection names, or influencing conditional logic that changes query structure— the application may expose MongoDB operations in an unsafe way.

Consider a scenario where a Buffalo handler dynamically selects a field name based on a query parameter and uses it inside a template that also drives a MongoDB filter. If the field name is not strictly whitelisted, an attacker can inject template actions that alter the resulting map passed to MongoDB, potentially bypassing intended filters or causing information disclosure. For instance, template injection can inject map keys or values that change the query’s behavior, leading to sensitive data exposure or unexpected query paths. In a Black-box scan using middleBrick, such endpoints would be flagged under Property Authorization and Input Validation checks, with findings tied to the OWASP API Top 10 and categorized as high severity due to unauthorized data access risks.

An example pattern that can be vulnerable in Buffalo is building a MongoDB filter map in Go and then passing it to a template for rendering context, where the template inadvertently re-uses user input. If the template uses variable variables or includes user-controlled strings in map construction, malicious payloads like {{ .UserInput }} could modify structure in ways that affect downstream query logic. middleBrick’s LLM/AI Security checks do not apply here because this is a server-side injection issue, but the scanner’s Input Validation and Property Authorization tests would surface the unsafe data flow. The risk is compounded when templates are used to generate dynamic query structures, and there is no strict schema validation on the data sent to MongoDB.

To illustrate a vulnerable handler, consider a Buffalo action that takes a field name from the request and uses it to construct a MongoDB filter without strict allowlisting, then passes data to a template for rendering:

// vulnerable_handler.go
package actions

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

func ShowUser(c buffalo.Context) error {
	col := db.Collection("users") // assuming db is available
	field := c.Param("field")     // user-controlled
	filter := bson.M{field: c.Param("value")}
	var result bson.M
	if err := col.FindOne(c.Request().Context(), filter).Decode(&result); err != nil {
		return c.Render(500, r.JSON(err))
	}
	return c.Render(200, r.JSON(result))
}

If the field parameter is not validated, an attacker could supply a payload such as {'$ne': ''} or use template injection if the parameter is later rendered in a template context, altering the effective query. middleBrick’s BOLA/IDOR and Property Authorization checks would highlight the missing allowlist as a finding, emphasizing the need for strict schema controls around field names and values passed to MongoDB.

Remediation focuses on strict allowlisting, avoiding dynamic construction of queries with user input, and ensuring templates do not influence MongoDB logic. Always validate field names and values against a known set, and construct filters programmatically rather than through templates.

Use a hardcoded mapping for allowed fields and build the filter explicitly in Go code, keeping user input as values only, never as keys or operators. Here is a secure Buffalo handler example:

// secure_handler.go
package actions

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

var allowedFields = map[string]bool{
	"email": true,
	"name":  true,
	"role":  true,
}

func ShowUserSecure(c buffalo.Context) error {
	col := db.Collection("users")
	field := c.Param("field")
	value := c.Param("value")

	if !allowedFields[field] {
		return c.Render(400, r.JSON(buffalo.Error{
			Code:    "invalid_field",
			Message: errors.New("field not allowed").Error(),
		}))
	}

	filter := bson.M{field: value}
	var result bson.M
	if err := col.FindOne(c.Request().Context(), filter).Decode(&result); err != nil {
		if err == mongo.ErrNoDocuments {
			return c.Render(404, r.JSON(buffalo.Error{
				Code:    "not_found",
				Message: errors.New("user not found").Error(),
			}))
		}
		return c.Render(500, r.JSON(err))
	}
	return c.Render(200, r.JSON(result))
}

Additionally, if rendering user data in HTML templates is necessary, always use html/template auto-escaping and never inject raw map keys from user input. For MongoDB operations, prefer building filters directly in Go and avoid passing request-derived strings into template functions that might affect query construction. middleBrick’s CLI can be used to verify remediation by rescans; for example, run middlebrick scan <url> to confirm that the input validation findings are resolved.

Complement development practices with continuous monitoring if using the Pro plan, which supports scheduled scans and alerts. The GitHub Action can enforce a maximum risk score threshold in CI/CD, preventing deployments that reintroduce insecure patterns. This approach ensures that SSTI-related issues tied to MongoDB are caught before reaching production, aligning with secure coding standards and reducing reliance on post-deployment fixes.