Server Side Template Injection in Rocket with Mongodb

Server Side Template Injection (SSTI) in a Rocket application that uses MongoDB occurs when user-controlled data is embedded into a template and then interpreted as logic by the template engine. If the template engine supports dynamic evaluation or variable interpolation without proper escaping, an attacker can inject expressions that read or write data in the MongoDB instance. Rocket, a web framework for Rust, commonly integrates with templating engines such as Tera or Askama; misconfigured or overly permissive templates can expose data or behavior when untrusted input reaches the rendering layer.

For example, if a handler passes an unescaped query parameter directly into a template that can invoke functions or access nested fields, an attacker may attempt Tera-specific injections such as {{ config }} or {{ () }} to probe for runtime objects. While Rust’s type system and strict compile-time checks reduce the surface compared to dynamic languages, unsafe use of filters, custom functions, or serialization features can still lead to unintended data exposure. If the template has access to a MongoDB helper or a database handle, injected expressions might trigger additional queries or influence which documents are fetched, effectively turning SSTI into an indirect data exposure vector.

When templates deserialize or render MongoDB documents (e.g., BSON-derived structs) and include user input in computed fields or dynamic keys, the risk shifts toward property-level authorization issues and data exposure. An attacker might manipulate input to traverse nested paths (e.g., user.profile.email) or to trigger inclusion of sensitive fields that should have been filtered server-side. Because Rocket endpoints often map directly to MongoDB collections, a successful SSTI can expose entire documents or enable enumeration of usernames, roles, or configuration metadata depending on how the templates are designed. The combination of a powerful template engine, loose input validation, and direct data mapping to MongoDB structures amplifies impact.

Consider an endpoint that renders a user profile by name. If the route parameter flows into a template without strict allowlisting, an input like {{ user }}.roles might reveal privileged assignments when the template engine resolves the expression against the context object. Even without direct database access from the template, SSTI can facilitate secondary issues such as Mass Assignment or Authorization Bypass if the rendered output influences downstream logic. Therefore, validating and sanitizing all inputs, disabling unsafe eval features, and ensuring MongoDB queries rely on parameterized operations rather than interpolated values are essential mitigations.

middleBrick scans such scenarios as part of its 12 security checks, including Input Validation, Property Authorization, and Data Exposure, and surfaces findings with severity and remediation guidance. For teams using the CLI, running middlebrick scan <url> provides an immediate assessment; the Pro plan offers continuous monitoring to detect regressions, while the GitHub Action can fail builds if risk scores drop below a defined threshold.

To secure Rocket applications that interact with MongoDB, remove any direct interpolation of user input into templates and enforce strict schema-based access patterns. Use strongly typed request deserialization and ensure template contexts contain only intended, non-derived data. The following patterns illustrate safe practices.

1) Use Rocket's form and JSON extractors with serde to bind input, and pass only verified data to templates:

#[macro_use] extern crate rocket;

use rocket::serde::json::Json;
use rocket::response::content::Html;
use serde::Deserialize;

#[derive(Deserialize)]
struct ProfileQuery {
    user_id: String,
}

#[get("/profile")]
fn profile(query: Form, db: &State) -> Html {
    let user = db.collection("users").find_one(doc! { "user_id": &query.user_id }, None).unwrap_or_default();
    let ctx = tera::Context::from_serialize(json!({ "user": user })).unwrap();
    Html(render_template("profile.html", &ctx))
}

2) Configure Tera to disable unsafe filters and functions, and avoid exposing database handles to the template engine:

let mut tera = match Tera::new("templates/**/*") {
    Ok(t) => t,
    Err(e) => panic!("Failed to parse templates: {}", e),
};

// Ensure custom functions that could reach MongoDB are not registered
tera.set_escape_fn(|s| s.to_string());
// Do not register a function like db_handle or collection

3) Validate and allowlist paths used in rendering to prevent traversal via nested keys:

fn safe_render(value: &Document, template_name: &str) -> Result {
    let allowed_paths = vec!["user.name", "user.email", "user.settings.theme"];
    let filtered = value.iter().filter(|(k, _)| allowed_paths.contains(&k.as_str())).collect();
    let ctx = tera::Context::from_serialize(doc! { filtered }).unwrap();
    Ok(tera.render(template_name, &ctx)?)
}

4) Enforce MongoDB query patterns that rely on filters and projections rather than dynamic field selection driven by templates:

let filter = doc! { "user_id": user_id };
let projection = doc! { "name": 1, "email": 1, "_id": 0 };
let user = collection.find_one(filter, Some(doc! { "$project": projection })).unwrap_or_default();

These steps align with the checks in middleBrick’s Input Validation, Property Authorization, and Data Exposure categories. The Dashboard helps track scores over time, and the MCP Server enables scanning directly from AI coding assistants to catch unsafe patterns during development.