Insecure Design in Chi with Mongodb

Insecure Design in a Chi application that uses Mongodb often arises from how routes, handlers, and data access patterns are structured before code is ever written. Chi is a minimalistic HTTP router that encourages small handler functions, but if route parameters are passed directly into Mongodb queries without validation or transformation, the application surface becomes prone to injection and authorization issues.

Consider a route defined as /users/{id}. If the handler retrieves the path parameter id and uses it to build a Mongodb filter like { _id: req.URLParam("id") }, the design assumes the client-supplied value is safe. Because Chi does not sanitize or type-check route parameters by default, this design permits injection of invalid ObjectId values or unexpected query expressions. An attacker can supply values such as 64c0a1b2e9b1a87d5e2f3c4d || { $where: "return true" } or manipulate string inputs to produce skewed queries, effectively testing the boundary between application logic and data retrieval.

Another dimension of insecure design is the lack of schema enforcement and query scoping. Mongodb is schemaless by nature, which means developers must explicitly enforce constraints in application code. If handlers fetch user data without verifying ownership or tenant context, the design may allow horizontal privilege escalation across user boundaries. For example, a handler that executes usersCollection.FindOne(ctx, bson.M{"_id": id}) without confirming that the authenticated subject is authorized to view that id exposes a BOLA/IDOR flaw rooted in design. Similarly, endpoints that return full documents including internal fields such as passwordHash or apiKey reflect a design oversight around data exposure, because Mongodb queries can inadvertently project sensitive fields if projection is not explicitly set.

Insecure Design also manifests in how logging, error handling, and retry logic are structured around Mongodb interactions. Chi handlers that expose stack traces or raw database errors can leak internal query shapes or field names, aiding reconnaissance. If retry loops or caching layers are introduced without considering idempotency or injection boundaries, the design may amplify injection opportunities. For instance, concatenating user input into a JSON string that is later evaluated by a script interface or passed to a dynamic lookup can create paths for injection that are not obvious at the route level.

Because middleBrick scans the unauthenticated attack surface, it can detect endpoints where route parameters flow into Mongodb queries without validation, where responses expose sensitive fields, or where authorization checks are missing. The scanner’s checks for Input Validation, Property Authorization, and Data Exposure highlight these design-level weaknesses by observing runtime behavior, such as whether overly permissive queries return other users’ data or whether error responses reveal internal structure. These findings do not imply that Chi or Mongodb are insecure; rather, they show how certain design choices in this combination can expand the attack surface when security controls are omitted.

Developers can mitigate these risks by adopting strict input validation, using typed identifiers, and explicitly defining data access boundaries before writing handler logic. Tools that provide runtime analysis alongside design reviews, such as middleBrick, can surface these insecure patterns early, enabling teams to adjust architecture decisions rather than relying on post-deployment fixes.

Secure design for Chi with Mongodb centers on validating inputs, constraining queries, and enforcing authorization at the handler level. Below are concrete patterns and code examples that address the issues described above.

• Validate and convert route parameters to ObjectId: Before using an id from the URL, parse it into a proper ObjectId. This prevents injection of malformed queries and ensures type safety.

import (
    "context"
    "net/http"
    "github.com/go-chi/chi/v5"
    "go.mongodb.org/mongo-driver/bson"
    "go.mongodb.org/mongo-driver/bson/primitive"
    "go.mongodb.org/mongo-driver/mongo"
)

func getUserHandler(usersCollection *mongo.Collection) http.HandlerFunc {
    return func(w http.ResponseWriter, r *http.Request) {
        idStr := chi.URLParam(r, "id")
        id, err := primitive.ObjectIDFromHex(idStr)
        if err != nil {
            http.Error(w, `{"error": "invalid user id"}`, http.StatusBadRequest)
            return
        }
        var user struct {
            ID   primitive.ObjectID `bson:"_id"`
            Name string             `bson:"name"`
        }
        err = usersCollection.FindOne(r.Context(), bson.M{"_id": id}).Decode(&user)
        if err != nil {
            http.Error(w, `{"error": "not found"}`, http.StatusNotFound)
            return
        }
        // encode user as JSON response
    }
}

• Enforce ownership checks to prevent BOLA/IDOR: Always scope queries by the authenticated subject, not only by the provided identifier.

func getUserDataHandler(usersCollection *mongo.Collection) http.HandlerFunc {
    return func(w http.ResponseWriter, r *http.Request) {
        userID := chi.URLParam(r, "id")
        subjectID := r.Context().Value("user_id").(string) // from auth middleware
        objID, err := primitive.ObjectIDFromHex(userID)
        if err != nil || subjectID == "" {
            http.Error(w, `{"error": "invalid request"}`, http.StatusBadRequest)
            return
        }
        filter := bson.M{
            "_id": objID,
            "owner_id": subjectID,
        }
        var data bson.M
        err = usersCollection.FindOne(r.Context(), filter).Decode(&data)
        if err != nil {
            http.Error(w, `{"error": "access denied"}`, http.StatusForbidden)
            return
        }
        // return limited projection excluding secrets
    }
}

• Use explicit projections to limit data exposure: Do not rely on default query behavior that may return sensitive fields.

projection := bson.M{
    "name": 1,
    "email": 1,
    "_id": 1,
    // do not include passwordHash, apiKey, internal flags
}
err = usersCollection.FindOne(r.Context(), filter, mongo.FindOneOptions{Projection: projection}).Decode(&user)

• Apply input validation and schema checks: Use struct-based validation or a library to ensure only expected formats reach the database layer.

import "gopkg.in/go-playground/validator.v9"

var validate = validator.New()

type UserQuery struct {
    Email string validate:"required,email"
}

func listUsersHandler(usersCollection *mongo.Collection) http.HandlerFunc {
    return func(w http.ResponseWriter, r *http.Request) {
        var q UserQuery
        if err := decodeAndValidate(r, &q); err != nil {
            http.Error(w, `{"error": "validation failed"}`, http.StatusBadRequest)
            return
        }
        cursor, err := usersCollection.Find(r.Context(), bson.M{"email": q.Email})
        // handle cursor safely
    }
}

• Ensure idempotent operations and safe error handling: Do not leak stack traces or internal query details in responses, and design handlers to avoid side effects on invalid input.

By embedding these patterns into Chi handlers, developers reduce the risk of injection, limit data exposure, and align the design with secure-by-default principles. middleBrick’s scans can verify whether these controls are effective in runtime by checking for improper query scoping, missing projections, and unauthenticated endpoints that expose sensitive data.