Xpath Injection in Flask with Firestore

XPath Injection occurs when untrusted input is concatenated into an XPath expression without proper sanitization or parameterization, allowing an attacker to alter the query logic. While XPath is commonly associated with XML documents, it can also appear in backend logic that queries structured data stores through custom XPath-based access layers. In a Flask application using Firestore, this risk arises when developers build dynamic queries by interpolating user-controlled values into XPath-like selectors or query parameters, especially when integrating Firestore data with XML transformations or custom indexing logic that relies on path expressions.

Flask, as a lightweight Python web framework, does not enforce any specific query pattern for Firestore, leaving developers responsible for safely constructing all queries. If user input such as a document ID, field name, or filter value is directly embedded into an XPath-style string used to traverse Firestore document hierarchies—either through custom business logic or third-party libraries that expose XPath-like interfaces—an attacker can inject additional path segments or predicates. For example, a path like /users/{user_id}/profile could become /users/attacker_id/profile or /users/123/profile and //admin if input is not validated, potentially accessing unauthorized documents.

Because Firestore does not natively support XPath, the injection typically occurs in application-level code that interprets user input as part of a path-based access control or data retrieval mechanism. A Flask route that dynamically builds a Firestore document path using string formatting is vulnerable if the input is not strictly validated or encoded. Consider a route that retrieves user settings using a user-supplied key: path = f'/users/{user_input}/settings'. If user_input contains malicious path traversal or logical operators, the resulting query may bypass intended access controls or expose sensitive documents.

Moreover, when combined with Firestore’s flexible data model, an injected path can lead to enumeration attacks, where an attacker iterates through document IDs or namespace prefixes to discover sensitive collections. Even though Firestore enforces authentication rules, misconfigured security rules combined with XPath-style path manipulation can allow access to data that should be restricted. The risk is compounded if the Flask app exposes endpoints that return raw document paths or metadata, which can be leveraged to refine injection payloads.

To detect such issues, middleBrick performs black-box scanning of the unauthenticated attack surface and tests input vectors that could manipulate path-based logic. It checks for improper concatenation of user input into query-like structures and flags endpoints where XPath-style expressions are constructed dynamically. The scanner maps findings to the OWASP API Top 10 and provides severity-ranked remediation guidance, helping teams identify whether their Firestore integration introduces path traversal or injection risks.

Securing Flask applications that interact with Firestore requires strict validation and canonicalization of any user-controlled data used in document paths or query construction. The primary defense is to avoid string-based path assembly entirely and instead use Firestore’s native SDK methods with explicit document references.

Instead of building paths via string interpolation, always use the Firestore client to reference documents by ID after validating and sanitizing the input. For example, if your route accepts a user ID, ensure it matches an expected pattern (e.g., alphanumeric) and use db.collection('users').document(user_id) directly rather than constructing a path string.

from flask import Flask, request, jsonify
import firebase_admin
from firebase_admin import credentials, firestore
import re

app = Flask(__name__)
cred = credentials.Certificate('service-account.json')
firebase_admin.initialize_app(cred)
db = firestore.client()

@app.route('/user-settings')
def get_user_settings():
    user_id = request.args.get('user_id')
    # Validate user_id to allow only safe characters
    if not re.match(r'^[a-zA-Z0-9_-]{1,30}$', user_id):
        return jsonify({'error': 'Invalid user ID'}), 400
    doc_ref = db.collection('users').document(user_id).collection('settings').document('profile')
    doc = doc_ref.get()
    if doc.exists:
        return jsonify(doc.to_dict())
    else:
        return jsonify({'error': 'Not found'}), 404

This approach ensures that the document path is constructed safely by the Firestore SDK, eliminating the risk of path injection. Additionally, always enforce strict allow-lists for identifiers and avoid using user input as field names or collection names.

For more complex queries, use Firestore’s built-in query methods with explicit field filters instead of dynamic path traversal. If your application requires XML transformations that rely on XPath, process those transformations server-side using trusted data only, and never pass raw user input into XPath evaluators. middleBrick’s scans can help identify endpoints where unsafe string formatting is used, and the Pro plan enables continuous monitoring to prevent regressions in API behavior.