Ldap Injection in Flask with Dynamodb

Ldap Injection occurs when an attacker can manipulate LDAP query construction, typically via unsanitized user input. In a Flask application that uses LDAP for authentication or group membership checks, if input is concatenated directly into LDAP filter strings, malicious payloads can alter the query logic. When this Flask service also stores or references user data in Amazon DynamoDB, the combination exposes two related risks: LDAP injection against the identity provider and data exposure or unauthorized access via DynamoDB due to over-permissive IAM policies or insecure data modeling.

Consider a Flask route that takes a username from a login form and builds an LDAP filter to validate credentials. If the input is used without escaping or strict allowlisting, an attacker can inject special characters such as *, ), or ( to bypass authentication or retrieve additional attributes. Because the application trusts the LDAP response to grant access, a successful injection can cause the server to bind as a privileged user or query unintended entries. Meanwhile, DynamoDB might store user metadata, roles, or mappings (e.g., LDAP DN to IAM role). If the application derives access control decisions from this DynamoDB data without additional authorization checks, a compromised LDAP query can lead to retrieving or modifying sensitive DynamoDB items.

For example, an attacker might supply uid=*)(uid=admin as the username. If the Flask code builds a filter like (&(uid={username})(objectClass=person)), the resulting LDAP filter becomes (&(uid=*)(uid=admin)(objectClass=person)), which can return multiple or all entries depending on server configuration. If the Flask app then queries DynamoDB using the attacker-supplied identifier to fetch group memberships, insecure IAM permissions or a lack of row-level security may allow reading other users’ records. This illustrates how LDAP injection and DynamoDB access can interact to amplify impact.

Additionally, DynamoDB’s schema-less design can inadvertently store sensitive attributes that, when exposed through an LDAP-injected path, are returned to the attacker. For instance, if user objects in DynamoDB contain fields such as password_hash or secret_key, and the application returns these fields in error messages or logs after a malformed LDAP query, sensitive data may be leaked. Therefore, securing the Flask-LDAP-DynamoDB pipeline requires input validation, strict filter construction, and tightly scoped IAM policies for DynamoDB access.

To mitigate Ldap Injection in Flask when using DynamoDB, adopt strict input validation, parameterized queries, and least-privilege IAM. Never concatenate user input into LDAP filters. Instead, use an LDAP library that supports parameterized filters or explicitly escape special characters. For DynamoDB, avoid deriving access control solely from LDAP-derived identifiers; enforce authorization checks and use IAM roles scoped to specific table operations and attributes.

Below are concrete remediation steps with code examples for a Flask application.

• Validate and sanitize input: Use a strict allowlist for usernames (e.g., alphanumeric and a limited set of characters). Reject anything that does not match the pattern before using it in LDAP or DynamoDB operations.
• Use parameterized LDAP queries: Configure your LDAP connection to use parameterized filters or escape reserved characters. For example, with the ldap3 library, prefer placeholders over string interpolation.
• Scope DynamoDB access with IAM: Ensure the IAM role associated with your Flask application has only the necessary permissions (e.g., dynamodb:GetItem on specific partition keys) and use conditions to restrict access by LDAP-derived user identifiers when appropriate.
• Separate authentication from data retrieval: Use LDAP strictly for authentication (bind) and retrieve permissions from DynamoDB using a verified, canonical user identifier that is not influenced by attacker input.

Example: Secure Flask route with parameterized LDAP and DynamoDB access

import re
from flask import Flask, request, jsonify
import boto3
from ldap3 import Server, Connection, ALL, SUBTREE

app = Flask(__name__)

# Input validation: allowlist usernames (alphanumeric and underscore)
def is_valid_username(username):
    return re.match(r'^[a-zA-Z0-9_]{1,64}$', username) is not None

# Parameterized LDAP bind (no string interpolation in filter)
def ldap_authenticate(username, password):
    server = Server('ldap://ldap.example.com', get_info=ALL)
    # Use parameterized filter via ldap3's safe construction
    conn = Connection(server, user=f'uid={username},ou=people,dc=example,dc=com', password=password)
    if not conn.bind():
        return None
    # After bind, fetch canonical user ID safely
    if conn.search('ou=people,dc=example,dc=com', f'(uid={username})', attributes=['uid', 'dn']):
        entry = conn.entries[0]
        return entry.entry_dn
    return None

# DynamoDB access with scoped IAM permissions and canonical ID
def get_user_permissions(dynamodb_table_name, user_dn):
    # In practice, map user_dn to a canonical user ID stored in DynamoDB
    # Use a GSI or a dedicated PK/SK design to avoid scanning
    dynamodb = boto3.resource('dynamodb')
    table = dynamodb.Table(dynamodb_table_name)
    try:
        response = table.get_item(Key={'user_dn': user_dn})
        item = response.get('Item')
        if item:
            # Return only the permissions needed for the operation
            return item.get('permissions', [])
    except Exception as e:
        # Log error, avoid exposing details
        app.logger.error(f'DynamoDB error: {e}')
    return []

@app.route('/login', methods=['POST'])
def login():
    data = request.get_json()
    username = data.get('username', '')
    password = data.get('password', '')

    if not is_valid_username(username):
        return jsonify({'error': 'invalid username'}), 400

    user_dn = ldap_authenticate(username, password)
    if user_dn is None:
        return jsonify({'error': 'invalid credentials'}), 401

    permissions = get_user_permissions('UsersTable', user_dn)
    return jsonify({'status': 'authenticated', 'permissions': permissions})

Additional recommendations:

• Use environment variables or a secure parameter store for LDAP and DynamoDB connection details.
• Enable AWS CloudTrail and DynamoDB streams cautiously; ensure logs do not contain sensitive input from LDAP queries.
• Periodically review IAM policies for the principle of least privilege and test access boundaries using IAM policy simulations.