Ldap Injection in Feathersjs with Dynamodb

LDAP Injection is an injection technique where untrusted input is concatenated into LDAP query strings, leading to unauthorized authentication or directory access. When FeathersJS, a framework for building REST and real-time APIs, is used with an LDAP authentication strategy and a DynamoDB backend for user or session storage, the combination can expose an authentication bypass or information leak if input is not strictly validated.

FeathersJS applications often rely on hooks and services to manage authentication. If a developer builds an LDAP bind or search using string interpolation with user-controlled fields such as username or email, and those values are passed directly into the LDAP filter, an attacker can inject malicious filter syntax. For example, a username like admin)(uid=* could alter the intended LDAP filter logic. In setups where FeathersJS queries DynamoDB to retrieve user metadata before or after LDAP bind, malformed or over-privileged LDAP queries may bypass intended access controls, especially if DynamoDB data is used to determine group membership or authorization flags.

DynamoDB itself does not execute LDAP queries; the risk arises when application code builds LDAP filter strings using unsanitized inputs that originate from or are influenced by data stored in DynamoDB (e.g., user attributes or group mappings). If DynamoDB contains improperly validated or attacker-influenced data used in subsequent LDAP operations, the effective security boundary is weakened. Moreover, if FeathersJS services expose LDAP-related operations via hooks without strict schema validation or allow dynamic query building based on user input, the attack surface expands. The combination therefore does not create LDAP Injection in isolation, but it can expose the vulnerability when untrusted data stored in or retrieved from DynamoDB is used to construct LDAP filters or determine LDAP bind behavior in FeathersJS.

Consider a scenario where a FeathersJS service retrieves user attributes from DynamoDB and then uses those attributes to form an LDAP search filter. If the attribute values are not sanitized, an attacker who can write to DynamoDB (e.g., via an exposed or misconfigured endpoint) can store crafted values that later manipulate LDAP queries. This cross-vector illustrates why input validation, strict schema definitions, and separation of concerns between directory services and database storage are critical when integrating FeathersJS, LDAP, and DynamoDB.

Remediation centers on preventing untrusted input from affecting LDAP query construction and ensuring DynamoDB data is treated as untrusted unless validated. Use parameterized or strongly-typed approaches for LDAP filters, and enforce schema validation for any data read from DynamoDB before it is used in authentication logic.

Example: Safe LDAP bind with parameterized filter

Instead of concatenating user input into an LDAP filter, use an array or object representation that a library can safely encode, or sanitize with a dedicated LDAP filter escaper. Below is a Node.js example using the ldapjs client where the username is passed as a parameter rather than interpolated:

const ldap = require('ldapjs');
const client = ldap.createClient({ url: 'ldap://localhost' });

async function safeBind(username, password) {
  // Validate username format strictly (e.g., alphanumeric + length)
  if (!/^[a-zA-Z0-9_.-]{3,64}$/.test(username)) {
    throw new Error('Invalid username format');
  }
  const dn = `uid=${username},ou=people,dc=example,dc=com`;
  return new Promise((resolve, reject) => {
    client.bind(dn, password, (err) => {
      if (err) reject(err);
      else resolve();
    });
  });
}

DynamoDB data validation before LDAP use

When FeathersJS retrieves user data from DynamoDB, validate and sanitize fields before they influence LDAP operations. Below is an example using the AWS SDK for JavaScript v3 with a schema check:

const { DynamoDBClient, GetItemCommand } = require('@aws-sdk/client-dynamodb');
const { unmarshall } = require('@aws-sdk/util-dynamodb');

const ddb = new DynamoDBClient({ region: 'us-east-1' });

async function getUserAttributes(userId) {
  const cmd = new GetItemCommand({
    TableName: 'Users',
    Key: { userId: { S: userId } }
  });
  const resp = await ddb.send(cmd);
  if (!resp.Item) throw new Error('User not found');
  const user = unmarshall(resp.Item);
  // Strict validation: ensure expected structure
  if (typeof user.email !== 'string' || !user.email.includes('@')) {
    throw new Error('Invalid user data');
  }
  return user;
}

FeathersJS hook with validated input

In a FeathersJS hook, combine validation and safe LDAP bind. This example uses a custom hook to ensure only validated data reaches LDAP:

const { authenticate } = require('@feathersjs/authentication').hooks;
const { iff, isProvider } = require('feathers-hooks-common');

function validateAndSetUser() {
  return async context => {
    const { username, password } = context.data;
    // Validate input before any LDAP interaction
    if (!username || !password) {
      throw new Error('Missing credentials');
    }
    // Perform safe bind (defined earlier)
    await safeBind(username, password);
    // Optionally fetch and validate DynamoDB data
    const user = await getUserAttributes(username);
    context.params.user = user;
    return context;
  };
}

// Usage in a Feathers service
const authHooks = {
  before: {
    create: [
      iff(isProvider('external'), authenticate('local'), validateAndSetUser())
    ]
  }
};

General measures

• Use allowlists for usernames and reject any characters not explicitly permitted.
• Do not build LDAP filters via string concatenation; prefer library APIs that separate filter components.
• Treat DynamoDB as an untrusted source; validate and sanitize all data before it influences authentication or directory queries.
• Apply principle of least privilege to LDAP bind accounts and restrict DynamoDB access with IAM policies.