Ldap Injection with Jwt Tokens

LDAP injection in JWT tokens occurs when user-supplied data within a JWT is used to construct LDAP queries without proper sanitization. This vulnerability is particularly dangerous because JWTs are designed to be self-contained and trusted by the receiving system.

The most common attack vector involves LDAP-based authentication systems that validate JWT claims against directory services. When a JWT contains user identifiers, group names, or other attributes that are directly inserted into LDAP queries, attackers can craft malicious tokens to manipulate these queries.

Consider a typical JWT containing a "username" claim that's used for LDAP authentication:

const token = jwt.sign({
  username: 'admin', // User-controlled value
  role: 'user'
}, 'secretkey');

If the backend validates this token and uses the username in an LDAP filter like:

(&(objectClass=user)(uid=admin))

An attacker can craft a JWT with a username containing LDAP metacharacters:

const maliciousToken = jwt.sign({
  username: 'admin)(|(uid=*))', // Injected LDAP filter
  role: 'user'
}, 'secretkey');

This creates the LDAP filter:

(&(objectClass=user)(uid=admin)(|(uid=*)))

The injected portion "(|(uid=*))" acts as an OR condition that matches any user, potentially bypassing authentication entirely. The vulnerability is compounded when JWTs contain multiple claims used in LDAP queries, such as group memberships, department names, or organizational units.

Another manifestation occurs in search-based LDAP operations where JWT claims determine search parameters. An attacker can use wildcard injections or boolean operators to expand the search results beyond intended boundaries, potentially exposing sensitive directory information or escalating privileges.

Detecting LDAP injection in JWT tokens requires examining both the token validation logic and the LDAP query construction. The most effective approach combines static analysis with runtime scanning.

Static analysis should focus on identifying code patterns where JWT claims are directly interpolated into LDAP filters. Look for these red flags:

// Vulnerable pattern - direct interpolation
const filter = `(uid=${token.username})`;

Dynamic detection using middleBrick's API security scanner can identify LDAP injection vulnerabilities by:

• Testing JWT endpoints with payloads containing LDAP metacharacters like *, (, ), &, |, !
• Analyzing the backend's response patterns for authentication bypass or information disclosure
• Checking for inconsistent behavior when injecting boolean operators
• Verifying proper input validation and output encoding

middleBrick specifically tests for LDAP injection by constructing JWTs with malicious payloads and monitoring the API's response. The scanner checks 12 security categories including input validation and authentication bypass scenarios.

For JWT-specific LDAP injection detection, focus on these patterns:

# Test with LDAP metacharacters
middlebrick scan https://api.example.com/auth \
  --payload "username=admin*)(|(uid=*)" \
  --header "Authorization: Bearer $JWT_TOKEN"

Runtime detection should also monitor for:

• Unexpected authentication successes with malformed JWT claims
• Directory service logs showing unusual LDAP query patterns
• Performance anomalies suggesting wildcard expansion
• Privilege escalation attempts through group membership manipulation

middleBrick's LLM security features can also detect if your API uses AI/ML components that might inadvertently process or validate JWT claims, adding another layer of attack surface that needs protection.

Remediating LDAP injection in JWT-based systems requires a defense-in-depth approach that addresses both token validation and LDAP query construction.

The first layer of defense is strict claim validation. Never trust JWT claims without validation, even if the token is properly signed. Implement a whitelist approach:

const validateLdapSafe = (input) => {
  const ldapMetaChars = /[\*\(\)\&\|\!\\]/;
  if (ldapMetaChars.test(input)) {
    throw new Error('Invalid LDAP characters detected');
  }
  return input;
};

// Validate before using in LDAP queries
const safeUsername = validateLdapSafe(decoded.username);
const safeGroup = validateLdapSafe(decoded.group);

The second layer involves using parameterized LDAP queries or escaping mechanisms provided by your LDAP library. Most modern LDAP libraries offer built-in protection:

const ldap = require('ldapjs');

// Use parameterized queries
const client = ldap.createClient({ url: 'ldap://localhost:389' });

const searchOptions = {
  filter: '(uid=' + ldap.escape(safeUsername) + ')',
  scope: 'sub'
};

client.search('ou=users,dc=example,dc=com', searchOptions, (err, res) => {
  // Handle results
});

For JWT-specific scenarios, implement claim transformation that maps user-friendly identifiers to internal LDAP DNs:

const claimToDnMap = {
  'admin': 'uid=admin,ou=admins,dc=example,dc=com',
  'john.doe': 'uid=john.doe,ou=users,dc=example,dc=com'
};

// Transform claims before LDAP use
const safeDn = claimToDnMap[decoded.username];
if (!safeDn) {
  throw new Error('Invalid user identifier');
}

// Use the pre-mapped DN instead of raw claims
const searchOptions = {
  filter: '(objectClass=person)',
  scope: 'sub'
};

// Bind with the specific DN
client.bind(safeDn, 'userPassword', (err) => {
  // Proceed with authenticated operations
});

Additional remediation steps include:

• Implementing rate limiting on JWT validation endpoints to slow down brute-force LDAP injection attempts
• Using middleBrick's continuous monitoring to detect when new vulnerabilities are introduced
• Adding security headers and proper error handling to prevent information leakage
• Regularly updating LDAP libraries to patch known vulnerabilities

For enterprise deployments, middleBrick's Pro plan offers continuous scanning that can detect LDAP injection vulnerabilities as they're introduced, with automated alerts when security scores drop below your configured threshold.