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Before yesterdayResearch - Companies

Cracking RDP NLA Supplied Credentials for Threat Intelligence

21 October 2021 at 19:40
By: Ray Lai

NLA Honeypot Part Deux

This is a continuation of the research from Building an RDP Credential Catcher for Threat Intelligence. In the previous post, we described how to build an RDP credential catcher for threat intelligence, with the caveat that we had to disable NLA in order to receive the password in cleartext. However, RDP clients may be attempting to connect with NLA enabled, which is a stronger form of authentication that does not send passwords in cleartext. In this post, we discuss our work in cracking the hashed passwords being sent over NLA connections to ascertain those supplied by threat actors.

This next phase of research was undertaken by Ray Lai and Ollie Whitehouse.

What is NLA?

NLA, or Network Level Authentication, is an authentication method where a user is authenticated via a hash of their credentials over RDP. Rather than passing the credentials in cleartext, a number of computations are performed on a user’s credentials prior to being sent to the server. The server then performs the same computations on its (possibly hashed) copy of the user’s credentials; if they match, the user is authenticated.

By capturing NLA sessions, which includes the hash of a user’s credentials, we can then perform these same computations using a dictionary of passwords, crack the hash, and observe which credentials are being sprayed at RDP servers.

The plan

  1. Capture a legitimate NLA connection.
  2. Parse and extract the key fields from the packets.
  3. Replicate the computations that a server performs on the extracted fields during authentication.

In order to replicate the server’s authentication functionality, we needed an existing server that we could look into. To do this, we modified FreeRDP, an open-source RDP client and server software that supported NLA connections.

Our first modification was to add extra debug statements throughout the code in order to trace which functions were called during authentication. Looking at this list of called functions, we determined six functions that either parsed incoming messages or generated outgoing messages.

There are six messages that are sent (β€œIn” or β€œOut” is from the perspective of the server, so β€œNegotiate In” is a message sent from the client to the server):

  1. Negotiate In
  2. Negotiate Out
  3. Challenge In
  4. Challenge Out
  5. Authenticate In
  6. Authenticate Out

Once identified, we patched these functions to write the packets to a file. We named the files XXXXX.NegotiateIn, XXXXX.ChallengeOut, etc., with XXXXX being a random integer that was specific to that session, so that we could keep track of which packets were for which session.

Parsing the packets

With the messages stored in files, we began work to parse these messages. For a proof of concept, we wrote a parser for these six messages in Python in order to have a high-level understanding of what was needed in order to crack the hashes contained within the messages. We parsed out each field into its own object, taking hints from FreeRDP code.

Dumping intermediary calculations

When it came time to figure out what type of calculation was being performed by each function (or each step of the function), we also added code to individual functions to dump raw bytes that were given as inputs and outputs in order to ensure that the calculations were correctly done in the Python code.

Finally, authentication

The ultimate step in NLA authentication is when the server receives the β€œAuthentication In” message from the client. At that point, it takes all the previous messages, performs some calculation on it, and compares it with the β€œMIC” stored in the β€œAuthentication In” message.

MIC stands for Message Integrity Check, and is roughly the following:

# User, Domain, Password are UTF-16 little-endian
NtHash = MD4(Password)
NtlmV2Hash = HMAC_MD5(NtHash, User + Domain)
ntlm_v2_temp_chal = ChallengeOut->ServerChallenge
                  + "\x01\x01\x00\x00\x00\x00\x00\x00"
                  + ChallengeIn->Timestamp
                  + AuthenticateIn->ClientChallenge
                  + "\x00\x00\x00\x00"
                  + ChallengeIn->TargetInfo
NtProofString = HMAC_MD5(NtlmV2Hash, ntlm_v2_temp_chal)
KeyExchangeKey = HMAC_MD5(NtlmV2Hash, NtProofString)
if EncryptedRandomSessionKey:
    ExportedSessionKey = RC4(KeyExchangeKey, EncryptedRandomSessionKey)
else:
    ExportedSessionKey = KeyExchangeKey
msg = NegotiateIn + ChallengeIn + AuthenticateOut
MIC = HMAC_MD5(ExportedSessionKey, msg)

In the above algorithm, all values are supplied within the six NLA messages (User, Domain, Timestamp, ClientChallenge, ServerChallenge, TargetInfo, EncryptedRandomSessionKey, NegotiateIn, ChallengeIn, and AuthenticateOut), except for one: Password.

But now that we have the algorithm to calculate the MIC, we can perform this same calculation on a list of passwords. Once the MIC matches, we have cracked the password used for the NLA connection!

At this point we are ready to start setting up RDP credential catchers, dumping the NLA messages, and cracking them with a list of passwords.

Code

All the code we developed as part of this project we have open sourced here – https://github.com/nccgroup/nlahoney this includes:

Along with all our supporting research notes and code.

Future

The next logical step would be to rewrite the Python password cracker into a hashcat module, left as an exercise to the reader.

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