JA3 is a new technique for creating SSL client fingerprints that are easy to produce and can be easily shared for threat intelligence.
This repo includes JA3 scripts for Bro and Python.
JA3 support has also been added to Moloch and Trisul NSM.
JA3 fingerprint for the standard Tor client:
e7d705a3286e19ea42f587b344ee6865
JA3 fingerprint for the Dyre malware family:
b386946a5a44d1ddcc843bc75336dfce
JA3 fingerprint for Metasploit's Meterpreter (Linux):
5d65ea3fb1d4aa7d826733d2f2cbbb1d
While destination IPs, Ports, and X509 certificates change, the JA3 fingerprint remains constant for the client application in these examples.
A list of over 400 JA3's and their associated applications can be found here
Work on a public JA3 Malware Blacklist is in progress.
TLS and it’s predecessor, SSL, I will refer to both as “SSL” for simplicity, are used to encrypt communication for both common applications, to keep your data secure, and malware, so it can hide in the noise. To initiate a SSL session, a client will send a SSL Client Hello packet following the TCP 3-way handshake. This packet and the way in which it is generated is dependant on packages and methods used when building the client application. The server, if accepting SSL connections, will respond with a SSL Server Hello packet, thus continuing the cryptographic negotiation. Because SSL negotiations are transmitted in the clear, it’s possible to fingerprint and identify client applications using the details in the SSL Client Hello packet.
JA3 gathers the decimal values of the bytes for the following fields in the Client Hello packet; SSL Version, Accepted Ciphers, List of Extensions, Elliptic Curves, and Elliptic Curve Formats. It then concatenates those values together in order, using a "," to delimit each field and a "-" to delimit each value in each field.
The field order is as follows:
SSLVersion,Cipher,SSLExtension,EllipticCurve,EllipticCurvePointFormat
Example:
769,47-53-5-10-49161-49162-49171-49172-50-56-19-4,0-10-11,23-24-25,0
If there are no SSL Extensions in the Client Hello, the fields are left empty.
Example:
769,4-5-10-9-100-98-3-6-19-18-99,,,
These strings are then MD5 hashed to produce an easily consumable and sharable 32 character fingerprint. This is the JA3 SSL Client Fingerprint.
769,47-53-5-10-49161-49162-49171-49172-50-56-19-4,0-10-11,23-24-25,0 --> ada70206e40642a3e4461f35503241d5
769,4-5-10-9-100-98-3-6-19-18-99,,, --> de350869b8c85de67a350c8d186f11e6
We also needed to introduce some code to account for Google’s GREASE (Generate Random Extensions And Sustain Extensibility) as described here. Google uses this as a mechanism to prevent extensibility failures in the TLS ecosystem. JA3 ignores these values completely to ensure that programs utilizing GREASE can still be identified with a single JA3 hash.
JA3 is a much more effective way to detect malicious activity over SSL than IP or domain based IOCs. Since JA3 detects the client application, it doesn’t matter if malware uses DGA (Domain Generation Algorithms), or different IPs for each C2 host, or even if the malware uses Twitter for C2, JA3 can detect the malware itself based on how it communicates rather than what it communicates to.
JA3 is also an excellent detection mechanism in locked-down environments where only a few specific applications are allowed to be installed. In these types of environments one could build a whitelist of expected applications and then alert on any other JA3 hits.
Certainly, more analysis needs to be done with JA3, on what it can detect as well as other things it could be used for. Please contact me on twitter @4A4133 or over email, let me know what you find and if you have any feature requests.
John B. Althouse
Jeff Atkinson
Josh Atkins
Please send questions and comments to John B. Althouse.