Published on January 9th, 2016 📆 | 5850 Views ⚑0
Maltrail – Malicious Traffic Detection System
zvpprsensinaix.comfor Banjori malware), URL (e.g.
https://126.96.36.199/harsh02.exefor known malicious executable ) or IP address (e.g.
188.8.131.52for known attacker). Also, it has (optional) advanced heuristic mechanisms that can help in discovery of unknown threats (e.g. new malware).
The following (black)lists (i.e. feeds) are being utilized:
alienvault, autoshun, badips, bambenekconsultingc2, bambenekconsultingdga, binarydefense, bitcoinnodes, blocklist, botscout, bruteforceblocker, ciarmy, cruzit, cybercrimetracker, dshielddns, dshieldip, emergingthreatsbot, emergingthreatscip, emergingthreatsdns, feodotrackerdns, feodotrackerip, greensnow, malwarepatrol, malwareurlsnormal, maxmind, myip, nothink, openbl, openphish, palevotracker, proxylists, proxyrss, proxy, riproxies, rutgers, sblam, snort, socksproxy, sslipbl, sslproxies, torproject, torstatus, voipbl, vxvault, zeustrackerdns, zeustrackerip, zeustrackermonitor, zeustrackerurl, etc.
As of static entries, the trails for the following malicious entities (e.g. malware C&Cs) have been manually included (from various AV reports):
alureon, android_stealer, angler, aridviper, axpergle, babar, balamid, bamital, bankpatch, bedep, black_vine, bubnix, carbanak, careto, casper, chewbacca, cleaver, conficker, cosmicduke, couponarific, crilock, cryptolocker, cryptowall, ctblocker, darkhotel, defru, desertfalcon, destory, dorifel, dorkbot, dridex, dukes, dursg, dyreza, emotet, equation, evilbunny, expiro, fakeran, fareit, fbi_ransomware, fiexp, fignotok, fin4, finfisher, gamarue, gauss, htran, jenxcus, kegotip, kovter, lollipop, lotus_blossom, luckycat, mariposa, miniduke, modpos, nbot, nettraveler, neurevt, nitol, nonbolqu, nuqel, nwt, nymaim, palevo, pdfjsc, pift, plugx, ponmocup, powelike, proslikefan, pushdo, ransirac, redoctober, reveton, russian_doll, sality, sathurbot, scieron, sefnit, shylock, siesta, simda, sinkhole_1and1, sinkhole_abuse, sinkhole_blacklistthisdomain, sinkhole_certpl, sinkhole_drweb, sinkhole_fbizeus, sinkhole_fitsec, sinkhole_georgiatech, sinkhole_kaspersky, sinkhole_microsoft, sinkhole_shadowserver, sinkhole_sinkdns, sinkhole_zinkhole, skyper, smsfakesky, snake, snifula, sofacy, stuxnet, teerac, teslacrypt, torpig, torrentlocker, unruy, upatre, vawtrak, virut, vobfus, volatile_cedar, vundo, waterbug, zeroaccess, zlob, etc. [adsense size='2']
Maltrail is based on the Sensor <-> Server <-> Client architecture. Sensor (s) is a standalone component running on the monitoring node (e.g. Linux platform connected passively to the SPAN/mirroring port or transparently inline on a Linux bridge) or at the standalone machine (e.g. Honeypot) where it "sniffs" the passing traffic for blacklisted items/trails (i.e. domain names, URLs and/or IPs). In case of a positive match, it sends the event details to the (central) Serverwhere they are being stored inside the appropriate logging directory (i.e.
LOG_DIR described in the Configuration section). If Sensor is being run on the same machine as Server (default configuration), logs are stored directly into the local logging directory. Otherwise, they are being sent via UDP messages to the remote server (i.e.
LOG_SERVER described in theConfiguration section).
Server 's primary role is to store the event details and provide back-end support for the reporting web application. In default configuration, server and sensor will run on the same machine. So, to prevent potential disruptions in sensor activities, the front-end reporting part is based on the "Fat client" architecture (i.e. all data post-processing is being done inside the client's web browser instance). Events (i.e. log entries) for the chosen (24h) period are transferred to theClient , where the reporting web application is solely responsible for the presentation part. Data is sent toward the client in compressed chunks, where they are processed sequentially. The final report is created in a highly condensed form, practically allowing presentation of virtually unlimited number of events.
Note: Server component can be skipped altogether, and just use the standalone Sensor . In such case, all events would be stored in the local logging directory, while the log entries could be examined either manually or by some CSV reading application.
The following set of commands should get your Maltrail Sensor up and running (out of the box with default settings and monitoring interface "any"):
sudo apt-get install python-pcapy
git clone https://github.com/stamparm/maltrail.git
sudo python sensor.py