Around a month ago Miguel Jacq got in contact to let me know about a couple of errors he encountered when running InfoSanity’s mimic-nepstats.py with a small data set. Basically if your log file did not include any submissions, or was for a period shorter than 24hours the script would crash out, not the biggest problem as most will be working with larger data sets but annoying non the less.
Amun has been running away quite happily in my lab since initial install. From a statistic perspective my wor has been made really easy as Miguel Cabrerizo has previously taken one of the InfoSanity statistic scripts written for Nepenthes and Dionaea and adapted it to parse Amun’s submission.log files. If you’re wanting to get an overview of submissions from another Amun sensor the script has been uploaded alongside the other InfoSanity resources and is available here.
No single technology can do or handle every situation; the same holds true with honeypot sensors which is why I’m always interested in finding new systems to add to my environment. I’d had Amun on my list of potentials for a while, but after reading a short blog post that suggested install and setup was relatively quick and painless, it got moved up the to-do list.
InfoSanity’s honeyd-geoip.py script has been useful for analysing the initial findings from a HoneyD installation, but one of weaknesses identified in the geolocation database used by the script was that a large proportion of the source IP addresses connecting to the honeypot environment weren’t none within the database. Markus pointed me in the direction of the cymruwhois (discussed previously)python module as an alternative. I’ve re-written the initial script.
Since posting my Python whois class it’s lead to a (relatively) high volume of search hits pointing people to it. So I’d like to apologise for inflicting my code on other people. After a recent post with the honey-geoip.py script I was pointed in the direction Team Cymru’s whois service and accompanying python script.
Honeydsum is a script created by Lucio Henrique Franco and Carlos Henrique Peixoto Caetano Chaves for the Brazilian Honeynet project. As described by it’s Authors, it is a tool written in Perl designed to generate a text summary from Honeyd logs.
After getting a working HoneyD environment I wanted to better dig into the information provided by the system. First up was a quick script to get a feel for where the attacks/connections originate from. At first glance I really like the log format that is used by honeyd.log, it is nice an easy to parse. From this I quickly knocked up a python script to parse the honeyd.log file, collect a list of unique source addresses and finally use GeoIP to determine (and count) the county of origin.
In this case it is a section of the site dedicated to the code and tools released as part of the research carried out by InfoSanity. No new content yet, but it has served as a nice reminder of some of the intended features still incomplete in existing projects, hopefully updates should be coming soon.
I was recently pointed towards www.reportspammers.net, which is a good resource for all things spam related and is steadily increased the quantity and quality of the information available. As much as I like the statistics that can be gathered from honeypot systems, live and real stats are even better and the data utilised by Report Spammers is taken from the email clusters run by Email Cloud.
Since reading Virtual Honeypots I’ve been wanting to implement a HoneyD system, developed by Niels Provos. From it’s own site, HoneyD is a small daemon that creates virtual hosts on a network. The hosts can be configured to run arbitrary services, and their personality can be adapted so that they appear to be running certain operating systems. Honeyd enables a single host to claim multiple addresses – I have tested up to 65536 – on a LAN for network simulation. Honeyd improves cyber security by providing mechanisms for threat detection and assessment. It also deters adversaries by hiding real systems in the middle of virtual systems.