Hi newbie, getting back to my earliest crude brute force solution which could be a quick fix for an attack.
The solution involves taking a list of ip addresses who have bet into an office over the web. Then passing this list onto a service provider and having them exclusively allow only these known ips, or class c ranges.
The problems with this solution is that not every customer will come into your shop from day to day on an ip address which he/she has used in the past. Using the class-c allow list, it also means that an attacker has a more likely chance of using a bogus ip from an allowed class-c network.
I did some analysis on my site, which gets very little traffic, I suspect that this sample is way too small to get real figures, but there is no reason why every shop owner cannot do their own analysis to see how this solution may benefit them, more importantly, to estimate how many of their normal existing clients would be allowed into their shop were they to choose this style of a solution during an attack.
I took my data from an httpd-access.log which included traffic from November 1st, 2003 through December 31st 2003.
I started by breaking it out into ip addresses which were tracked during the login sequence. A shop owner would be better off using ips that were used during successful credit card processing, or bet processing.
I had 2635 unique ip addresses in 1413 class c ranges who hit the site between Oct 1 and Nov 30. Of these, 404 ips logged in within 108 class c ranges.
Lets assume that starting December 1, I will be hit by an attack where bogus ips are created and traffic is sent into my network to either clog up memory with unfinished connections, or just gobble bandwidth. So I will take my list of ips or class c ranges that I know are my customers which login regularly, and did so between October1 and November30. I will ask my ISP to only allow traffic sourced from this list into my network, or I may just add this filter to my own router.
If I had used my unique ip allow list on the first day of December, I would have missed login connections from 6 ip addresses that had not hit my site in the previous 2 months. This 6 of 404 ips might represent that 1.48% of my existing customers will be pissed off the first day. Had I used the class-c range allow list, then on the first day of december, all customers who logged in had been seen on that network and would not have known that an attack was going on.
Lets assume that the attack does not last one day, instead it lasts 9 days, December 1 through December 9. Using the ip allow list, I would have missed login connections from 42 ip addresses that had not hit my site in the previous 2 months. This 42 of 404 might represent that 10.4% of my customers will be pissed off at least once within the first 9 days of december. Had I used the class-c range allow list, then logins from 9 new networks would have been missed because they hadn't been seen in the previous 2 months. This 9 of 108 classes represents a similar 8.3% of my existing known customers who will be pissed in the first 9 days of December.
Lets assume that the attacks go on for the entire month of December. By this time, Im about to cut my own throat however my customer service staff would have already done so. By now, more and more of my customers are being affected by my exclusive allow list, but I havent lost them all just yet. I have traffic from 140 ips that cannot login. Thats 34% of my existing customers who cannot login, 66% that can, thats a D in my book, and I can assume that Ive lost those customers by now, or converted them to phone players. Had I used the class-c allow list, Id have missed traffic from 32 new networks pissing off 29.6% of the customers that Id have had less the attacks.
So my solution, though it be quick and dirty, and something that any techy should be able to create and implement within the first 2 hours of an attack, is not perfect, and would not last forever. However, assuming that you are down, keeping 98% of your traffic happy the first day, and 90% of your traffic happy in the first 9 days, and 65% of your traffic happy during the first month, is much much better than missing 100% of your internet traffic.
So newbie and other techies, would you consider doing the same analysis on your sites, and sharing them here?
Just trying to help,
-lab