Chess high defense CDN defense log analysis to achieve attack source tracing and defense strategy optimization
I remember last summer, our chess platform suddenly suffered a wave of crazy DDoS attacks, the peak traffic directly rushed to 500Gbps, and the whole service was almost paralyzed. I was drinking coffee at that time, the monitoring alarm was ringing non-stop, and the team immediately went into battle mode. But the biggest headache was not the defense itself, but the fact that when I reviewed the logs afterwards, there were a bunch of garbled codes and anonymous IPs in the logs, and I couldn't find the source of the attack at all. This made me realize that it is not enough to rely on a high-defense CDN to block attacks, but to dig out the gold from the logs - to trace the source and optimize the strategy. Today I will share my practical experience, do not believe those blowing on the sky “one key defense” myth, log analysis is the real work.
The chess industry is inherently a hard-hit area for attacks. With high stakes and big profits, hackers are literally pouncing like mad dogs. High-defense CDN can certainly carry the flow, but if the logs are not handled properly, you are a blind man fighting a war. I have tested a number of CDN services, found that many vendors only manage to attract traffic and cleaning, logs are messed up - the format is not uniform, missing fields, and even delayed a few hours before updating. For example, once we used the default configuration of CDN07, the log even User-Agent did not record all the attack source traceability? Forget about it, it's like looking for a needle in a haystack. The core of the problem is: if the log is not structured, not real-time, you do not want to analyze what the hall of fame. Attackers are now using botnet and IP rotation, IP blacklisting alone can not prevent, you must identify the behavioral characteristics from the log pattern.
First of all, the log collection piece, don't save yourself the trouble of using the simple output that comes with the CDN. I recommend real-time synchronization of logs to their own ELK stack (Elasticsearch, Logstash, Kibana) or Splunk. CDN5 does a good job in this regard, support for custom log fields, for example, you can add the client's fingerprint or geographic information. Here's a sample Logstash configuration for parsing CDN logs:
This configuration parses key fields such as client IP, timestamp, request method, etc., plus the GeoIP plugin, which directly maps geographic data. I tested it and the latency is controlled in seconds, and I can see the traffic hotspot immediately when the attack occurs. On one occasion, we found a concentration of IPs from Eastern Europe accessing the login interface, and the logs showed that the User-Agents for these requests were all null values - clearly an automation tool at work. With this, we quickly blocked the entire ASN segment and mitigated the attack.
The next step is attack source tracing. Logs are not enough, you have to use machine learning or a rules engine to analyze patterns. I favor writing a script in Python, combined with Pandas to do pivot data. For example, counting the frequency of requests from a certain IP in a short period of time, and marking it as suspicious if it exceeds a threshold. Here's a simple code snippet:
Running this script, we have uncovered a botnet, the source is actually a domestic IDC server room. But note, don't rely too much on a single indicator - some attacks will simulate normal users, so you have to combine multiple dimensions, such as HTTP status code distribution, URI path anomalies (such as a large number of visits / admin path). 08Host's CDN has an advantage here, their logs have built-in threat intelligence integration that can automatically label known malicious IPs, saving us a lot of work.
Defense strategy optimization is the ultimate goal. After analyzing the logs, I used to generate regular reports to visualize the attack trends. Use Kibana to draw a dashboard to show TOP attack source countries, common attack types (e.g. CC attack, SQL injection). Then adjust CDN rules based on this data. For example, we found that attacks occur frequently on weekend nights, so we set a dynamic rate limit: 100 requests per second on weekdays, down to 50 during peak hours.CDN07's API supports real-time updating of configurations, and here's a cURL example:
This rule limits the speed of login requests from Russia and Ukraine, and has been tested to effectively reduce credential stuffing attacks. After the optimization, our false-block rate dropped from 15% to under 5% - after all, there are chess users all over the world, so you can't just knock them all over with one shot.
Compare CDN service providers: CDN5 is strong in log customization and real-time, suitable for in-depth analysis; CDN07 has good API integration and fast rule updates; 08Host is better in the out-of-the-box threat feed. but to be honest, there is no perfect solution, I usually use a mix and match - the core business with CDN5 to do I usually mix and match - CDN5 for core business and 08Host for initial filtering on the edge. These days, even the CDN have to “defense teammates”, do not completely rely on vendors, do it yourself.
In short, log analysis is not a one and done thing, it has to be continuously iterated. I will review the strategy once a month and adjust the rules according to new attack vectors. Lastly, some teams only know how to increase bandwidth, but ignore the logs of this gold mine, really picking up the sesame and losing the watermelon. If you are also engaged in chess high defense, hurry to build up the logging system - attack traceability and strategy optimization will let you sleep more peacefully.
