In this blog post, we will continue our discussion of Analyst's Problems as a Service (APaaS), if you have not read the previous parts, please read them here and here. In this one we will see what are few things an analyst can do to overcome or at least have a different approach to the problems we mentioned in "The usual", "Architectural", "Logs" and "Alerts" sections.
What an analyst can do regarding all these issues. There are
problems everywhere and it seems like there is no light at the end of the
tunnel. Don’t worry, we will discuss some of the things which are in the analyst’s
power that may help mitigate or at least improve the process.
1)
The first and foremost thing to help the problem
of short staffing and less skilled staff is sharing. Remember the quote
“Sharing is Caring”, it is true in the SOC world. If you have a decent team,
then it is a great idea to have analysts gather to share something among
themselves. The second thing is documentation, it is an
important part of any organization and in SOC it will help reduce the training
period and also help analysts to follow set policies and procedures.
2)
Automation is something we can leverage to solve
the short staff issues. Like some of the simple things like writing/utilizing a
tool to perform common tasks that are performed by an analyst, creating an
ability in the SIEM to perform external searches like IPscan.
3)
Sometimes we need to go a little beyond our job
responsibilities like if your business has a policy that you need to collect
all the logs and everything else then you need to discuss with the business to
understand the reason behind the policy/procedure. Often it is a simple
misunderstanding of a framework, a requirement, or something which is dictating
the policy. So then discuss with them and agree to move to an approach that
works for you. This will improve search speed significantly.
4)
If you work with on-boarding logs, understand
how you can get logs into an environment. Gather all the methods and ways.
Also, finding what data sources can be correlated is very important but hard. Even
the hardest and the important one is how we collect them as this will have many
implications on the amount of context, we get from the data sources and what fields
we get.
5)
Data is like the paid subscription you bought
but never used. To get the most out of it, you have to read the content you
bought, same with the data, you have to understand it and analyze it.
6)
Often logs contain things that are of little
value to an organization and analyst. Do not be afraid to trim that fat. This helps
the SIEM cause now you are only removing the things which you do know that
provide little or no value and also dropping into analysis mode immediately
after collecting them. Also, better to do this in the pre-deployment phase or a
roll-out phace, this way the resources will be minimal
7)
If the data is not correlated in the logs/alerts, the best
place to start is to get familiarity with the product presence in the
organization’s architecture to see what other data sources the logs can be
correlated with.
8)
Sometimes too many features and data will
confuse an analyst. Imagine you are in a buffet you will likely have too many
options to choose from and too many items to start from still you will go in a
sequence by creating a mental map of what are the items you like what you do
not like, among the items you like which is an appetizer that you start with
and so on. You will not just eat one or two things and call it a day.
Similarly, in SIEM, you will probably have many options it is you who has to
create a mental map of what you will be starting an investigation with.
9)
Also, one of the other
things that can help in searching logs is, creating some pre-defined questions
related to what you want to see in your logs, like determining the goal of the
search. This will help in avoiding complex regex searches (sometimes you
need them to get results) and also the return time of logs.
10
When analyzing techniques for detections do
research on:
- what data sources it can be applied to?
- what data sources it will be effective with lower false positive?
- how it will affect the overall alert queue to determine if we want to take the risk or not
- Figure out if this technique can be stacked or layered. If it can, great. We can use the technique to the data sources and/or techniques it is related and relevant to. The goal of this is that, if one technique fails to catch the behavior of the attack then the other stacked/layered technique will catch.
11)
Firewalls, intrusion detection systems,
intrusion prevention systems, web server logs, proxy logs all consist of more
of the same data with different purposes. We can group them to build a
dashboard that tells a story.
12)
If threat intel is creating a lot of alerts, the
main purpose of threat intel feeds can be changed according to our
organization. We can use threat intel feeds to allow us to add additional
context to the logs. Depending on the level you want to go, we can use its
underlying capabilities to enhance an organization's capabilities around
logging and detection. Like we decide not to alert on the feeds but to ingest
them as a way to use them for intelligence purposes. Looking for trends and
then creating our detections around the observed trends.
This concludes of our three-part series on Analyst's Problems as a Service (APaaS). Thank you for reading. Feedback and thoughts are much appreciated.
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