Network Knowledge and Segmentation

If you look at most cutting-edge network information security guidance, job #1 can be paraphrased as “Know Thy Network.” It is firmly recommended (and in much regulatory guidance demanded) that organizations keep up-to-date inventories of hardware and software assets present on their computer networks. In fact, the most current recommendation is that organizations utilize software suites that not only keep track of inventories, but monitor all critical network entities with the aim of detecting any hardware or software applications that should not be there.

Another part of network knowledge is mapping data flows and trust relationships on networks, and mapping which business entities use which IT resources and information. For this knowledge, I like to go to my favorite risk management tool: the Business Impact Analysis (BIA). In this process, input comes from personnel across the enterprise detailing what they do, how they do it, what resources they need, what input they need, what output they produce and more (see MSI blog archives for more information about BIA and what it can do for your information security program).

About now, you are probably asking what all this has to do with network segmentation. The answer is that you simply must know where all your network assets are, who needs access to them and how they move before you can segment the network intelligently and effectively. It can all be summed up with one phrase: Need to Know. Need to know is the very basis of access control, and access control is what network segmentation is all about. You do not want anyone on your network to “see” information assets that they do not need to see in order to properly perform their business functions. And by the same token, you do not want network personnel to be cut off from information assets that they do need to perform their jobs. These are the reasons network knowledge and network segmentation go hand-in-hand.

Proper network knowledge becomes even more important when you take the next step in network segmentation: enclaving. I will discuss segmentation versus enclaving in my next blog later this month.

Why Segment Your Network?

Network segmentation is the practice of splitting your computer network into subnetworks or network segments (also known as zoning). This is typically done using combinations of firewalls, VLANs, access controls and policies & procedures. Implementing network segmentation requires planning and effort, and it can entail some teething problems along the way as well. So why should it be done?

The number one reason is to protect the security of your network resources and information. When people first started to defend their homes and enterprises from attack, they built perimeter walls and made sure everything important was inside of those walls. They figured doing this would keep their enemies outside where they couldn’t possibly do any damage. This was a great idea, but unfortunately it had problems in the real world.

People found that the enemy only had to make one small hole in their perimeter defenses to be able to get at all of their valuables. They also realized that their perimeter defense didn’t stop evil insiders from wreaking havoc on their valuables. To deal with these problems, people started to add additional layers of protection inside of their outer walls. They walled off enclaves inside the outer defenses and added locks and guards to their individual buildings to thwart attacks.

This same situation exists now in the world of network protection. As network security assessors and advisors, we see that most networks we deal with are still “flat;” they are not really segmented and access controls alone are left to prevent successful attacks from occurring. But in the real world, hacking into a computer network is all about gaining a tiny foothold on the network, then leveraging that access to navigate around the network. The harder it is for these attackers to see the resources they want and navigate to them, the safer those resources are. In addition, the more protections that hackers need to circumvent during their attacks, the more likely they are to be detected. It should also be noted that network segmentation works just as well against the internal threat; it is just as difficult for an employee to gain access to a forbidden network segment as it is for an Internet-based attacker.

Increased security is not the only advantage of network segmentation. Instead of making network congestions worse, well implemented segmentation can actually reduce network congestion. This is because there are fewer hosts, thus less local traffic per segment. In addition, segmentation can help you contain network problems by limiting the effects of local failures that occur on other parts of the network.

The business reasons for implementing network segmentation are becoming more apparent every day. Increasingly, customers are demanding better information security from the businesses they employ. If the customer has a choice between two very similar companies, they will almost assuredly pick the company with better security. Simply being able to say to your customers that your network is fully segmented and controlled can improve your chances of success radically.

Segmenting With MSI MachineTruth

Many organizations struggle to implement network segmentation and secure network enclaves for servers, industrial controls, SCADA or regulated data. MicroSolved, Inc. (“MSI”) has been helping clients solve information security challenges for nearly twenty-five years on a global scale. In helping our clients segment their networks and protect their traffic flows, we identified a better approach to solving this often untenable problem.

That approach, called MachineTruth™, leverages our proprietary machine learning and data analytics platform to support our industry leading team of experts throughout the process. Our team leverages offline analysis of configuration files, net flow and traffic patterns to simplify the challenge. Instead of manual review by teams of network and systems administrators, MachineTruth takes automated deep dives into the data to provide real insights into how to segment, where to segment, what filtering rules need to be established and how those rules are functioning as they come online.

Our experts then work with your network and security teams, or one of our select MachineTruth Implementation Partners, to guide them through the process of installing and configuring filtering devices, detection tools and applications needed to support the segmentation changes. As the enclaves start to take shape, ongoing oversight is performed by the MSI team, via continual analytics and modeling throughout the segmentation effort. As the data analysis and implementation processes proceed, the controls and rules are optimized and transitioned to steady state maintenance.

Lastly, the MSI team works with the segmentation stakeholders to document, socialize and transfer knowledge to those who will manage and support the newly segmented network and its various enclaves for the long term. This last step is critical to ensuring that the network changes and segmentation initiatives remain in place in the future.

This data-focused, machine learning-based approach enables segmentation for even the most complex of environments. It has been used to successfully save hundreds of man-years of labor and millions of dollars in overhead costs. It has reduced the time to segment international networks from years to months, while significantly raising the quality and security of the new environments. It has accomplished these feats, all while reducing network downtime, outages and potentially dangerous misconfiguration issues.

If your organization is considering or in the process of performing network segmentation for your critical data, you should take a look at the MachineTruth approach from MSI. It could mean the difference between success and struggle for this critical initiative.


Network Segmentation Month

February is Network Segmentation Month at MSI. During February, our blog and social media content will focus on network segmentation initiatives. A how, why, when, what and who –  kind of look at creating secure enclaves within your network.

These enclaves could be based on risk zones, types of systems, types of access, business process, regulatory requirements or many other meta factors. 

We will discuss different reasons for segmenting, approaches to segmentation, some of the lessons we’ve learned from segmenting some of the largest and most complex environments in our 25 year history. It won’t all be positive – we’ll also share some of the ways that segmentation fails, some of the challenges and some of the drawbacks of segmenting networks.

So, strap in and stay tuned for a month of content focused on using segmentation to better secure your environment.

As always, if you have stories to share or want to discuss a specific segmentation question, you can do that via email (info@microsolved.com) or via Twitter to @microsolved or to me personally. (@lbhuston) MSI is always available to help you with segmentation projects, be that planning, implementation, oversight or attestation. We have a proprietary, data-centric approach to this work which we have been using for several years. You can learn more about it here – MachineTruth. We look forward to hearing from you!

Last Quick and Dirty Log Tip for the Week

OK, so this week I posted two other blog posts about doing quick and dirty log analysis and some of the techniques I use. This one also covers converting column logs to CSV.

After the great response, I wanted to drop one last tip for the week. 

Several folks asked me about re-sorting and processing the column-based data in different ways and to achieve different analytical views. 

Let me re-introduce you to my friend and yours, sort.

In this case, instead of using the sort -n -r like before (numeric sort, reverse order), we can use:

  • sort -k# -n input_file (where # is the number of the column you’d like to sort by and the input file is the name of the file to sort)
    • You can use this inline by leveraging the pipe (|) again – i.e.: cat input.txt | sort -k3 -n (this types the input file and sends it to sort for sorting on the third column in numeric order) (-r would of course, reverse it…)
    • You can write the output of this to a file with redirects “> filename.txt”, i.e.: cat input.txt | sort -k3 -n -r > output.txt
      • You could also use “>>” as the redirect in order to create a file if it doesn’t exist OR append to a file if it does exist… i.e..:  cat input.txt | sort -k3 -n -r >> appended_output.txt

That’s it! It’s been a fun week sharing some simple command line processing tips for log files. Drop me a line on Twitter (@lbhuston) and let me know what you used them for, or which ones are your favorite. As always, thanks and have a great weekend! 

Quick And Dirty Log Analysis Followup

Earlier this week, I posted some tips for doing Quick and Dirty PA Firewall Log Analysis.

After I posted this, I got a very common question, and I wanted to answer it here.

The question is something along the lines of “When I use the techniques from your post, the outputs of the commands are column separated data. I need them to be CSV to use with my (tool/SEIM/Aunt Gracie/whatever). How can I convert them?” Sound familiar?

OK, so how do we accomplish this feat of at the command line without all of the workarounds that people posted, and without EVER loading Excel? Thankfully we can use awk again for this.

We can use:

  • awk ‘BEGIN { OFS = “,”} ; {print $1,$2,$3}’
    • Basically, take an input of column data, and print out the columns we want (can be any, in this case I want the first 3 columns), and make the outputs comma delimited.
    • We can just append this to our other command stacks with another pipe (|) to get our output CSV
  • Example: cat log.csv | awk ‘BEGIN { FS = “,”} ; {print $8,$9}’ | sort -n | uniq -c | sort -n -r | awk ‘BEGIN { OFS = “,”} ; {print $1,$2,$3}’
    • In this example, the source IP and destination IP will be analyzed, and the reduced to unique pairs, along with the number of times that that pair is duplicated in the input log (I use this as a “hit rate” as I described earlier
      • A common question, why do I ask for two columns in the first awk and then ask for three columns in the second awk?
        • The answer of course, is that the first awk prints the unique pairs, but it also adds a column of the “hit rate”, so to get the output appropriately, I need all three fields.

So, once again, get to know awk. It is your friend.:)

PS – Yes, I know, there are hundreds of other ways to get this same data, in the same format, using other command line text processing tools. Many may even be less redundant than the commands above. BUT, this is how I did it. I think it makes it easy for people to get started and play with the data. Post your ways to Twitter or share with the community. Exploration is awesome, so it will encourage users to play more. Cool! Hit me on Twitter if you wanna share some or talk more about this approach (@lbhuston).

Thanks for reading!

Quick & Dirty Palo Alto Log Analysis

OK, so I needed to do some quick and dirty traffic analysis on Palo Alto text logs for a project I was working on. The Palo Alto is great and their console tools are nice. Panorama is not too shabby. But, when I need quick and dirty analysis and want to play with data, I dig into the logs. 
 
That said, for my quick analysis, I needed to analyze a bunch of text logs and model the traffic flows. To do that, I used simple command line text processing in Unix (Mac OS, but with tweaks also works in Linux, etc.)
 
I am sharing some of my notes and some of the useful command lines to help others who might be facing a similar need.
 
First, for my project, I made use of the following field #’s in the text analysis, pulled from the log header for sequence:
  • $8 (source IP) 
  • $9 (dest IP)
  • $26 (dest port)
  • $15 (AppID)
  • $32 (bytes)
 
Once, I knew the fields that corresponded to values I wanted to study, I started using the core power of command line text processing. And in this case, the power I needed was:
  • cat
  • grep
    • Including, the ever useful grep -v (inverse grep, show me the lines that don’t match my pattern)
  • awk
    • particularly: awk ‘BEGIN { FS = “,”} ; {print $x, $y}’ which prints specific columns in CSV files 
  • sort
    • sort -n (numeric sort)
    • sort -r (reverse sort, descending)
  • uniq
    • uniq -c (count the numbers of duplicates, used for determining “hit rates” or frequency, etc.)
 
Of course, to learn more about these commands, simply man (command name) and read the details. 😃 
 
OK, so I will get you started, here are a few of the more useful command lines I used for my quick and dirty analysis:
  • cat log.csv | awk ‘BEGIN { FS = “,”} ; {print $8,$9,$26}’ | sort | uniq -c | sort -n -r > hitrate_by_rate.txt
    • this one produces a list of Source IP/Dest IP/Dest Port unique combinations, sorted in descending order by the number of times they appear in the log
  • cat log.csv | awk ‘BEGIN { FS = “,”} ; {print $8,$9}’ | sort -n | uniq -c | sort -n -r > uniqpairs_by_hitrate.txt
    • this one produces a list of the uniq Source & Destination IP addresses, in descending order by how many times they talk to each other in the log (note that their reversed pairings will be separate, if they are present – that is if A talks to B, there will be an entry for that, but if B initiates conversations with A, that will be a separate line in this data set)
  • cat log.csv | awk ‘BEGIN { FS = “,”} ; {print $15}’ | sort | uniq -c | sort -n -r > appID_by_hitrate.txt
    • this one uses the same exact techniques, but now we are looking at what applications have been identified by the firewall, in descending order by number of times that application identifier appears in the log
 
Again, these are simple examples, but you can tweak and expand as you need. This trivial approach to command line text analysis certainly helps with logs and traffic data. You can use those same commands to do a wondrous amount of textual analysis and processing. Learn them, live them, love them. 😃 
 
If you have questions, or want to share some of the ways you use those commands, please drop us a line on Twitter (@microsolved) or hit me up personally for other ideas (@lbhuston). As always, thanks for reading and stay safe out there! 

An Exercise to Increase IT/OT Engagement & Cooperation

Just a quick thought on an exercise to increase the cooperation, trust and engagement between traditional IT and OT (operational technology – (ICS/SCADA tech)) teams. Though it likely applies to just about any two technical teams, including IT and development, etc.

Here’s the idea: Host a Hack-a-thon!

It might look something like this:

  • Invest in some abundant kits of LittleBits. These are like Legos with electronics, mechanical circuits and even Arduino/Cloud controllers built in. Easy, safe, smart and fun!
  • Put all of the technical staff in a room together for a day. Physically together. Ban all cell phones, calls, emails, etc. for the day – get people to engage – cater in meals so they can eat together and develop rapport
  • Split the folks into two or more teams of equal size, mixing IT and OT team members (each team will need both skill sets – digital and mechanical knowledge) anyway.
  • Create a mission – over the next 8 hours, each team will compete to see who can use their smart bits set to design, program and proto-type a solution to a significant problem faced in their everyday work environments.
  • Provide a prize for 1st and 2nd place team. Reach deep – really motivate them!
  • Let the teams go through the process of discussing their challenges to find the right problem, then have them use draw out their proposed solution.
  • After lunch, have the teams discuss the problems they chose and their suggested fix.Then have them build it with the LittleBits. 
  • Right before the end of the day, have a judging and award the prizes.

Then, 30 days later, have a conference call with the group. Have them again discuss the challenges they face together, and see if common solutions emerge. If so, implement them.

Do this a couple times a year, maybe using something like Legos, Raspberry Pis, Arduinos or just whiteboards and markers. Let them have fun, vent their frustrations and actively engage with one another. The results will likely astound you.

How does your company further IT/OT engagement? Let us know on Twitter (@microsolved) or drop me a line personally (@lbhuston). Thanks for reading! 

My 3 Favorite Podcast Episodes (So Far…)

The State of Security Podcast has been a fun endeavor and I am committed to continue working on it. I am currently working on raising it to multiple episodes per month, so as I was reflecting, I thought I would share my 3 favorite episodes so far. There are so many great moments, and so much generosity from my guests, I am certainly thrilled with all of them – but everyone has to have favorites… 🙂 

#1 – Episode 1 – This one holds a special place in my heart. Thanks to the wonderful Dave Rose and the absolutely brilliant Helen Patton, they made this interview segment much more comfortable than it should have been. If you can get past my stumbling and bumbling, they share some pure magic with the audience. I hopefully have improved as an interviewer, but much thanks to them for helping SoS get off to a roaring start! 

#2 – Episode 6 – One of the most personal episodes ever, an anonymous friend shares a tale of what it is like to work for over year on a major breach. There is heartbreak and pain here, well beyond infosec. I still get chills every time I listen to it.

#3 – Episode 9 – This one is so personal to me, I get butterflies when people tell me they listened to it. Adam Luck interviews me, and the questions get very personal, very fast. We cover some personal history, why I am an infosec professional and some of the amazing friendships I have enjoyed over the years. Stark and raw, this is worth dealing with the crappy audio, or at least people tell me it is. (This episode is also why we hired audio professionals for our episodes.)

Those are my 3. What are yours? Hit me up on Twitter (@lbhuston) or @microsolved and let us know. Thanks for listening!

State of Security Episode 12 Now Aavailable

We’ve just released episode 12 of the State Of Security Podcast. This time around, I answer questions from listeners. Things like the idea of a “Great Firewall” for the USA, the hack of the DNC, questions about launching products, working with mentees and even what I read in 2016. 

There’s some good stuff in here, and the podcast is just less than an hour. 

Check it out and let me know on Twitter what you think (@lbhuston) or drop @microsolved a line. 

Happy New Year, folks, and thanks for listening!