Slice It Smart: Extend Your Capture Time With Packet Slicing

I would say packet slicing is one of the most critical techniques to understand.

Back in the day when we had hard drives with limited disk space and we needed to capture for long periods of time, we used packet slicing.

Packet slicing in Wireshark is one of those features that doesn’t get much love, but once you use it, you wonder how you ever captured packets without it. The basic idea is simple: instead of grabbing the entire packet payload, you only capture the first N bytes. For many troubleshooting and analysis tasks, that’s more than enough to see headers, flags, and protocol behavior without hauling around a ton of unnecessary data. One of the biggest benefits of packet slicing is smaller capture files. Full packet captures can balloon in size fast, especially on busy links or during long troubleshooting sessions. By slicing packets, you drastically reduce disk usage and make your capture files easier to store, share, and archive. This is especially handy when you need to send a capture to a colleague or attach it to a ticket without watching your email client cry. Packet slicing also improves performance during both capture and analysis. Writing less data to disk means less I/O overhead, which can be critical on laptops, virtual machines, or resource-constrained systems. Later on, when you open the capture in Wireshark, smaller files load faster, filters apply quicker, and scrolling through packets feels noticeably smoother. Less data means less waiting, Finally, packet slicing can help reduce risk and noise. By not capturing full payloads, you lower the chance of collecting sensitive or private data you don’t actually need for troubleshooting. In many cases—like diagnosing TCP handshakes, DNS issues, or routing problems—the headers tell the whole story. Packet slicing keeps your captures focused, efficient, and a little safer, proving that sometimes less really is more when you’re packet wrangling.

I use packet slicing for a slightly different situation. Sure, I might have a large drive but now the network speeds are much higher than 15 years ago. The other important reason why I use packet slicing is when the data is sensitive and we are not allowed to see the captured data. There are some other reasons covered in the video.

The point of the video is to introduce you to packet slicing but you should go look at your packet capture tool to determine if you have packet slicing and how to configure it.

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A Random Walk(*) with Artificial Intelligence (by Paul W. Smith)

 

My wife and I recently joined some of the last homeowners to contribute to the $11 billion robot vacuum industry. Since I am usually the one who does the vacuuming, I liked the idea of completing this chore with the simple push of a button. It was an exciting day when I took our new Roomba out of the box, placed it on it’s little charging dock (which we located in the laundry room for our convenience), and then stood back and pressed “Clean” on my iPhone app.

Our Roomba (which we named “MaxBot”) banged up against the dryer a few times, then headed off down the hallway toward the living room. Our 13-yr old Shih Tzu soon began barking frantically, having failed to grasp the utility of this intruder. At his age, the only thing he does frantically anymore is eat; it was clear that a black hockey puck bigger than he is should not be scooting around the house unattended – at least not on his watch. Lesson #1: AI robots are not for everyone.

According to the promotional literature, robot vacuums use Artificial Intelligence to map out and store the boundaries of your home, calculating the most efficient way to cover every square foot. They are also supposed to anticipate their own demise, returning to the home base and recharging when needed.

On the morning after the first trial run, I awoke expecting to find a bunch of neatly vacuumed rows, like the freshly mowed patterns on a major league baseball field. I assumed the robot would be back in the laundry room, with full batteries and eagerly awaiting its next cleaning assignment. Instead, MaxBot was cowering guiltily under the dining room table and the living room looked as if it had been run over by a drunk monkey. While I was peacefully dreaming of things unrelated to household chores, MaxBot had texted a desperate message to my phone, pleading for a charge. The laundry room base station was the most convenient for us, but not for MaxBot which was unable to find its way back there. Lesson #2: AI will require some accommodations.

The naturally intelligent folks at Stanford have studied the impact of emerging AI developments on robotics, predicting that by the end of the next decade, domestic robots like ours will be much more common. They noted that current robot vacuums don’t do stairs, while the majority of homes have one or more of them (MaxBot will tip over about 30 degrees at our top stair before altering course in search of level ground). Those same folks who tape over the little camera on their laptop computer have also expressed concern that robotic vacuums contain valuable data about the size and floor-plan of our rooms, coupled with the geo-location of the home. Stanford NI believes these, and other problems, will eventually be overcome.

One of the most puzzling aspects of AI in many of its applications is that it can be hard for even the developers to understand what it’s up to. Algorithms based on self-learning, neural networks, or deep learning can make AI smarter without revealing exactly how it got that way. One example from the medical field was recently reported in New Scientist.

If your cardiologist diagnoses you with a serious incurable heart problem, you would understandably want to know just how much time you have left. Doctors expect this question and will make a reasonable and compassionate effort to answer it. Meanwhile, scientists in a Pennsylvania healthcare group have been evaluating an AI solution.

In order to avoid the inevitable ethical questions, their AI test system was given electrocardiogram data for patients whose date of demise was already known. The researchers not only found that the AI was much more accurate than the cardiologists in its predictions, it also forecast the risk of death in patients previously classified as having a normal ECG. Although this new AI technology can tell you when you will die, no one is quite sure how it knows.

All of which leads to the most important lesson of all, Lesson #3: Don’t expect too much from technology, especially one that cleans like a drunk monkey.

(*) The movements of an object or changes in a variable that follow no discernible pattern or trend.

Author Profile - Paul W. Smith - leader, educator, technologist, writer - has a lifelong interest in the countless ways that technology changes the course of our journey through life. In addition to being a regular contributor to NetworkDataPedia, he maintains the website Technology for the Journey and occasionally writes for Blogcritics. Paul has over 40 years of experience in research and advanced development for companies ranging from small startups to industry leaders. His other passion is teaching - he is a former Adjunct Professor of Mechanical Engineering at the Colorado School of Mines. Paul holds a doctorate in Applied Mechanics from the California Institute of Technology, as well as Bachelor’s and Master’s Degrees in Mechanical Engineering from the University of California, Santa Barbara.

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Using Wireshark to Find the HTTP Login Decode

 

In past articles I covered how to search for HTTP login credentials. After some feedback, I wanted to cover another approach used to find login credentials. Just want to start with a simple statement.

Packet Capture vs Accurate Packet Capture (Chris Greer)

I just wanted to take a few minutes to share the results of some of the "Capture Limit" testing I have been doing in my lab. These results were shared at Sharkfest Europe 2019 in Estoril, Portugal. The purpose of the session was to discuss the considerations of building your own capture appliance. I am not trying to promote any specific product; rather my goal is to demonstrate the limits where the accuracy of a capture on a laptop becomes questionable. 

During my performance testing, I found that there was a huge difference between capturing everything (no packet loss) and capturing everything correctly (packet timing is accurate). Before getting into the results of the testing, let me tell you a bit about my setup. 

The Rise of Artificial Stupidity (by Paul W. Smith)

 

"Never underestimate the power of stupid people in large groups.” – George Carlin

Judging from the number of times we use the word “stupid” in our daily discourse, you might conclude that it’s on our minds a lot. It should come as no surprise that Merriam-Webster has numerous definitions for stupid. We have all vilified a stupid computer that loses our work, or one that insists on peppering us with stupid popups. Exasperating events, as well as those which hold no interest for us, happen much too often.

It is a rare person who has never made a stupid decision, although those committed by unthinking individuals other than ourselves are much more common. For folks who are slow of mind, prone to unintelligent choices, acting in a careless manner, or just lacking in reason, MW also has a word. Stupid.

Whether driven by our preoccupation with stupidity or by our giddy infatuation with technology, we are rapidly pressing onward with the development of Artificial Intelligence. American author Sebastian de Grazia, who is often described as the “Father of Leisure”, predicted in 1967 that by the year 2020 automation technologies would give us a 16 hour workweek. Sebastian also warned that this would lead to boredom, immorality and personal violence. We are still waiting for the 16-hour workweek.

As with other shiny new technologies, the push to develop AI is driven by good intentions; better medical care, safer vehicles, and more efficient cities are often cited. The lingering fear that AI will take over our jobs does not seem to be impeding progress. Although the predictions from the “Father of Leisure” remain enticing, the reality is that some of us may end up with 16-hour workdays, while others are left with zero-hour workweeks.

While the objections to AI are focused on the jobs it will take, not much has been said about the subtle changes it will make in our culture. What happens when our daily tasks are taken over by computers? Do we understand the impact of the things we routinely do on our physical and mental health? We can already see how voice guidance from a GPS distorts the spatial awareness we once got from looking at a map. What other AI-induced changes await us?

Who among us wouldn’t love to have a personal assistant, one who would answer our phone, schedule our appointments and make restaurant reservations? Google Duplex is closing in on exactly that. Not only will it screen your calls and secure those coveted tables, it will do so in a convincing way, mimicking all the pauses, “ums” and “ahs” that humans typically use. Your maître d’ will never suspect that he was talking to a machine. We provide the basic data and constraints and AI takes over the human role, engaging with other humans by forming sentences and communicating intent.

If AI can communicate convincingly once given the rules, it’s not hard to imagine that at some point it will be able to listen and record information. Note taking, whether in meetings, lecture halls, or even courtrooms, is a tedious chore that most of us would gladly hand off to a machine. Won’t it be nice when we can depend on AI to hand us the written transcript of anything we desire? The connection between hearing, transcribing, prioritizing and recalling the material will be lost.

As for communicating in different languages, AI has been doing that in more ways than we realize. As annoying (or even humorous) as auto-correct can sometimes be, it is essentially the beginnings of a system which translates from one language (a grammatically incorrect or wrongly spelled one) to a proper one. That AI system can not only convincingly make restaurant reservations, but now it can also make them in French (and in your own voice).

Where AI really veers out of its lane is in the area of speaking and writing. Digital media has already started taking away our pencils, and with them a fundamental connection with how we think and communicate. Our various forms of language are not annoying barriers between us so much as windows into our innermost thinking. Adjusting tone and presentation, reflecting on and modifying our ideas and assessing our purpose are real-time processes that occur during human-to-human connection.

Noble Laureate and famous free-thinker Richard Feynman wrote about AI at a time when the technology was in its infancy. Dr. Feynman drew an analogy with the development of a machine to run fast like a Cheetah. You could certainly study videos of running Cheetahs, connect motors, linkages and software, and probably build a machine that accurately mimics a Cheetah. You might also note that it’s much easier to build a faster machine using wheels, or perhaps even one which flies just above the ground. AI will never think exactly like humans, but it can do some things much better and faster.

There are tedious (or dangerous) jobs that make good candidates for replacement. Assembly line workers, tax preparers or truck drivers are a few that should probably consider new careers. A radiologist reading x-rays or an oncologist formulating the most effective chemotherapy treatment will be difficult to replace but could benefit from AI augmentation. Some jobs will be missed in the short term, but the long-term benefit to humanity will be worth it.

Artificially Intelligent devices may take accurate notes, but will they ever capture that little twinkle in the Professor’s eye hinting that a certain topic will be on the next exam? When I struggle through a conversation in the small central Italian village of Soriano nel Cimino, am I just getting directions or am I connecting to the culture in profound ways that leave a lasting impression on my personal worldview? The genius of AI lies not in pushing it into all corners of our daily lives, but in recognizing where it frees us from ordinary activities, and where it begins to take away that which makes us human.

“The difference between stupidity and genius is that genius has its limits” – Albert Einstein

Author Profile - Paul W. Smith - leader, educator, technologist, writer - has a lifelong interest in the countless ways that technology changes the course of our journey through life. In addition to being a regular contributor to NetworkDataPedia, he maintains the website Technology for the Journey and occasionally writes for Blogcritics. Paul has over

40 years of experience in research and advanced development for companies ranging from small startups to industry leaders. His other passion is teaching - he is a former Adjunct Professor of Mechanical Engineering at the Colorado School of Mines. Paul holds a doctorate in Applied Mechanics from the California Institute of Technology, as well as Bachelor’s and Master’s Degrees in Mechanical Engineering from the University of California, Santa Barbara.