In just three months, the massive Aisuru botnet launched more than 1,300 distributed denial-of-service attacks, one of them setting a new record with a peak at 29.7 terabits per second.
Aisuru is a huge botnet-for-hire service that provides an army of routers and IoT devices compromised via known vulnerabilities or through brute-forcing weak credentials.
Internet management and infrastructure company Clou...
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Technical cheat sheets are one of those things you don’t truly appreciate until you’re knee-deep in a problem and need the right command right now. When you’re working with Linux—especially with command-line utilities like cp—even seasoned pros can blank on syntax or flags. A good reference sheet acts like a mental shortcut, giving you instant access to the commands you use often, the ones you occasionally need, and the obscure options you’ve inevitably forgotten. Instead of digging through man pages or searching the web, you have the essentials neatly distilled into something you can scan in seconds.
-r, -v, --parents, --no-clobber, etc.) isn’t a realistic expectation—especially when you're switching between tasks all day. A good cheat sheet reduces that mental juggling. It lets you focus on solving the actual problem instead of second-guessing whether you’re about to overwrite the wrong directory or miss a crucial flag that changes behavior. That reduction in friction adds up to faster, more accurate work.
There’s also an incredible amount of invisible effort that goes into creating a solid technical reference sheet. Anyone who has made one knows it’s more than “just jotting down commands.” You have to test each use case, verify edge behaviors, compare different versions of the command across distributions, and decide what’s essential enough to include. It’s a balance between completeness and usability. Too little info, and it’s pointless. Too much, and it becomes another overwhelming document no one wants to use. Curating clean, reliable, concise technical guidance takes real time, technical depth, and often several iterations.
From Dan Nanni www.study-notes.org
When you're staring at a firehose of packets in Wireshark, trying to find that one moment in a chaotic capture can feel like decoding ancient hieroglyphics. That’s where packet bookmarks—or more accurately, sending a deliberate “ping” or identifiable packet during a trace—comes in clutch. By injecting a unique packet into the capture at the right moment, you create a visual anchor that helps you quickly zero in on the part of the traffic you actually care about, instead of scrolling endlessly like you're searching for lost treasure.
This technique is especially handy during live troubleshooting. Let’s say you’re working with a remote user and need to isolate when they clicked something, recreated a bug, or triggered a specific network event. Instead of guessing, you have them run a quick ping or curl command right when the issue occurs. That injected packet shows up as a bright, unmistakable blip in the capture. Once you find it, you’re instantly transported to the exact section of packets you need to analyze—no more hunting through thousands of frames by timestamp alone.
It also helps when multiple engineers are involved. If you're collecting captures from different vantage points—client, server, firewall—you can have everyone trigger the same “bookmark” moment. Later, when comparing traces, those bookmarks become synchronization points. This makes aligning timelines between captures a breeze and eliminates those awkward moments where you're trying to figure out why the client’s clock is three minutes off from the server’s.
Ultimately, packet bookmarks are simple, fast, and surprisingly powerful. They don't require any special Wireshark features or advanced filters—just a strategically injected, recognizable packet. Next time you're taking a trace, throw in a deliberate ping or custom packet at key moments. Your future self, scrolling through a mountain of traffic at 2 AM, will thank you.
Enjoy
In theory, an easy task. In practice? It went about as well as trying to start a campfire with wet spaghetti.
At first glance, the script looked like it whispers, “Trust me, I know what I'm doing.” So naturally, like any responsible tech professional, I copied it, pasted it, hit Enter, and waited for magic. What I got instead was a spectacular combination of syntax errors, modules that apparently only exist in another dimension, and authentication failures so dramatic that I’m pretty sure the server judged me personally. The script didn’t “execute” so much as it “flopped politely.”
As I debugged the digital Picasso it had produced, I realized the script wasn’t even using real-world PowerShell SSH practices. It had invented its own syntax, mashed together three different module styles, and confidently referenced a function I’m 99% sure was made up on the spot. It’s like the AI had the right vibe of a script, but none of the actual functionality. Meanwhile, Google AI sat there proudly like, “You’re welcome,” while I manually rewrote the whole thing like a disappointed parent fixing a child’s science fair project made out of duct tape and crayons.
So here’s the moral of the story: AI code suggestions are great for inspiration, terrible for production, and absolutely perfect if you enjoy chaos. Don’t blindly trust them. Verify, test, tweak, and for the love of uptime, don’t assume they actually know how PowerShell works. Otherwise, you too may find yourself arguing with a server because you copy-pasted code written by a very confident, very imaginative robot author who has clearly never SSH’d into anything in its life.
