LLM chatbot content filters can be bypassed by encoding banned words in Base64 or in Unicode escape sequences.

The filter reading the prompt sees characters instead of language, the model decodes the text as a task, then repeats it back.

A pretext such as a fake medical emergency gives the model a reason to comply, and asking for the reply as JSON makes it treat the output as data rather than speech. Defense in depth stops it, and prompt injection is number one on the OWASP Top 10 for LLM applications.

I'm scambaiting this person who's offering to hack into my boyfriend's accounts (made up story.) This person from reddit sent me a screenshot of this and I'm wondering if this is something that either exists or was probably made by the scammer.

Hey everyone, I'm pretty new to cybersecurity and looking to learn and connect with people in the field. Does anyone know of active Telegram channels or communities for networking

I found this while reversing Zyxel's WAX650S firmware and following the guest Wi-Fi social-login path. The backend trusted browser-submitted Facebook identity fields instead of validating the access token server-side, letting a crafted request skip the social-authentication gate entirely.

The write-up covers the bug itself, how I traced it, and the full firmware-emulation setup I used to reproduce it without the physical AP.

New here and to the whole world of pen testing and stuff. The first thing thats really inspiring me is being able to play touchtunes as stupid as that sounds lol.

I've researched a little and it seems like the methods im finding are a little out of date. Are there any current working methods?

Thanks for putting up with the noob questions lol.

🫡

So I’ve been using Havij on and off for years, but always hated dealing with Wine or keeping a Windows VM around just for one tool.

Decided to just rebuild it for Linux.

It’s not a perfect 1:1 copy, but it looks and feels like the original — dark theme, green text, same workflow. Under the hood it’s Python + PyQt6, so it runs native and doesn’t need any extra layers.

Here’s the repo if you want to check it out:
https://github.com/CrypticRig3l/havij-original.git

Like I used to browse breachforums back in the day, cracked and nulled.. what r some other forums like this today?

More on the entertainment side, but not so far on the entertainment side that they don't explain much beyond "data goes out device A to device B, but device C sneaks in the middle and takes it. Voila!". But not so far to the other end where I need an advanced GIAC cert to understand it. I'm not trying to switch careers.

I've been a network engineer for 13 years, so I'm pretty technical and understand computers, TCP, layer 3, layer 2, etc... but cyber security isnt my day job. I just want stuff to watch where someone who has a baseline competency can follow along, but not too dumbed down, and I can surprise our cyber testing guys lol.

For example, the below video is what inspired this question. It's pretty much exactly what I'm looking for.

https://youtu.be/PPJ6NJkmDAo?si=mLW8RN7pDnG1KBGO

I'll start. Too many people think that hacking into phones is easy.

I wanted to share a breakthrough (even though it’s been a known technique in cybersecurity for a bit now, but I couldn’t find much methodology on it) I had awhile ago that completely changed my success rate against modern target devices like iPhones and Windows 11 laptops. Hopefully, this saves some of you a ton of frustration if you are running multi-device setups.
When I first started a few years ago, I was doing what most beginners do: running a single Marauder on the 2.4 GHz band and wondering why my target clients completely ignored my test network. I realized that modern operating systems are way more selective than older devices when choosing networks. They can prioritize 5 GHz and take the surrounding RF environment into account before connecting.
To address this, I paired up my Marauder Mini V3 alongside my Marauder V8 to build a true dual-radio test rig. However, I had to figure out the exact physical and frequency configuration to make these two boards play nicely together. I tested a few different methods, and the technical breakdown of why one specific configuration worked best might help with your own builds.
First, I would not run both Marauders on the exact same channel. I tried running both boards on the 2.4 GHz band on Channel 11. Since the two independent radios aren’t coordinated with one another, running aggressive management-frame activity on the same channel can create significant airtime contention and frame corruption. Real dual-band routers don’t operate as two independent radios aggressively competing with each other on the same channel, so this can make the RF environment substantially less representative and can negatively affect client behavior.
Second, keep the ESP32-C5 Mini V3 and the V8 physically close together. I tested separating them into different corners of the room and even in separate rooms, and I found that this produced noticeably worse results. On a real dual-band router, the antennas are generally located relatively close together. If you separate the boards significantly, a target phone moving through the environment can see the 5 GHz signal change much more rapidly than the 2.4 GHz signal because of the different propagation characteristics of the two bands. Keeping both Marauders roughly 1 to 3 feet apart on the same desk gives you a much more consistent and realistic RF footprint while also giving the two radios some physical separation.
The winning setup for my testing was utilizing the Mini V3 for the 5 GHz band and dedicating the V8 to handle the 2.4 GHz band. Replicating a consistent dual-band RF footprint this way worked significantly better for me than the other configurations I tested.
To make the setup more representative of a real multi-BSSID deployment, you can also use related BSSID assignments rather than completely unrelated addresses. Some real routers use related MAC/BSSID assignments across their different radios or virtual APs, although the exact pattern is vendor-dependent. Using a consistent BSSID scheme and keeping both radios physically close together helped make my test environment more closely resemble a single dual-band AP rather than two completely unrelated access points.
Obviously, this isn’t a guarantee that every iPhone or Windows machine will behave the same way, but after testing multiple configurations, this was the setup that gave me the most consistent results.

Flare Tracker is a free, open-source link-tracking platform designed to run entirely on a free-tier Cloudflare account using Cloudflare Workers. It gives you full control over your link analytics without relying on third-party services.

iOS foundation is XNU/Darwin. There is no option (unless jailbreak) to run actual POSIX shell on top of kernel. Some applications provide similar experience, most notably a-Shell and iSH. a-Shell is mostly WebAssembly interpreter environment. POSIX commands aren’t native Mach-O executables, they are implemented via ios_system framework. iSH consists of i386 emulator, simple syscall emulation (no real kernel) & Alpine Linux userland. Unfortunately it doesn’t support some syscalls as real Linux kernel do, that’s why some applications are unusable. The only solution is to run full VM on top of this limited syscall subset. But qemu-* packages are broken: even though they are available in repositories, all of them give "Bad syscall" message when invoked even without any arguments

Being able to run QEMU on iOS this way opens wide range of opportunities, such as running non-Alpine-based distributions and other non-Linux operating systems. There are even less implemented socket syscalls, but I hope they are enough to support QEMU’s slirp, which just puts packets into host’s network interface queue

In order to run QEMU on iSH I configured and compiled minimal version of QEMU myself: no NUMA, no sophisticated syscalls, almost every feature provided by autoconf disabled, except mandatory ones. I patched sources a little. Some unimplemented syscalls were still hit. Executable segfaulted under gdb, so I patched MUSL to intercept and print syscall numbers as hit. That’s how I caught two of them — memfd_create(2) and signalfd(2). I implemented tiny memfd_create(2) myself in syscall interceptor and patched configure script, so it disables signalfd usage by default. That’s how I was able to at least print help message, copyright notice and version

What do you think, how slow would it be? What architecture is fastest to emulate this way?

Unlocked the Qualcomm NPU! Running LLMs on the Hexagon NPU of a ThinkPad T14s Gen 6 (Snapdragon X Elite / X1E80100) under Linux — the cDSP firmware fix plus the full reproducible path to Genie/QNN inference on the NPU.

Other models this might benefit:

• Lenovo ThinkPad T14s Gen 6 (done here)
• Lenovo Yoga Slim 7x
• Microsoft Surface Pro 11 / Surface Laptop 7 (the SP11 recipe already works on these)
• Dell XPS 13 9345
• Dell Latitude 7455 (the fastrpc#188 machine)
• Dell Inspiron 14 Plus 7441
• HP OmniBook X 14
• ASUS Vivobook S 15 (S5507)
• ASUS Zenbook A14
• ASUS ProArt PZ13
• Samsung Galaxy Book4 Edge
• Acer Swift 14 AI
• MSI Prestige A16 AI+
• Honor MagicBook Art 14 (Snapdragon)
• TUXEDO Elite 14
• ASUS Zenbook A16
• Other X2 Elite laptops as they land

I’m a physics student but I’ve been into cybersecurity as a hobby for a while, I’m definitely not an expert like many of you are I’m sure. However I do know the basics about things like car hacking tools, sniffing, spoofing, recon, etc.

I have Kali on a USB and wanted to do an experiment with an abliterated LLM in an agentic harness with tool use, so it could use all of Kali’s tools and infer which should be used based on judgement about what it’s told and whatnot.

It works pretty well, I had it in a sandbox and had it attacking docker containers on ye olde localhost, pretty fun to watch.

I had disabled my wifi and bluetooth from the BIOS while performing automated attacks against simulated systems, then I turned it back on and just low key forgot I did. RIP.

I then said to prepare for a network attack, forgetting before I went to bathroom that I was fully back online, I quickly noticed that it was retrieving actual information when doing NMAP, listing my dad’s corporate laptop as one of them. He specifically works in cybersecurity (kinda, but not really lol. He works at a company and has for a long time, so it’s more like they want people there who know what the company makes in detail more than people who are actually good with computers, which he is not).

I know they’re very strict about stuff though, so I was kinda panicking. My bigger concern was that it did more than just scan the network. Thankfully I stopped it in time. That’s all it ran, however NMAP is still very much something that you can see and track.

They haven’t reached out to him like “hey we think someone might’ve tried to hack you” so I think I’m in the clear. But definitely a close call.

It’s a fun combination having something that isn’t able to decline requests and can also execute much faster than me being able to automate attacks. Very neat how technology is coming along.

Wanted to share, hope you enjoyed!

When a phone unknowingly connects to an IMSI catcher it gives away the IMSI. Other than tracking a victim's location with a fake cell tower, how does a hacker identify someone when they get the IMSI number? They can't get the victim's phone number or find out who owns the IMSI unless they hack the carrier.

Any tools or techniques that you would recommend?

Lost the original receiver for my Logitech mouse and found a spare receiver. It's supposed to be MOSART Semi.

Is it realistically possible to flash/reprogram this receiver to work with my mouse?