The response to our 𝐀𝐠𝐞𝐧𝐭𝐢𝐜 𝐑𝐞𝐦𝐞𝐝𝐢𝐚𝐭𝐢𝐨𝐧™ launch has been incredible. In our last post, we showed how Agentic Remediation can take vulnerabilities from detection to automated patching with a human in the loop. This new demo highlights another reality of vulnerability management: many scanner findings are actually false positives. Scanners cannot account for the endless environmental conditions that determine whether a vulnerability is truly exploitable. In the video below, our AI agent investigates a flagged vulnerability in OpenSSL: 1️⃣ It researches the CVE and finds it is only exploitable on PowerPC CPUs 2️⃣ It checks the impacted asset directly and confirms it is running x86 3️⃣ It concludes that the vulnerability is a false positive, and no patch is required Here we see how Agentic Remediation reduces wasted cycles by validating exploitability in real time and separating signal from noise. Sanaz Yashar Ben Seri Snir Havdala #CTEM #ExposureManagement #VulnerabilityManagement #AgenticAI
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CROSSBOW encrypts all data using ChaCha20, one of the most powerful encryption algorithms available. In general, encryption and decryption are expected to slow down transmission speed. However, CROSSBOW experiences no slowdown at all thanks to its sophisticated thread separation and job control design. Encryption and decryption introduce no speed penalty—only a slight increase in CPU usage.
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In the last video, we learned how TTL defines when a cache object should expire. ⏱️ Now, let’s see how the Expiration Interval steps in to clean up those expired objects efficiently. Instead of checking every millisecond — which consumes tons of CPU — caches run cleanup threads at fixed intervals (like every 1 minute) to evict expired data. This keeps your cache blazing fast for storing and retrieving data, while expiration happens smartly in the background. ⚙️ Video URL: https://lnkd.in/gdjZWAn3 #SystemDesign #CacheExpiration #BackendDevelopment #CacheMechanism #InMemoryCache #TTL #ExpirationInterval #RedisCache #ServerArchitecture #PerformanceOptimization #Scalability #TechExplained #SoftwareEngineering #Microservices #ProgrammingConcepts #thegenzcoder
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𝐂𝐚𝐧 𝐲𝐨𝐮𝐫 𝐌𝐂𝐔 𝐭𝐞𝐥𝐥 𝐰𝐡𝐞𝐧 𝐢𝐭'𝐬 𝐛𝐞𝐢𝐧𝐠 𝐰𝐚𝐭𝐜𝐡𝐞𝐝? When developing firmware we're always peeking into our MCU's every move with a debugger. But does the silicon know that we are watching? Turns out, it can, and the check is surprisingly simple. Detecting an attached debugger can be used for several things: 🔹 Protect secrets like keys by wiping them from the memory 🔹 Enable special diagnostic modes only during development 🔹 Send tampering alerts from a device in the field Of course, for devices in the field, the best option would be to enable the MCU's memory readout protection, but there are cases where that may not be possible. The magic lies in a single bit (𝖢_𝖣𝖤𝖡𝖴𝖦𝖤𝖭) inside the ARM CoreDebug 𝖣𝖧𝖢𝖲𝖱 register: 𝘪𝘧(𝘊𝘰𝘳𝘦𝘋𝘦𝘣𝘶𝘨->𝘋𝘏𝘊𝘚𝘙 & 𝘊𝘰𝘳𝘦𝘋𝘦𝘣𝘶𝘨_𝘋𝘏𝘊𝘚𝘙_𝘊_𝘋𝘌𝘉𝘜𝘎𝘌𝘕_𝘔𝘴𝘬){ // 𝘋𝘦𝘣𝘶𝘨𝘨𝘦𝘳 𝘪𝘴 𝘢𝘵𝘵𝘢𝘤𝘩𝘦𝘥! } But 𝖣𝖧𝖢𝖲𝖱 is just one of the registers, for a deep-dive into all the registers that give the debugger its power, check out the full article on my blog. 👉 https://lnkd.in/dPs6x8f6 👈 #EmbeddedSystems #Firmware #MCU #ARM #CortexM #Debugger #TamperDetection
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Hey connections...Here's the latest on my 16-bit CPU project, up and running in Proteus. The core datapath is finally working, featuring a 16-bit ALU, two registers, and a fully operational data bus. The real story here, though, isn't the design...it's the debug process. I spent way more time hunting down bus contention and floating states than on the initial build, and that's honestly where the real learning happened. It's awesome to finally have a stable system that works as expected. Check out the demo! #DigitalLogic #ComputerArchitecture #CPUdesign #Proteus #ALU
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False sharing silently kills multithreaded performance. Threads may be working on different variables, but if those variables share a CPU cache line, they constantly invalidate each other’s caches. What is False Sharing? Multiple threads updating variables on the same cache line cause unnecessary cache synchronization, even if the variables are independent. The Effect Tight loops or frequent updates can become 2–5× slower, often without obvious symptoms. How to Avoid Separate hot variables on different cache lines: • C++11: alignas(64) • C++17: std::hardware_destructive_interference_size Both approaches isolate variables so threads update independently, eliminating cache conflicts. Source Code: https://lnkd.in/d8RK_mwT Next → Lock-Free Queues & Ring Buffers: atomic operations, memory ordering, and padding all in action. #CPP #Cpp #CPlusPlus #Concurrency #LowLatency #FalseSharing #LearnInPublic
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Semiconductor intellectual property (IP) provider CAST today announced the availability of a new SM4 Cipher IP Core, delivering compact, high-performance hardware implementations of the SM4 symmetric block cipher for both ASIC and FPGA designs. #cast #sm4 #cipher #ip #core #asic #fpga #semieda #semiconductor #semiconductors #semiconductorindustry #semiconductormanufacturing #semiwiki https://lnkd.in/g4bT6ZaQ
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Think your `if/else` order doesn't matter? Huge mistake. CPUs bet on which branch runs first to be faster. A wrong guess stalls everything. Simple fix: put the most common case in the `if`, not the `else`. But get it wrong, and you've just slowed your code down. Is this a critical optimization or a pointless micro-management? Fight me. #GaboTips
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How std::thread works, conceptually? std::thread is a type-safe abstraction over the OS’s low-level thread API (e.g., POSIX Threads, Win32 Threads). In the screenshot, I provide a wrapper to illustrate what's happening under the hood: 1-) Captures the callable and its arguments, perfectly forwarding them to preserve value categories. 2-) Encapsulates them into a lambda that takes ownership and is ready to run on a separate thread. 3-) Delegates to the underlying OS thread (kernel-level thread that the CPU executes). 4-) Controls the thread’s lifetime manually with join(). #ModernCpp #multithreading #cpp
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Think your `if/else` is just logic? It's a performance lottery. CPUs guess the path your code will take. A wrong guess is slow. Sorting data so your `if` condition is predictable in a loop can be a massive speed boost. The catch? It can make your logic a total mess. Is raw performance worth ugly code? #GaboTips
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An introduction to hardware offloading in DPDK library - For beginners ------------------------------------------------------------------------------- 'Hardware offloading' means transferring certain functionalities from software to NIC (Network Interface Card) hardware. The packet processing application can be accelerated by transferring or 'offloading' certain responsibilities from software to NIC's hardware. For example: The IP checksum calculation can be done by NIC's hardware instead of doing it in software, thus saving the precious CPU cycles. Some examples of offloading: 1. IP layer checksum calculation. 2. UDP layer checksum calculation. 3. VLAN header stripping. 4. ... This article explains the concept of hardware offloading for beginners. A guide for the software engineers who are interested in writing fast packet processing applications using DPDK library. #cpp, #cplusplus, #softwareengineering, #highperformancecomputing, #algorithms, #programming, #datapath, #dpdk, #softwaredevelopment https://lnkd.in/dxCCbUp6
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