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AI 资讯

How AI Hunts Vulnerabilities: A Security Researcher's New Partner

The Transition A few years ago, bug hunting was a manual craft. You scanned subdomains with one tool, tested endpoints with another, and stitched results together by hand. Today, AI changes the speed entirely. Not by replacing the hunter. By eliminating the boring parts. What AI Actually Changes 1. Reconnaissance at Scale Subdomain enumeration, port scanning, and technology fingerprinting used to take hours. AI-powered pipelines now do this in minutes: Passive reconnaissance via Certificate Transparency logs, search engines, and DNS records Automated crawling and endpoint discovery Technology stack detection from response headers and HTML patterns JavaScript file analysis for hidden endpoints and API keys The machine does the grunt work. The human interprets the results. 2. Pattern Recognition Vulnerability classes have signatures. SQL injection looks different from XSS, which looks different from SSRF. AI models trained on thousands of real vulnerabilities can flag suspicious patterns faster than manual code review. This is not about finding zero-days. It is about catching the low-hanging fruit that everyone else misses because they are in a hurry. 3. Intelligent Fuzzing Traditional fuzzers throw random data at endpoints and wait for crashes. AI-guided fuzzers understand the input format and generate test cases that explore edge cases a human would not think of. The result: fewer requests, better coverage, higher signal-to-noise ratio. Where AI Struggles Business Logic Flaws AI does not understand your application's purpose. It cannot tell if a discount code is applied twice, or if a user can access another user's private data through a convoluted API flow. These are the vulnerabilities that require context. Human context. Authentication Logic Authentication bypasses are often creative. They exploit the gap between what the developer intended and what the code actually enforces. AI can find simple auth flaws, but multi-step authentication bypass chains still need h

2026-05-29 原文 →
AI 资讯

Microsoft 365 Copilot gets a speed boost and cleaner design

Microsoft is launching a revamped version of Microsoft 365 Copilot, offering a cleaner design that the company claims loads twice as fast. As part of this update, Copilot will provide more reliable and structured responses that are easier to scan, according to Microsoft. The redesign, which is rolling out across desktop and mobile devices, comes […]

2026-05-29 原文 →
开发者

What’s next for Microsoft’s Surface PCs?

Nearly 10 years ago I reviewed my favorite Surface device. Microsoft hand-delivered its Surface Studio all-in-one PC to me, and I was hooked from the moment I switched it on. It had a beautiful floating touchscreen that you could push all the way down into a drawing board mode, making it unlike anything I had […]

2026-05-29 原文 →
AI 资讯

Why DDR5 Bandwidth Kills Dual-LLM Inference on APUs (Benchmarks Inside)

Did you know that a 35-billion-parameter model can generate tokens at the same compute cost as a 4B model? That single fact made me abandon a multi-model agent architecture I'd spent a weekend building. But I had to run the benchmarks first to understand why. Here's the full breakdown, with commands, numbers, and the architectural reason it all falls apart on shared-memory hardware. The Discovery That Changed Everything I'd been running qwen3.6:35b on my Minisforum UM790Pro for weeks as my daily coding assistant. 17.8 tokens/second -- genuinely usable for interactive work. But I kept wondering: could I run a lightweight sidecar model alongside it for quick classification and tool-calling in an agent pipeline? Before I even started benchmarking, I dug into what qwen3.6:35b actually is under the hood. It's a Mixture of Experts model: 256 total experts with only 8 activated per token. The architecture also incorporates SSM (State Space Model) components alongside traditional attention -- Mamba-style layers that handle certain sequence patterns more efficiently than pure transformers. The math hit me: 8 out of 256 experts means each token only touches roughly 4-5B parameters worth of compute. The model carries 36 billion parameters of knowledge , but its per-token cost is comparable to a small dense model. I was planning to run a separate 4B model for "fast tasks" next to a model that already operates at 4B-class speed. But I had to prove it with numbers. Hardware and Ollama Setup The UM790Pro specs that matter for this experiment: CPU: AMD Ryzen 9 7940HS (Zen 4, 8C/16T) iGPU: AMD Radeon 780M (12 RDNA 3 compute units) RAM: 96 GB DDR5-5600 (~80 GB/s bandwidth) GPU memory pool: 2 GB dedicated VRAM + 46 GB GTT = 48 GB GPU-accessible That 48 GB GPU pool sounds enormous until you realize it's carved from the same DDR5 that the CPU also uses. There is no separate GDDR6 bus. Everything -- CPU inference, GPU inference, KV caches, OS operations -- flows through one 80 GB/s pipe.

2026-05-28 原文 →
AI 资讯

These new iOS 27 renders hint at Siri’s big redesign

Apple's long-awaited Siri overhaul, expected to arrive in iOS 27, might look a lot like ChatGPT with a splash of Liquid Glass. Renders from Bloomberg offer a preview of iOS 27, including the new app and chat interface for Siri. The renders are "based on information viewed by Bloomberg and people with knowledge of [Apple's] […]

2026-05-28 原文 →
AI 资讯

Microsoft Introduces MDASH for Large-Scale AI Vulnerability Research

Microsoft has introduced a new AI-driven vulnerability discovery system called MDASH, a multi-model agentic security platform designed to automate large-scale code auditing across Windows and other Microsoft software environments. The system combines more than 100 specialized AI agents that work together to scan, validate, debate, and prove vulnerabilities across complex codebases. By Robert Krzaczyński

2026-05-26 原文 →
开发者

The State of CSS Centering in 2026

Despite the countless number of online resources, it’s easy to get confused when trying to center an element. There are documented solutions, but do you really understand why the code you picked works? Let's look at the current state of centering options today in 2026. The State of CSS Centering in 2026 originally handwritten and published with love on CSS-Tricks . You should really get the newsletter as well.

2026-05-22 原文 →
AI 资讯

Alleged Kimwolf Botmaster ‘Dort’ Arrested, Charged in U.S. and Canada

Canadian authorities on Wednesday arrested a 23-year-old Ottawa man on suspicion of building and operating Kimwolf, a fast spreading Internet-of-Things botnet that enslaved millions of devices for use in a series of massive distributed denial-of-service (DDoS) attacks over the past six months. KrebsOnSecurity publicly named the suspect in February 2026 after the accused launched a volley of DDoS, doxing and swatting campaigns against this author and a security researcher. He now faces criminal hacking charges in both Canada and the United States.

2026-05-22 原文 →
AI 资讯

Anti-DDoS Firm Heaped Attacks on Brazilian ISPs

A Brazilian tech firm that specializes in protecting networks from distributed denial-of-service (DDoS) attacks has been enabling a botnet responsible for an extended campaign of massive DDoS attacks against other network operators in Brazil, KrebsOnSecurity has learned. The firm's chief executive says the malicious activity resulted from a security breach and was likely the work of a competitor trying to tarnish his company's public image.

2026-04-30 原文 →
产品设计

‘Scattered Spider’ Member ‘Tylerb’ Pleads Guilty

A 24-year-old British national and senior member of the cybercrime group "Scattered Spider" has pleaded guilty to wire fraud conspiracy and aggravated identity theft. Tyler Robert Buchanan admitted his role in a series of text-message phishing attacks in the summer of 2022 that allowed the group to hack into at least a dozen major technology companies and steal tens of millions of dollars worth of cryptocurrency from investors.

2026-04-21 原文 →