See how Foundry turns LLM hunches into verified findings on Langflow, MLflow, and PyGoat, using an evidence gate and an honest look at token cost.
Source: https://blogs.cisco.com/cisco-devnet/foundry-verified-security-findings-part-2. 8 Sync News only summarizes and links out; content copyright belongs to the authors and original sources.
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Try itN-able has taken its hosted N-central environments offline and urged on-premises customers to shut down their servers after a security researcher publicly disclosed more than 30 alleged zero-day vulnerabilities, including exploits that could let attackers take over vulnerable systems.
Understanding how malicious actors infiltrate networks is the first step to building resilient infrastructure. To help developers and aspiring security analysts learn the fundamentals of offensive sec
pwn.college is a free, hands-on education platform for learning core cybersecurity and hacking skills, maintained by a team at Arizona State University. Learners progress through belt ranks, starting with a 'white belt' and earning belts through practice. Hackers continue beyond the platform to 'brown belt' and eventually 'black belt' status, which must happen outside the dojo. The site powers much of ASU's cybersecurity curriculum and asks users not to post writeups or walkthrough videos of challenge solutions. It points learners toward CTFtime.org for Capture The Flag events and a GitHub list of wargames for further practice. The underlying infrastructure is open source and accepts pull requests, though some modules remain closed-source.
...explained visually (with tradeoffs in production).
How DeepSeek Harness's Super-agent works: a Router, isolated Workers, event triggers and a Watchdog let one AI agent run many tasks. Diagrams inside.
UK shoppers caught up in third-party security mess, and nobody knows whether the data was flushed away
I document how I use AI, one year after my first writeup. Everything's completely different.
Bối cảnh của bài viết khám phá liệu chúng ta có đang quá tư duy hóa việc tạo prompt hay không. Nguyên nhân kỹ thuật được nêu ra là một phương pháp đơn giản chỉ cần 3 yếu tố: context, instruction, và input, được đề xuất bởi nhà sáng tạo Claude Code. Hệ quả khi áp dụng phương pháp này là việc tạo prompt hiệu quả trở nên dễ dàng hơn nhiều so với những cách phức tạp trước đây. Điều đáng học là ngay cả những AI model mạnh nhất hiện nay như Claude 3 hay GPT-4 vẫn phản ứng tốt với prompt có cấu trúc đơn giản này.
Bài viết này giúp bạn hiểu ra cách đơn giản hóa việc tạo prompt hiệu quả chỉ với ba yếu tố cơ bản.
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