第2章 2.3 HTTP/HTTPS协议详解：请求/响应/状态码
前几天朋友发我一个链接，说点进去银行卡里的钱就没了。我拿过来一看，网址栏前面是 http:// 不是 https://，当场就明白了——他在钓鱼网站输入了密码，数据全是明文传输，黑客在咖啡店WiFi里就能截获。这事儿说白了，就是HTTP和HTTPS的区别没搞懂。
《自然》（20240321出版）一周论文导读
Abstract:Floods are one of the most common natural disasters， with a disproportionate impact in developing countries that often lack dense streamflow gauge networks. Accurate and timely warnings are critical for mitigating flood risks， but hydrological simulation models typically must be calibrated to long data records in each watershed. Here we show that artificial intelligence-based forecasting achieves reliability in predicting extreme riverine events in ungauged watersheds at up to a five-day lead time that is similar to or better than the reliability of nowcasts from a current state-of-the-art global modelling system . In addition， we achieve accuracies over five-year return period events that are similar to or better than current accuracies over one-year return period events. This means that artificial intelligence can provide flood warnings earlier and over larger and more impactful events in ungauged basins. The model developed here was incorporated into an operational early warning system that produces publicly available forecasts in real time in over 80 countries. This work highlights a need for increasing the availability of hydrological data to continue to improve global access to reliable flood warnings.
“开箱”国内知名买手品牌hug新店
“开箱”国内知名买手品牌hug新店回溯 Retrace空间略呈方形，有城墙环绕，四面均设城门，城内纵横交错，布局有如棋盘，此为庞贝。因维苏威而毁灭，因毁灭而得到永恒。
2.1 OSI七层模型与TCP/IP协议栈 —— 网络的骨架
上次写完工具概览，有朋友问我："阿亮，我想学渗透测试，但直接看Burp Suite感觉像在看天书，有没有什么必须先把基础打牢？"有。而且这个基础，是所有网络安全学习的地基。不懂网络协议，学安全就像盖房子不打地基——看起来在盖，其实随时会塌。
网络安全｜第4课：实验环境搭建——打造你的"黑客实验室"
你好，我是阿亮。今天聊聊实验环境搭建。为什么需要实验环境？上节课我们讲了法律法规边界，知道了很多攻击手法不能真刀真枪练。那怎么练技术？答案：搭建实验环境。
大模型其实很脆弱！科学家发现仅需250份恶意文档即可攻陷大模型
当业界普遍相信更大的模型意味着更强的安全性时，来自Anthropic、英国AI安全研究院、艾伦·图灵研究所与牛津大学的联合研究团队揭示了一个令人不安的事实：仅需约二百五十个恶意文档，就足以在任意规模的大语言模型中植入可触发的后门，且这一数字与模型参数量几乎无关。
最大规模AI投毒实验结果惊人：仅250个样本，就让大模型中毒
最新研究揭开了一个令人不安的真相：仅需250份恶意文档，就能让研究中的AI模型“中毒”，成功植入后门！这颠覆了“模型越大越安全”的基本假设。更可怕的是，这意味着攻击成本与训练集规模无关，随着大模型的训练数据越多，攻击者的相对成本反而在降低。