Krebs指出，住宅代理服务是恶意流量的主要来源，涵盖账户接管、广告欺诈和AI内容抓取。
正如过去一年本站多篇报道所详述，住宅代理服务是大量不受欢迎且往往带有恶意的流量的主要来源，包括账户接管、广告欺诈以及为AI项目进行的大规模内容抓取。原文 (en)
As detailed in several stories here over the past year, residential proxy services are a major source of unwanted and often malicious traffic, including account takeover activity, advertising fraud, and mass content scraping for AI projects.
Krebs警告称住宅代理在政府和企业网络中极为常见，而不仅限于普通用户设备。
住宅代理对毫不知情的终端用户而言风险很大，而它们在政府和企业网络中也极为常见。原文 (en)
As risky as residential proxies can be for unsuspecting end users, they are all too commonly found on government and corporate networks.
Krebs 警告，支付赎金无法保证被盗数据被删除，PowerSchool 受害者遭二次勒索即为例证。
虽然没有人指称 ShinyHunters 是针对 PowerSchool 用户第二波勒索的幕后黑手，但这一事件凸显了一个现实：没有任何技术手段能够核实威胁行为者是否如承诺那样删除了被盗数据，也无法阻止他人滥用同样的记录。原文 (en)
While nobody has alleged ShinyHunters was behind the second wave of extortion against PowerSchool users, the incident drives home the reality that there is no technical way to verify the threat actors have deleted the stolen data as promised, or prevent others from abusing the same records.
Krebs 指出事件响应行业的结构性问题：拒绝协助支付赎金的公司会被愿意付款的公司取代，导致赎金谈判行业存在利益冲突。
但并非所有网络取证和事件响应公司都愿意代表客户向勒索软件团伙支付赎金。因此，一旦受害企业决定付款，那些拒绝奖励勒索者的公司总会被毫无顾忌的公司所取代。原文 (en)
But not all cyber forensics and breach response companies will agree to facilitate payments to ransomware groups on behalf of their clients. As a result, once victim firms make a decision to pay, the firms that eschew rewarding extortionists are invariably replaced by companies that have no such qualms.
Krebs 认为 Cryptomus 和 Heleket 的国际金融服务资质似乎来自西撒哈拉一个虚假监管机构颁发的假牌照。
像 Cryptomus 和 Heleket 这样的实体，提供国际金融服务的授权从何而来？答案似乎涉及由一个虚假监管机构监管的假金融机构，而该机构位于一个未被广泛承认为主权国家的地区。原文 (en)
Where do entities like Cryptomus and Heleket derive their authority to offer international financial services? The answer appears to involve fake financial institutions overseen by a phony regulatory body positioned in a country that is not widely recognized as a sovereign nation.
Krebs指出AI驱动的漏洞发现导致微软补丁数量创纪录，给需要逐一测试补丁的企业安全团队带来额外压力。
微软将漏洞发现数量激增归功于大语言模型，想必修复这些漏洞的许多补丁也要归功于 AI。与此同时，安全专家一直警告，微软这些异常庞大的补丁批次正在给企业安全团队带来额外压力，这些团队往往需要先测试每个更新，再在网络中部署，以确保修复不会给其他软件造成问题。原文 (en)
Microsoft credits large language models for the high volume of bug discovery, and presumably AI gets credit for many of the patches used to fix these flaw. Meanwhile, security experts have been warning that these unusually large patch volleys from Microsoft are placing extra strain on corporate security teams, which often have to test individual updates before deploying them across a network to ensure the fixes don’t cause problems for other software.