Aggregator
CVE-2024-44282 | Apple visionOS User Information out-of-bounds (Nessus ID 211697 / WID-SEC-2024-3291)
CVE-2024-44282 | Apple iOS/iPadOS User Information out-of-bounds (Nessus ID 211697 / WID-SEC-2024-3291)
CVE-2024-44282 | Apple tvOS User Information out-of-bounds (Nessus ID 211697 / WID-SEC-2024-3291)
CVE-2024-44278 | Apple macOS information disclosure (Nessus ID 211697 / WID-SEC-2024-3291)
CVE-2024-44278 | Apple visionOS information disclosure (Nessus ID 211697 / WID-SEC-2024-3291)
CVE-2024-44278 | Apple iOS/iPadOS information disclosure (Nessus ID 211697 / WID-SEC-2024-3291)
CVE-2024-44278 | Apple watchOS information disclosure (Nessus ID 211697 / WID-SEC-2024-3291)
CVE-2024-44280 | Apple macOS prior 13.7/14.7 access control (Nessus ID 211697 / WID-SEC-2024-3291)
How Mimecast brings enterprise-grade email protection to API deployment
In this Help Net Security video, Andrew Williams, Senior Product Manager at Mimecast, walks through the company’s API-based email security protection for Microsoft 365 and Google Workspace environments. The video covers a core problem: AI-generated phishing and business email compromise are slipping past native Microsoft 365 controls. According to Mimecast’s State of Human Risk report, 64% of organizations know their built-in email security has gaps. Mimecast’s API solution connects via Microsoft Graph API in minutes, … More →
The post How Mimecast brings enterprise-grade email protection to API deployment appeared first on Help Net Security.
中国光伏,为什么“全球第一”却依然难赚钱?
从“人格”到“功能性情绪”:Anthropic 两篇新研究对 AI 情感交互的机理揭示
Fortinet 紧急修复遭利用的零日漏洞
Когда увольнение пошло не по плану. Бывший сотрудник прислал компании счет на $750000
真正改变历史走向的人,可能只是情报中心里一个沉默的分析员
真正的情报战,打的从来不是枪,是人性——CIA、KGB、MI6 最核心的能力到底是什么
【热点研判】美国延长俄油经哈输我制裁豁免,中亚能源通道博弈与我能源安全风险研判/马克龙访问日韩,跨区域安全联动与对我战略挤压
你以为只是喝了杯咖啡,其实已经被问出了所有秘密
微软将 Medusa 勒索软件联盟与零日攻击关联
Google study finds LLMs are embedded at every stage of abuse detection
Online platforms are running large language models at every stage of LLM content moderation, from generating training data to auditing their own systems for bias. Researchers at Google mapped how this is happening across what the authors call the Abuse Detection Lifecycle, a four-stage framework covering labeling, detection, review and appeals, and auditing. Earlier moderation systems, built on models like BERT and RoBERTa fine-tuned on static hate-speech datasets, could identify explicit slurs with reasonable accuracy. … More →
The post Google study finds LLMs are embedded at every stage of abuse detection appeared first on Help Net Security.