Deploys AI/NLP-driven detection system for business email compromise (BEC) attacks, analyzing writing style, behavior patterns, and contextual anomalies to catch rule-evading fraud.
npx claudepluginhub killvxk/cybersecurity-skills-zhThis skill uses the workspace's default tool permissions.
AI 驱动的 BEC 检测使用机器学习、NLP 和行为分析来识别不包含恶意链接或附件的复杂冒充攻击。传统基于规则的过滤器会遗漏这些攻击，因为 BEC 完全依赖社会工程学。现代 AI 方法分析写作风格、语调、词汇、语法模式和行为上下文，以确定邮件是否真实来自所声称的发件人。基于 BERT 的模型在 BEC 检测中达到 98.65% 的准确率，AI 增强平台比基于关键词的规则显示出钓鱼识别率提升 25%。
Deploys AI/NLP systems to detect business email compromise attacks by analyzing writing style, behavioral patterns, and contextual anomalies. For SOC threat hunting and incident response.
Deploys AI/NLP systems to detect business email compromise attacks by analyzing writing style, behavioral patterns, and contextual anomalies in emails.
Detects business email compromise (BEC) attacks using email gateway rules, behavioral analysis, and financial controls. Useful for phishing defense against executive impersonation and fraud.
Share bugs, ideas, or general feedback.
AI 驱动的 BEC 检测使用机器学习、NLP 和行为分析来识别不包含恶意链接或附件的复杂冒充攻击。传统基于规则的过滤器会遗漏这些攻击，因为 BEC 完全依赖社会工程学。现代 AI 方法分析写作风格、语调、词汇、语法模式和行为上下文，以确定邮件是否真实来自所声称的发件人。基于 BERT 的模型在 BEC 检测中达到 98.65% 的准确率，AI 增强平台比基于关键词的规则显示出钓鱼识别率提升 25%。