This detection rule targets potentially malicious PDF attachments purporting to be from Microsoft. The rule defines several criteria to identify these PDFs, including the presence of Microsoft-associated logos, specific keywords commonly found in phishing emails, and any embedded hyperlinks. The use of natural language understanding is noteworthy; it assesses the PDF's content for expressions indicating urgency or suspicious activity such as "password", "shared documents", or "security update". The rule also incorporates sender authentication checks to filter out messages from trusted domains unless they fail the DMARC authentication. By combining data from various analysis methods such as computer vision, file analysis, and sender profile evaluations, the rule effectively reduces false positives while maintaining a high detection rate for malicious attachments aimed at credential theft and malware delivery. This approach helps secure email communications, mitigating impersonation and phishing risks linked to malicious attachments.