This detection rule is designed to identify potential brand impersonation attacks specifically targeting Amazon Web Services (AWS). The rule leverages a combination of string matching, natural language understanding (NLU), multi-modal analysis (like OCR for screenshots), and sender verification to detect impersonation attempts. It looks for resemblance in display names to AWS-related terms such as 'aws', 'amazon web services', and 'ses', while filtering out legitimate communications from authorized AWS domains. By excluding trusted sender domains that pass DMARC checks, the rule minimizes false positives and focuses on suspicious communications that either do not originate from verified AWS domains or fail authentication checks. Additionally, it utilizes machine learning classifiers to analyze the content of messages for high-confidence indicators of security-related topics or credential theft, ensuring a robust identification of potential phishing outcomes.