The rule "Job Scam (unsolicited sender)" is designed to detect potential job scam attempts that originate from unsolicited senders by analyzing the content and characteristics of incoming messages. The detection mechanism employs advanced techniques, including Natural Language Understanding (NLU) to classify message intent, identifying high-confidence job scam indicators. The rule analyzes the message body for keywords related to job offers, such as 'salary package' or polite phrases like 'kindly', which are often used in scams. Additionally, it assesses the sender's profile to confirm that they are unsolicited, checking for any prior malicious or spam messages, and ensuring no false positives are present. The rule aims to reduce the risk of business email compromise (BEC) and fraud by flagging suspicious communications that could mislead recipients into sharing sensitive information or making financial commitments. It emphasizes the importance of scrutinizing unsolicited messages carefully and leveraging machine learning for accurate threat detection.