Write SQL to flag coordinated fake accounts

Assume the current date is 2025-06-01. You are given the following tables: - users(user_id, created_at, country) - logins(user_id, login_time, ip, country, device_id) - friend_requests(sender_id, receiver_id, sent_time, accepted, accepted_time) - messages(sender_id, receiver_id, sent_time) - posts(post_id, user_id, created_time) - devices(device_id, user_id, device_type) Using these tables, write a single SQL query (CTEs allowed) that outputs, for each user, the fields user_id, F1, F2, F3, and risk_score, where: • Consider the 7-day period from 2025-05-26 to 2025-06-01 (inclusive). • F1 = 1 if, using only login rows with login_time between '2025-05-26 00:00:00' and '2025-06-01 23:59:59', there exists at least one 24-hour window in which that user logs in from 3 or more distinct countries; otherwise F1 = 0. • F2 = 1 if, within 5 minutes of the account creation time (created_at), the user sends messages to 3 or more distinct recipients (receiver_id); otherwise F2 = 0. (This condition is independent of the 7-day window; it uses all messages relative to created_at.) • F3 = 1 if, considering only friend_requests with sent_time between '2025-05-26 00:00:00' and '2025-06-01 23:59:59', the user (as sender_id) sends at least 20 friend requests and their acceptance rate in that period is less than 10% (acceptance rate = accepted requests / total requests); otherwise F3 = 0. Compute a risk_score for each user as: risk_score = 0.5 * F1 + 0.3 * F2 + 0.2 * F3 Return only users with risk_score >= 0.5. Write a single SQL query that produces this result.