• Personalized risk assessments: Analyze device and account configurations, recent activity, and behavior to identify vulnerabilities and recommend prioritized fixes (e.g., weak passwords, outdated software, exposed personal data).
• Intelligent password management: Generate strong passwords, detect reused or compromised credentials, and auto-fill securely; alert users when leaks appear in breach databases (e.g., via hashed matching).
• Phishing and scam protection: Scan emails, messages, and webpages in real time to detect phishing, malicious links, or social-engineering patterns and warn or quarantine suspicious items.
• Adaptive multi-factor authentication (MFA): Suggest and enforce appropriate MFA levels based on contextual risk (location, device, transaction size) and streamline authentication flows (e.g., push notifications, biometric prompts).
• Automated software hygiene: Monitor and auto-install critical security updates, suggest safer app alternatives, and detect risky permissions or background behaviors.
• Secure browsing assistants: Provide content summaries, flag trackers and fingerprinting attempts, and offer privacy-preserving reading modes or sandboxed previews of untrusted sites.
• Data-minimization and privacy coaching: Recommend minimizing data shared with services, create templates for privacy settings, and guide account deletion or data export processes.
• Anomaly detection and incident response: Detect unusual account or network activity, triage potential incidents, suggest immediate containment steps (lock account, change passwords), and produce clear remediations.
• Usable security nudges: Offer timely, comprehensible prompts (not alarmist) to encourage good habits—regular backups, secure Wi‑Fi use, safe sharing practices—tailored to user skill level.
• Education and simulations: Provide bite-sized, context-relevant training and phishing simulations to improve user awareness without overwhelming them.

References: NIST Special Publication 800-63 (digital identity), OWASP guidance on secure development and user education, recent surveys on AI for cybersecurity (e.g., Gartner, 2023).