Threat Modeling and Attack Analysis Questions

Analyze likely attacker motivations and vectors against platform scale systems and design layered defenses and detection. This includes formally identifying assets and threat surfaces, building threat models and attack trees, enumerating concrete adversary techniques such as account takeover, credential stuffing, payment fraud, data scraping, distributed denial of service attacks, and insider threats, and prioritizing risks by likelihood and business impact. Candidates should describe concrete mitigations and trade offs for each vector, detection signals and telemetry to collect, alerting and tuning strategies to control false positives, automated and manual response playbooks, adversary emulation and red team approaches, integration of threat intelligence, and metrics to measure effectiveness. Practical controls to discuss include authentication hardening and multi factor authentication, rate limiting and abuse throttling, behavior and device signals, fraud scoring, web application controls, content protection, network and infrastructure controls, secrets and key management, and containment and recovery approaches.