If I had to Interview Security Again, I Would Study These 40 Real Security Engineering Problems
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Today’s post is something I wish I had in my early days.
When I was preparing for security engineering roles, I wasted months jumping between courses, blogs, scattered GitHub repos, and random CTF writeups. None of them helped me understand the problems real security engineers solve inside big companies.
If I could go back, I would spend my time learning the fundamentals through real problem statements like the ones below.
These are the exact challenges that come up at scale. These are the conversations you have during interviews. These are the issues you solve once you start the job.
If you want to break into security engineering in 2025, learn these by doing.
Not by memorising definitions. Not by watching a hundred videos.
By understanding how systems actually work.
1) Risk, Access, Identity
➤ Design a secure authentication system for a billion users
• Think about password hashing, rate limits, and device signals.
• Study how login flows break when latency increases at scale.
• Understand how to store credentials safely and how to respond to mass credential stuffing.
➤ Build OAuth based login for third party apps
• Understand authorisation codes, refresh tokens, and redirect security.
• Think about scopes and how to limit what apps can access.
• Handle token theft, rotation, and revocation properly.
➤ Design a Zero Trust access model inside a large company
• No request is trusted by default. Every access is verified.
• Study identity based routing, device posture checks, and continuous auth.
• Understand the tradeoff between developer productivity and stricter access controls.
➤ Create an automated privileged access review system
• Detect unused admin rights and auto remove them.
• Trigger reviews for high risk roles on a schedule.
• Maintain audit logs that satisfy compliance teams without slowing engineers down.
➤ Build a secure session management system for a mobile app
• Think about session IDs, refresh tokens, inactivity timeouts.
• Handle sessions across multiple devices and platforms.
• Protect sessions from replay, theft, and fixation.
➤ Design an MFA service that works reliably worldwide
• Consider SMS latency, unreliable networks, and fallback strategies.
• Support TOTP, push notifications, and hardware keys.
• Reduce friction while increasing assurance.
➤ Handle account recovery securely at scale
• Protect against social engineering and recovery abuse.
• Use device history, previous login signals, and risk scoring.
• Build flows that work even when users lose all devices.
2) Network Security and Traffic Protection
➤ Design a DDOS detection and mitigation pipeline
• Understand volumetric, protocol, and application layer attacks.
• Build real time traffic analytics and automated blocking.
• Plan for false positives so you never take down your own customers.
➤ Build secure service to service communication inside a microservices mesh
• Study mTLS, service identity, and certificate rotation.
• Never rely on IP based trust.
• Handle encryption with minimal CPU overhead.
➤ Design TLS termination and certificate rotation for large fleets
• Automate renewal, deployment, and revocation.
• Understand perfect forward secrecy and cipher suite choices.
• Build fallback strategies for expired or misconfigured certs.
➤ Build an internal VPN replacement for employees
• Move from network based trust to identity based trust.
• Support roaming users, mobile devices, and low bandwidth regions.
• Add logging and policy enforcement without slowing connections.
➤ Detect internal port scans or lateral movement attempts
• Track abnormal traffic patterns inside VPCs.
• Build alerting for privilege escalation pathways.
• Identify service misuse before it becomes an incident.
➤ Create a network segmentation strategy for production and staging
• Break high risk blast zones into smaller segments.
• Enforce strict rules between sensitive and non sensitive services.
• Keep developer experience smooth while improving safety.
3) Application and API Security
➤ Design a secure API gateway with rate limits and token validation
• Handle JWT verification, signature checks, and expiration rules.
• Build dynamic rate limits based on user behavior.
• Add traffic metadata for incident response and abuse detection.
➤ Build a system that auto detects broken access control
• Watch for privilege escalation in real user traffic.
• Catch endpoints that leak data because of missing checks.
• Integrate detection with engineering dashboards.
➤ Create an automated static analysis pipeline for monorepos
• Identify risky patterns in shared libraries early.
• Integrate SAST with pull requests so devs fix issues before merging.
• Track improvements over time with metrics.
➤ Detect business logic abuse in user workflows
• Understand how attackers exploit rules that developers never considered.
• Build anomaly detection models for edge cases.
• Study real incidents in fraud, gaming, and financial apps.
➤ Build a safe secrets storage and rotation service
• Use KMS or HSM backed encryption for sensitive keys.
• Rotate secrets automatically without breaking services.
• Alert teams when keys are leaked in logs or repos.
➤ Design a system that stops replay attacks in distributed environments
• Use nonces, timestamps, and signature verification.
• Prevent double spending in high volume transactional systems.
• Handle clock skew and distributed systems complexity.
4) Data Protection and Encryption
➤ Build a client side encryption flow for personal data
• Protect data even if servers are compromised.
• Manage key distribution without exposing secrets.
• Handle revocation and re encryption when users update their data.
➤ Design a key management service with HSM backed protection
• Isolate keys from applications completely.
• Handle signing, decryption, and rotation in hardware.
• Build auditing that tracks every operation.
➤ Create a secure deletion pipeline for sensitive user data
• Ensure backups, replicas, and caches are included.
• Track deletion failures across clusters.
• Prove deletion for compliance teams.
➤ Design end to end encrypted messaging for a large platform
• Think about key exchange, forward secrecy, and sealed sender.
• Handle multi device message syncing.
• Protect metadata where possible.
➤ Build a solution to track data lineage across hundreds of services
• Understand how data flows and where copies exist.
• Tag sensitive fields through pipelines.
• Build dashboards for compliance and investigations.
➤ Design a security boundary for machine learning training data
• Separate raw data from processed features.
• Limit access for labeling and training pipelines.
• Prevent leakage of sensitive information in model outputs.
5) Monitoring, Detection, and Incident Response
➤ Build a real time threat detection system using logs from thousands of services
• Normalise logs across many formats.
• Build a pipeline that scales under load.
• Detect malicious patterns fast without overwhelming analysts.
➤ Create an automated anomaly detection pipeline for user behavior
• Track baseline patterns for accounts and devices.
• Flag sudden changes in geography, device type, or velocity.
• Reduce false positives through context.
➤ Design a system to detect compromised employee accounts
• Monitor impossible travel, abnormal access, and session hijacks.
• Track admin actions closely.
• Combine network, device, and identity signals.
➤ Build a SOC alert prioritisation model
• Score alerts based on severity, likelihood, and business impact.
• Reduce noise so analysts focus on real incidents.
• Use feedback loops to improve detection.
➤ Create an incident response workflow with automated playbooks
• Auto isolate compromised machines.
• Send targeted notifications to relevant teams.
• Gather evidence automatically for forensics.
➤ Design a system that identifies abused cloud resources
• Detect crypto mining, unusual network bursts, and unauthorised APIs.
• Build guardrails that auto block suspicious behavior.
• Track resource changes through logs and IAM events.
6) Infrastructure and Cloud Security
➤ Design a secure CI CD pipeline that blocks risky deployments
• Enforce code scanning, dependency checks, and signature verification.
• Block misconfigurations before they reach production.
• Build visibility into each deployment.
➤ Build policy enforcement for thousands of Kubernetes clusters
• Use admission controllers for security policies.
• Enforce least privilege for pods and services.
• Detect drift in cluster configurations.
➤ Design image integrity checks for container builds
• Use signing and verification to prevent tampered images.
• Track the full build provenance.
• Reject unverified images at runtime.
➤ Create automated guardrails that prevent misconfigured S3 buckets
• Detect public access, risky ACLs, and missing encryption.
• Auto fix or block dangerous changes.
• Notify owners with clear guidance.
➤ Build a central vulnerability management system with prioritisation
• Track CVEs across containers, hosts, and packages.
• Prioritise based on exploitability and business impact.
• Provide engineers with clear remediation paths.
➤ Design a secure boot flow for Linux VMs at scale
• Use measured boot, TPM backed verification, and signed kernels.
• Prevent tampering during startup.
• Provide attestation for sensitive workloads.
7) Product and Consumer Security
➤ Build an anti fraud system for payments
• Detect unusual transactions, device fingerprints, and velocity spikes.
• Score risk based on user behavior and history.
• Limit false declines to keep customer trust.
➤ Design phishing resistant user onboarding
• Use biometrics, document checks, and device signals.
• Detect throwaway emails and risky phone numbers.
• Keep the flow smooth for genuine users.
➤ Create a real time abuse prevention system for comments or messages
• Detect spam waves, toxic content, and automation patterns.
• Rate limit abusive behavior in milliseconds.
• Penalise repeat offenders without harming normal users.
➤ Build a system that stops fake account creation
• Track device clusters, IP repetition, and behavioral anomalies.
• Detect signups from automated scripts.
• Protect growth metrics from manipulation.
➤ Detect automation or bot driven attacks against signup flows
• Use behavioral analysis instead of CAPTCHA reliance.
• Block sophisticated headless browser patterns.
• Track signals across sessions and devices.
➤ Design security review tooling for new product launches
• Give engineers a simple checklist for risky components.
• Auto detect missing encryption or unsafe defaults.
• Catch issues early in the design phase.
Closing Thoughts
If you are preparing for interviews, pick one problem each week and go deep.
Draw diagrams. Write a small prototype.
Read how big companies solved the same challenge.
Security is not about tools.
Security is about understanding how systems fail.
If you found this post helpful, share it with someone trying to break into security in 2025. It helps the newsletter grow more than you think.
See you at the next one.
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Love you guys ❤️
i came across another post from linked in. But i really like the list(could not go through it all), specially the 2 and 3 are my first lack few lack of knowledge in at my job. Definitely got a new follower today :)
I was previously a Security Engineer Intern and I appreciate you sharing your lessons that you’ve learned in your career.