The size and reliability constraints were the easy part to talk through.
Start by clarifying requirements and constraints, then outline a high-level architecture that separates upload handling from storage and processing. Focus on the chunked, resumable upload protocol, including chunk-level tracking and integrity verification, and discuss trade-offs around consistency, scalability, and cost.
Pro tip: Emphasize idempotency and exactly-once semantics for chunk uploads to handle retries gracefully, and mention how you'd monitor and alert on upload failures and latency to ensure reliability.
Ask about file sizes, network conditions, client types, security needs, and expected scale to scope the design appropriately.
Propose a service-oriented design with an upload API, chunk storage, metadata database, and asynchronous processing pipeline.
Detail the upload protocol: chunk size, unique upload ID, chunk tracking, retry logic, and integrity checks (e.g., checksums).
Discuss storage options (object store vs. block store), metadata consistency, and how to handle concurrent chunk uploads.
Analyze trade-offs (e.g., latency vs. durability, cost vs. performance) and explain how the design scales horizontally.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Quarantine bucket to evidence bucket, pretty standard pattern.
Start by clarifying the requirements: what types of footage, security checks, and latency expectations exist. Then propose a two-zone storage architecture (quarantine and trusted) with a promotion pipeline that validates and moves data after checks pass. Emphasize trade-offs around consistency, cost, and access control.
Pro tip: Mention that the quarantine zone should be immutable and write-only for uploaders, with strict network isolation, to prevent tampering or data exfiltration before checks complete. Also highlight the importance of idempotent promotion to handle retries safely.
Ask about data volume, upload frequency, security check types (e.g., malware scan, content moderation), latency SLAs, and compliance needs. This shapes the storage and pipeline design.
Propose a separate storage bucket/container with restricted access, encryption, and lifecycle policies. Uploads go here first, and no downstream systems can read directly.
Outline an event-driven pipeline: on upload, trigger security checks; upon success, copy/move to trusted zone and update metadata; on failure, quarantine further or delete. Use idempotent operations and dead-letter queues.
Specify storage with appropriate durability, access controls, and indexing for fast retrieval. Ensure it's optimized for read-heavy workloads and integrates with existing systems.
Discuss consistency (eventual vs strong), cost implications (duplicate storage during promotion), monitoring, and failure recovery. Mention how to handle large files and partial failures.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
SHA-256 the whole file on the client before upload, re-derive it server-side after assembly, store it in an append-only record.
Start by clarifying the threat model and the full lifecycle of the footage (capture, upload, storage, access, and sharing). Then propose a layered integrity approach using cryptographic hashing, digital signatures, and a tamper-evident audit trail, explaining how each layer addresses specific risks and trade-offs.
Pro tip: Emphasize that integrity verification must be end-to-end and include the chain of custody; mention that you would use hardware-backed keys or HSMs for signing to prevent key compromise, and that you would design for verifiability by third parties (e.g., courts) without exposing sensitive data.
Ask about the sensitivity of the footage, who needs to verify integrity, and what threats are in scope (e.g., tampering during upload, storage, or access). This ensures the solution is proportionate and addresses real risks.
Break down the lifecycle: capture (device), upload (network), storage (at rest), access (retrieval), and sharing (distribution). For each stage, identify how integrity could be compromised and what verification is needed.
Use SHA-256 hashing to create a unique fingerprint of the footage at capture. Digitally sign the hash with a device-specific private key to prove origin and integrity. Store the signature and hash in a tamper-evident ledger or database.
Implement a verification service that recomputes the hash and validates the signature at each stage. Maintain an immutable audit log of all actions (upload, access, modifications) with timestamps and user IDs to provide chain of custody.
Discuss trade-offs: performance overhead of hashing large files, key management complexity, and storage costs. Propose optimizations like chunked hashing, Merkle trees, or using a blockchain for decentralized trust if needed.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
This was the part I found most interesting.
Start by clarifying the requirements: what actions need to be logged, who can access the log, and what compliance standards (e.g., CJIS, GDPR) apply. Then propose an append-only, cryptographically chained log (like a blockchain) with immutable storage and strong access controls. Finally, discuss trade-offs around performance, scalability, and legal considerations like chain of custody and deletion policies.
Pro tip: Emphasize that the log itself must be tamper-evident and auditable, so consider using cryptographic hashing and digital signatures for each entry, and store the log in a write-once-read-many (WORM) storage. Also, mention the importance of separating the log from the footage to prevent a single point of compromise.
Ask questions to understand the scope: what actions to log (upload, access, legal hold, deletion), who needs access, retention policies, and regulatory requirements. Identify non-functional needs like scalability, latency, and durability.
Define the schema for log entries: timestamp, actor, action, target footage ID, metadata, and cryptographic hash of previous entry. Ensure entries are immutable and include enough context for auditing.
Select an append-only storage solution (e.g., WORM storage, blockchain, or a database with audit tables). Implement cryptographic chaining (hashing) and digital signatures to detect tampering. Consider replication and backup for durability.
Specify who can read the log and who can append entries. Use role-based access control (RBAC) and ensure all access to the log is itself logged. Provide an audit interface for authorized users to verify integrity.
Discuss trade-offs: performance vs. security, cost of immutable storage, handling legal holds (preventing deletion), and deletion policies (e.g., crypto-shredding). Consider how to handle log growth and archival.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Talked through role-based access, separating who can upload from who can view or export, and flagging any access event to the custody log.
Start by recommending a role-based access control (RBAC) model with attribute-based access control (ABAC) extensions to handle dynamic, context-aware policies. Then discuss security considerations specific to legal evidence, such as chain of custody, tamper-proof storage, and audit trails. Emphasize how these measures ensure integrity and admissibility in court.
Pro tip: Demonstrate awareness of legal standards like the Federal Rules of Evidence (e.g., Rule 901(b)(9) for electronic records) and mention the importance of cryptographic hashing and digital signatures to prove authenticity. This shows you understand the intersection of technology and law, which is critical for Axon.
Propose RBAC for basic role separation (e.g., officers, admins, legal) and ABAC for fine-grained, context-aware policies (e.g., time, location, case sensitivity).
Outline key roles (e.g., officer, supervisor, evidence custodian, external auditor) and their permissions, ensuring least privilege and separation of duties.
Explain how the model enforces chain of custody, immutability, and audit logging to meet legal standards for evidence integrity.
Describe technical controls like encryption at rest and in transit, cryptographic hashing, digital signatures, and tamper-evident logs.
Discuss how the system supports audits, compliance with regulations (e.g., CJIS, GDPR), and provides verifiable audit trails for court.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.