Securing File Uploads in AWS Workflows

You're in a senior backend interview. The interviewer asks: "Your API endpoint handles file uploads. Users upload 2GB video files. The request times out after 60 seconds but the upload takes 8 minutes. How do you fix this without increasing the timeout?" If your first instinct is to increase the timeout to 10 minutes, you've just committed to holding an HTTP connection open for 10 minutes per upload. At 100 concurrent uploads, that's 100 open connections doing nothing but waiting. I have designed file upload systems that handle gigabytes without timeouts while working as a backend engineer in the past. The obvious answer is async processing. But most teams implement it wrong. They accept the file upload in the API, save it to disk, return a response. The upload still happens synchronously. The 2GB file still transits through your application server. Your server's memory spikes. The connection still times out. The correct answer is the upload should never touch your application server. Generate a presigned S3 URL. Return it to the client immediately. The client uploads directly to S3. Your server never sees the 2GB file. No memory pressure. No timeout. No bandwidth consumed. When upload completes, S3 triggers an event notification to SQS. A background worker picks up the message and processes the file. All asynchronous. But presigned URLs introduce a problem most engineers don't anticipate. The client can upload anything. A 10GB file when you expected 2GB. A malicious executable disguised as a video. Presigned URLs bypass your application's validation entirely. The fix is validation in two stages. Before generating the presigned URL, validate the request. Check file size from Content-Length header. Check file type from extension or MIME type. Enforce limits. Generate the presigned URL only if validation passes. After upload completes, validate the actual file on S3. Check real file size. Scan file signature to confirm type matches what was declared. If validation fails, delete and notify user. Then there's progress tracking. The client uploads to S3, not your API. Your API doesn't know upload progress. The user sees a spinner with no indication how long it will take. Use S3 multipart upload with progress callbacks. Client breaks file into chunks, uploads each chunk, reports progress to your API via lightweight requests. Your API tracks progress in Redis. Frontend polls for updates. User sees "45% uploaded." The architecture in summary: Presigned URLs for direct S3 upload. Pre-validation before URL generation. Post-validation after upload. Multipart upload with progress tracking. SQS event notification for async processing. No timeouts. No memory spikes. No file transiting through your application. How do you handle large file uploads? #backend #systemdesign #aws #s3 #apidesign #softwarearchitecture

A candidate interviewing for L5 @ Google was asked to break down the design of Google Drive. Another candidate who was interviewing for the role of SDE-III @ Amazon, was asked another with a file upload system question. I’ve faced these too. System design rounds love “simple” file upload questions until you add one layer of complexity: – Add virus scanning? Whole new security headache. –  Add multi-region storage? Now you’re fighting replication and consistency. –  Add instant previews or image compression? Welcome to async pipelines and job queues. Here’s my personal checklist of 15 things you must get right when building file upload systems: 1. Never upload directly to your backend → Use presigned URLs so files go straight to S3, GCS, or your object storage, offloading bandwidth and freeing up backend resources. 2. Validate file type by content, not extension → Don't trust “.jpg” or “.pdf”, read the file’s magic bytes or headers to catch disguised executables or corrupted files. 3. Set strict file size limits (early) → Prevent memory blowups, denial of service, and accidental 50GB “cat video” uploads. 4. Multipart/chunked uploads for large files → Upload big files in chunks, so you can retry failed pieces, resume partial uploads, and never lose user progress. 5. Resumable uploads matter → User’s WiFi dies? Don’t make them start from scratch. Store upload progress, support resume tokens. 6. Async virus scanning before “marking ready” → Queue the scan; don’t let user-access or public-sharing happen until the result is clean. 7. Never trust user-supplied metadata → Recompute MIME types, image dimensions, video duration, etc., server-side, attackers will fake everything. 8. Expire unused presigned URLs fast → Every upload/download link should expire in minutes, not days. Stops replay attacks and stale-link leaks. 9. Background post-processing → Thumbnails, transcoding, compression, indexing, all should be async jobs, not blocking the upload. 10. Signed download URLs only  → Never expose raw S3 or GCS paths. Every download link should be time-bound and permission-checked. 11. Enforce per-user and per-IP rate limits → Throttle abusive clients, prevent brute force, and stop sudden spikes from melting your backend. 12. Encrypt files at rest (and in transit)  → Use server-side encryption (SSE) on S3 or GCS, plus HTTPS/TLS for every file transfer. 13. Version every upload → Store new files with unique IDs or version suffixes, never overwrite by default. Enables “undo” and rollback, and prevents race conditions. Continued ↓ – P.S: Say Hi on Twitter: https://lnkd.in/g9H82Q98 — P.P.S: Feel free to reach out to me if you're preparing for a switch, want to chat about interview preparation, or how to move to the next level in your career: https://lnkd.in/guttEuU7

File uploads sound easy - until you actually build them. Here are 10 things you must get right 👇 1 Never upload directly to your backend - use presigned URLs so files go straight to S3/GCS. 2 Validate file type by content, not just extension - .exe can easily be renamed to .jpg. 3. Set file size limits early - avoid memory blowups and bandwidth abuse. 4. Use multipart/chunked uploads for large files - retry failed chunks, not the whole file. 5. Add resumable uploads - let users pick up after a failed connection. 6. Always virus-scan uploads asynchronously before marking them “ready.” 7. Don’t trust user metadata - extract real MIME/type/dimensions server-side. 8. Expire unused presigned URLs - prevents old links from being reused maliciously. 9. Post-process asynchronously - thumbnails, compression, and indexing should happen in background jobs. 10. Secure access with signed download URLs - never expose raw S3 paths publicly.

🚀 𝗶𝗢𝗦 𝗦𝘆𝘀𝘁𝗲𝗺 𝗗𝗲𝘀𝗶𝗴𝗻 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄: 𝗗𝗲𝘀𝗶𝗴𝗻 𝗮 𝗙𝗶𝗹𝗲 𝗨𝗽𝗹𝗼𝗮𝗱 𝗦𝘆𝘀𝘁𝗲𝗺 One of the most common Senior iOS interview questions is: > "𝙃𝙤𝙬 𝙬𝙤𝙪𝙡𝙙 𝙮𝙤𝙪 𝙙𝙚𝙨𝙞𝙜𝙣 𝙖 𝙨𝙘𝙖𝙡𝙖𝙗𝙡𝙚 𝙖𝙣𝙙 𝙨𝙚𝙘𝙪𝙧𝙚 𝙛𝙞𝙡𝙚 𝙪𝙥𝙡𝙤𝙖𝙙 𝙨𝙮𝙨𝙩𝙚𝙢 𝙪𝙨𝙞𝙣𝙜 𝘼𝙢𝙖𝙯𝙤𝙣 𝙎3 (𝙤𝙧 𝙖𝙣𝙮 𝙘𝙡𝙤𝙪𝙙 𝙨𝙩𝙤𝙧𝙖𝙜𝙚)?" Most candidates immediately talk about URLSession. But interviewers want to evaluate your system design thinking, not just your coding skills. 𝐇𝐞𝐫𝐞'𝐬 𝐚 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧-𝐫𝐞𝐚𝐝𝐲 𝐚𝐩𝐩𝐫𝐨𝐚𝐜𝐡 👇 ✅ 1. Upload directly to S3 Request a Pre-Signed URL from your backend. Upload directly using URLSession. Notify the backend after a successful upload. ✅ 2. Validate the file Don't trust the file extension. Validate the MIME type, file signature (magic bytes), and file size. ✅ 3. Use multipart uploads Large files should be split into chunks, uploaded in parallel, and only failed chunks should be retried. ✅ 4. Support resumable uploads Network interruptions happen. Use Background URLSession so uploads can continue or resume later. ✅ 5. Don't expose files immediately A typical production flow is: Upload → Virus Scan → Validation → Metadata Processing → Available to Users ✅ 6. Use Signed Download URLs Keep your storage bucket private and generate temporary download URLs for authorized users. ✅ 7. Process everything asynchronously Thumbnail generation, OCR, AI processing, and compression should happen in the background—not during the upload. ✅ 8. Protect your system Enforce file size limits, upload rate limits, allowed file types, and user quotas. --- 💡 Interview Tip: Don't just explain how to upload a file. Explain why each architectural decision improves scalability, security, reliability, and user experience. That's what interviewers expect from Senior iOS Engineers and Technical Leads. How would you design this system differently? I'd love to hear your approach. #iOS #Swift #SwiftUI #SystemDesign #AWS #AmazonS3 #xcodw #SoftwareArchitecture #InterviewPreparation #AppleDeveloper #MobileDevelopment #iosdeveloper #iosdev #iosjobs

🚀 Uploading to S3 with Presigned URLs vs. Consuming Backend Resources for Binary Upload 🌐 In the realm of cloud storage and data handling, the choice of how to upload files can significantly impact efficiency and resource utilization. Let’s explore why using presigned URLs for S3 uploads shines over consuming backend resources and piping binary uploads: ⭐️ Reduced Server Load: Presigned URLs offload the upload process to the client side, reducing the burden on backend servers and enhancing scalability. ⚙️ Enhanced Security: Presigned URLs grant temporary access permissions, limiting exposure and bolstering security by minimizing direct interactions with backend systems. 🔗 Seamless Integration: Presigned URLs integrate seamlessly with various client-side technologies, facilitating smoother workflows and user experiences. ⏱️ Faster Uploads: By leveraging direct client uploads to S3, presigned URLs can achieve faster upload times, optimizing data transfer speed and user satisfaction. 💡 Cost Efficiency: Offloading uploads to S3 with presigned URLs can lead to cost savings by reducing the need for additional backend infrastructure and resources. Embracing presigned URLs for S3 uploads empowers businesses with a streamlined, secure, and cost-effective approach to managing data in the cloud. #CloudStorage #DataManagement #PresignedURLs #Efficiency #Security #CostSavings 💻☁️🔒🌟