Adopt a Prevention-First Cybersecurity Approach to AWS S3 Storage

AWS S3’s scalable storage is crucial for core business processes but contains unanticipated vulnerabilities. Explore the following reference architecture guide to learn how the Deep Instinct integration works and how our prevention-first, deep-learning solution can be implemented using our scalable, lightweight framework.


Unseen security gaps in your storage perimeter

While AWS protects your cloud environment, it doesn’t protect your files. Bad actors target AWS S3 buckets through file uploads and cross-application file exchange. Custom applications and cloud file storage hosted on AWS S3 don’t come with the native ability to scan files prior to upload. While third-party security applications can be utilized via AWS Lambda or similar functions, they cannot operate at scale and can incur high compute costs. Securing heavily utilized S3 storage quickly becomes costly, and user experience suffers. 


Predictive Prevention Using Deep Learning

The Deep Instinct Prevention Platform – powered by deep learning – provides a fast, efficient, and effective mechanism to scan files uploaded to AWS S3. When a user uploads a file to S3, or when an existing file is modified, Deep Instinct scans the file using functionality built into the AWS platform. If the user attempts to upload a file containing malware, the file will be quarantined, and an alert will notify the user.


AWS S3 and Deep Instinct integration

Deep Instinct Prevention for Storage (DPS) delivers enterprise scalability at a low cost and lightning-fast scanning. DPS prevents malicious files from reaching your S3 buckets, ensuring file integrity and securing access to vital assets.


Interested in learning more about preventing threats from ever reaching your AWS S3 environment?

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