If you haven’t scanned it, do you actually know what’s inside?
Security without Observation
In modern enterprises, cloud storage (Amazon S3, Azure Storage, GCP Buckets) is growing at a blistering pace. As cloud becomes the norm for organizations of all sizes worldwide, the volume of data is exploding.
At the same time, most organizations are operating in a kind of quantum uncertainty. From the outside, their cloud environments look controlled and compliant, but what’s actually inside remains unknown.
Teams assume their data is secure because they’ve put security controls in place that worked in the past. Their security appears consistent and comprehensive; IAM policies are strong, the bucket is labeled private, data is encrypted, and everything is backed up.
Yet none of these controls collapse the uncertainty. None of them tell security teams what is happening inside the cloud storage.
Why This Matters: The Cost of Not Observing
An unscanned cloud bucket exists in two states at once: safe and compromised. Until you look inside, both are true.
Most enterprises today operate under the illusion of security—believing that cloud storage is secure because the perimeter looks fine. But attackers know cloud storage is the new malware distribution layer.
In addition to countless semi-secure data ingestion points and increasingly sophisticated malware capable of bypassing safeguards, cloud storage offers unique places for malware to hide:
- Dormant backups and document archives might house malicious data
- Old ZIP files could be waiting to explode
- AI training datasets may be compromised
- Publicly shared artifacts can be infected
And, in the face of multi-petabyte data lakes, most security tools simply aren’t capable of scanning the volume of data that exists.
Files can be infected for years without anyone knowing. They sit and wait, uploaded and forgotten until someone is unfortunate enough to download them, kickstarting a breach years in the making.
The bottom line is that if you don’t scan it, you don’t know it. And if you don’t know it, you can’t prevent threats or protect against compromise.
The Schrödinger Analogy
A bucket that’s never been scanned is like Schrödinger’s box:
- It might contain 50,000 infected files (or even just one—which is more than enough)
- It might contain sensitive PII in an unencrypted tarball
- It might contain ransomware-planted loaders waiting to be downloaded
For most organizations, you literally cannot know until the moment you download or execute it on the endpoint, which should be your very last line of defense, not your first.
Cloud storage looks healthy on the surface—while silently accumulating risk beneath.
The Malware Superposition
Security teams feel comfortable in their existing security controls, but those controls don’t actually prevent threats or provide insight into incoming data. And even with those existing controls, when they download new updates, they need to rescan entire buckets and repositories, which most legacy tools simply lack the throughput to do.
Just like Schrödinger’s cat, cloud data (and the potential threats therein) exists in a sort of superposition. It is simultaneously compliant and non-compliant, clean and infected, safe and exposed. Inside your storage could be the one dormant piece of malware waiting to execute, the errant radioactive atom that will poison your organization.
And until you observe it, and collapse the superposition, you won’t know it’s there.
That’s where problems happen. Because in most cases, “observation” means allowing the file to execute or trying to dissect it in a sandbox, both of which have significant issues.
The only safe solution is to scan the actual stored files before they execute, without relying on outdated, signature-based tools. You need a way to see if the cat is dead before you open the lid. With DSX, every file is scanned ‘in the box,’ before it’s uploaded.
Collapsing the Superposition Safely
This is where Deep Instinct flips the model.
When legacy tools ‘observe’ a potentially malicious file, they need to either execute it in situ or in a sandbox. When they do so, the file performs the actions it was coded to do. If those actions are malicious, they can potentially bypass security and infect the organization.
To prevent that from happening, security teams need a way to scan or observe a file without executing it. That’s exactly what Deep Instinct does.
Instead of assuming cloud data is safe until proven unsafe, DSX treats every file as guilty until proven clean following modern zero trust architectures—using deep learning–based malware prevention, static analysis at scale (no execution required), real-time scanning of files (and whole S3 buckets), and continuous monitoring and event-driven detection.
DSX observes your cloud data without forcing you to open Schrödinger’s box. Every file is scanned and tagged before it has the chance to execute and put your organization’s data at risk. Deep Instinct differentiates itself through:
- Certainty: >99% efficacy against zero-day threats, <0.1% false positives—no guesswork, no noise, with only one to two updates per year.
- Visibility: <20ms per file means that scanning multi-petabyte repositories is possible without bottlenecks.
- Provable cleanliness: Deep learning detection doesn't need signatures, sandboxes, or prior malware samples to stop threats.
- Compliance: Your data never leaves your environment or control.
Find out what's really in your cloud storage. Request a DSX scan—before someone else opens the box for you.
*No cats were harmed in the making of this blog.
