Inspect-Data

You have a GDPR compliance program. You also have data in AWS you haven't fully inventoried. Both are true. The EU Commission just proved you can have both at the same time. ShinyHunters got into their cloud environment last week. Hundreds of gigabytes taken. The Commission confirmed the breach — then said the investigation is ongoing and they're still determining what was exposed. They don't fully know what was in there. Neither do you. Not because you're negligent. Because GDPR tells you what to do with data you've already catalogued. It was never designed to find the data you forgot about — the buckets spun up under a deadline, the migration that moved faster than the inventory, the contractor environment nobody decommissioned. The compliance program covers the data you know about. The breach exposes the rest. If someone got into your cloud environment tomorrow, how long before you could tell your board exactly what was taken? #DataSecurity #GDPR #CloudSecurity

"Robots vs. Robots" is the keynote title at RSA this morning. It's a great line. It's also missing the real question. If AI attackers are fighting AI defenders, what happens to the data caught in the middle? Because here's what nobody on that stage is asking: Before your AI defender can protect your sensitive data — it needs to know where that data lives. What kind it is. Whose it belongs to. Most organizations don't have that answer. They have a compliance scan from last quarter and an assumption that production is probably fine. The robots are fighting. The data inventory hasn't been done. That's not a robots problem. That's a homework problem. Security leaders at RSA this week — when your AI security tool says it's protecting your sensitive data, what's it actually scanning against? A complete inventory or a best guess?

You blocked ChatGPT on the corporate network. Good call. Your employees are now pasting the same data into the AI tool you licensed for them. The block felt like a win. Shadow IT, contained. But the instinct that made employees reach for ChatGPT didn't go away. You just redirected it — into a tool with a company logo on it and an IT ticket that says "approved." Here's the behavior nobody modeled for: When a tool is sanctioned, people stop self-censoring. The internal friction that made someone pause before pasting a customer list into ChatGPT? Gone. Because this one's approved. This one's safe. So now they paste freely. The contract terms. The patient intake form. The HR complaint they're trying to wordsmith. The internal incident report they need summarized before a meeting. All of it going into a system you vetted for vendor security. Not for what your employees would actually do with it once you handed it to them. Your data handling policy probably says "don't share confidential information with unauthorized tools." It almost certainly doesn't say anything about the one you bought. Security engineers — when your org rolled out its enterprise AI tool, did anyone define what data types were off-limits to paste into it? Or did the approval process stop at the vendor review?

Stop playing “Risk Roulette” with your data discovery budget. 🛑 I keep talking to CISOs who are forced to cherry-pick what they scan. When you’re charged per-GB—or locked into a massive platform fee—you end up leaving the most dangerous corners of your environment in the dark just to stay under budget. To keep costs down, most teams quietly ignore: • The “junk drawer” — massive, unorganized folders on legacy SMB shares • Developer shadow data — abandoned S3 buckets and unencrypted backups • M&A environments — acquired data that sits untouched for years because a full audit is “too expensive” This is where the PII and PHI actually hide. If you’re not scanning it because of a data toll, you’re not secure — you’re just lucky. Then there’s the complexity. If a tool requires agents everywhere, special service accounts, and a 6-week “onboarding” phase, you’re not reducing risk — you’re adding to your backlog. We decided to do this differently. We just released Inspect-Data Risk Finder on Docker Hub. We stripped out variable pricing and setup friction entirely. The basics: • Fixed cost — one flat fee. Scan as much data as you want, as often as you want • Docker-native — pull the image, run the command, get the report. No agents. No setup • Zero egress — your data stays in your VPC or on-prem. We don’t ingest a single byte • Real visibility — 150+ classifiers (PII, PHI, PCI), native OCR for scanned images/PDFs, and support for 1,000+ file types We built this for teams that want 100% visibility without unpredictable invoices. 👉 Docker Hub link in the first comment  

Stop settling for security tooling that takes weeks to deploy and months to configure. We’ve removed the complexity barrier with our new Docker-based Risk Scanner. Get from download to full data risk assessment in minutes—with a single command. No sales calls, no complex infrastructure, just immediate, auditable results. Start here - https://lnkd.in/gU9kevME