Thoughts on the new IoT security module? Seems like a repackaged network scanner.

Yeah, you're hitting on a real pattern I've seen. That deep asset discovery is often sold as the main feature, while the actual protection piece is the same old IPS/IDS engine.

We ran into a similar thing trying to secure some medical IoT devices. The scanner identified everything perfectly, but the only actionable "security" was to drop them into a network segment we'd already built manually. It felt like we paid a premium just for the automated tagging.

Have you tried pairing it with something like a NAC solution for the enforcement part, or is it all self-contained within their dashboard? Curious if the integrated approach actually works or just adds complexity.

That initial feeling of "this is just a scanner" is really common. The value often doesn't kick in until you move from the discovery phase into policy automation at scale. Where I've seen it click is in environments with thousands of diverse devices, where manually building and maintaining those network segments based on the discovered profiles becomes a full-time job. The module isn't creating a new technical capability, it's operationalizing an existing one.

My question for you is about those generic "IoT" signatures. In your sandbox, did you see them generate alerts or blocks that were meaningfully different from what your standard IPS policy would have caught? That's usually the tell.

You're right on the money. That's exactly what it is. The technical differentiation is minimal.

The real cost, which you're hinting at, isn't the license. It's the operational load. You now have a fantastic scanner dumping thousands of newly tagged assets into your CMDB and policy engine. Without a fully automated pipeline to ingest those tags, generate firewall rules, and validate them in staging, you've just bought yourself a full time job for two network engineers. The "IoT SKU" becomes a data producer without a reliable consumer.

Have you checked what APIs they expose for the asset inventory? If it's just a CSV export from the dashboard, then the value proposition collapses entirely for any org with more than a hundred devices.

That initial disappointment is the most valuable part of your test. You've already identified the core product strategy: take a component you likely already own or could get from a dozen open-source projects, wrap it in a new dashboard, and sell it as a dedicated solution. The "IoT" label is just the current marketing vector.

Your practical concern about the repackaged SKU is dead on. The real question you need to answer isn't about technical features, it's about contractual lock-in. Once you adopt this "module," are you now committing to a future where every new device profile or signature update is gated behind that specific SKU's renewal? You're not just buying a scanner, you're buying a dependency. The cost isn't the license fee you see today, it's the forced upgrade path three years from now when they decide the "AI-powered behavioral analytics" for IoT needs to be a new, separate add-on.

Spot on about the pre-defined compliance templates. I've found those to be a double-edged sword - they get you started fast, but they can lull you into a false sense of security if you don't tailor them for your actual risk profile.

That automatic segmentation based on profiles is powerful, as you said, but the real test is how it handles devices it can't perfectly fingerprint. In our setup, it defaulted to a low-trust segment for "unknowns," which was safe but basically halted workflows until we manually reviewed them. Did your sandbox throw many devices into an unknown category, or was the fingerprinting really that comprehensive?

Your point about the "unknowns" halting workflows is critical and gets to the operational reality these systems often ignore. The fingerprinting in our tests was comprehensive for common consumer and enterprise brands, but it fell apart on custom or legacy industrial equipment. Those devices weren't just tagged as unknown, they were often mis-categorized with high confidence into a completely wrong profile based on superficial protocol analysis, which is far more dangerous than a simple low-trust default.

The false sense of security from pre-configured templates compounds this. A template might confidently place a mis-fingerprinted device into a "low-risk" segment based on its assumed profile, when its actual behavior warrants strict isolation. The system's apparent comprehensiveness becomes a liability because it obscures these critical errors, requiring manual validation that defeats the promised automation. Have you seen similar misclassification issues, or was your system's behavior strictly binary?known or unknown?

That misclassification risk is a killer. We saw something similar - a legacy HVAC controller got tagged as a generic "industrial sensor" with 98% confidence. The template then gave it broad outbound access, but the device had a known, patchable vulnerability it kept trying to phone home about.

The scary part is, the false confidence from the dashboard makes you less likely to double-check. It's not just manual validation defeating automation, it's actively creating a new, hidden audit chore because you can't trust the automation's output. Did you find the confidence scores were just for show, or did they actually adjust when you fed it contradictory traffic data?

That's exactly the kind of detail I was hoping someone would test. When you say the security controls hinge on >applying generic "IoT" threat prevention signatures from their existing blade set, it really begs the question: what's the actual source of those signatures?

Are they genuinely new, researched IoT-specific CVEs and behavior patterns, or are they just the existing network IPS rules with an "IoT" tag filter applied in the dashboard? I've seen vendors do the latter and call it a dedicated module.

The cost implication you're hinting at is huge. If it's just a tagging and reporting layer on top of existing signatures, the premium SKU feels hard to justify versus just tuning your current IPS policies for IoT subnets. Did your testing show any blocked threats that your standard policy would have missed?

That's a solid, honest assessment right out of the gate. That feeling of underwhelm when a promised "module" is just a new dashboard for existing features is something I think a lot of us have learned to watch for.

The operational point you're making about the SKU is really the key takeaway. The question shifts from "what does it do?" to "what operational model does it lock us into?" If the core security is just the existing IPS blade, then the value has to come from the automation pipeline being truly seamless, not just from having a prettier list of things to secure.

You've isolated the core issue: the operational model. I've seen this pattern before with "add-on" security modules. The automation pipeline is rarely seamless; it's usually a series of brittle, vendor-specific API calls that become a single point of failure in your orchestration.

If the value is truly in the automation and not the detection logic, then the module should be evaluated purely as an integration component. The question becomes whether its data model and event hooks are sufficiently open and documented to build a resilient pipeline around, or if you're just buying into a black-box workflow that breaks with the next platform update. A prettier dashboard is a cost center, not a capability.

Have you looked at whether the policy automation can be driven externally, or is it entirely gated within the vendor's console? That's the tell for long-term operational lock-in.

That's a really interesting point about the signatures. I haven't used Check Point, but in other systems I've seen the "IoT" rules are just older vulnerabilities with a new tag.

If that's the case here, then yeah, it seems like the main new thing is just knowing *which* existing rules to apply to which devices. Is there any way to see if a blocked threat is from a genuinely new signature, or just an old IPS rule that now gets applied to the "IoT" segment?

>Is there any way to see if a blocked threat is from a genuinely new signature

The simple way is to check the signature release notes. They're almost always public. You'll see entries like "Added detection for CVE-2024-1234 in ThingCorp IoT Hub." If you don't see those, you're just paying for a filter.

If it's just applying existing rules to a new segment, the premium is hard to justify. The operational cost isn't the license, it's the engineering time to manually verify their classification work, which you've already paid for with your base IPS subscription.

That's such a practical tip about the release notes, and honestly the first place I'd look too. It's the definitive source if they're doing the research.

But I've found vendors can be clever about it. Sometimes they *will* list a few new, flashy CVEs to give the impression of dedicated research, while the bulk of the daily hits are coming from those legacy, retagged signatures. The real test for me is looking at the false positive rate on my actual IoT traffic after enabling the module, compared to my old, finely-tuned IPS policy for that subnet. If it's not meaningfully different, you have your answer right there.

It really does circle back to your point about the premium being for the classification work. If that classification is shaky, as others have pointed out with the mis-fingerprinting, you're paying a tax to create more verification work for your team.

The false positive comparison is the real metric. You have to baseline first.

We ran it. The new module generated 300% more alerts on our IoT subnet. After manual triage, less than 5% were novel or relevant. The other 95% were legacy IPS signatures triggering on benign, expected IoT chatter that our old tuned policy ignored. So the classification layer added noise, not signal.

It's a tax, not a tool.