How FlowAgents read multi-vendor Common Vulnerabilities & Exposures notices, reason about which products and versions are affected, and pinpoint exactly which devices are exposed.
Every time a vendor finds a problem with a device, they publish a Common Vulnerabilities & Exposures notice. What follows is a manual scramble for security and network teams: read the notice, interpret what it actually means, cross-reference it against inventory, and work out how many devices are genuinely affected. It’s judgment-heavy work that’s nearly impossible to script reliably, because the inputs are unstructured, they vary by vendor, and mapping a vulnerability to real-world exposure doesn’t reduce neatly to code. This is exactly where agentic reasoning earns its place.
In this technical webinar, we’ll demonstrate live how agents can take a vulnerability from notice to known exposure, governed by default. Powered by FlowAI, the agentic harness of the Itential Platform, FlowAgents reason through each CVE using live infrastructure context and a scoped set of tools: they ingest and parse multi-vendor notices from the National Vulnerability Database, interpret which products, versions, and configurations are affected, then cross-reference that against real device inventory to produce a precise, prioritized list of exposed devices for remediation.
If CVE response in your environment still means a spreadsheet, a long thread, and a lot of guesswork, this session shows a better way. You’ll see how agents turn an unstructured vulnerability notice into a precise, governed answer to the question that actually matters: which of my devices are exposed, and what do I do about it. You’ll leave with a working pattern you can apply to the next CVE, the kind of problem scripts were never built to solve. AI adds the reasoning. Itential adds the guardrails.
Manual CVE triage is slow, error-prone, and never finished. Every advisory means hours of reading, interpreting, and cross-referencing inventory by hand, and the answer is only as good as the analyst’s memory of what’s deployed where. The cost isn’t just time. It’s the exposure window that stays open while you figure it out, and the devices that get missed when you’re working from spreadsheets. Agents collapse that work from hours to minutes, check every device instead of a sample, and shorten the gap between disclosure and a confident answer to the only question that matters: am I exposed, and where?