An n8n workflow monitors CVEs from sources like CISA and OTX, scores them with AI, and alerts via Slack, Gmail and Google Sheets.
An n8n workflow monitors CVEs from sources like CISA and OTX, scores them with AI, and alerts via Slack, Gmail and Google Sheets.
Bright Data nodes in n8n scrape CISA, NIST, CERT-FR and BleepingComputer. A Cohere Command-R agent with session memory extracts CVE details and scores severity, using CISA KEV, CIRCL and AlienVault OTX enrichment. Output parsing and normalization stop it recalculating scores arbitrarily. Hash-based diff checks remove duplicates. Alerts go to Slack, Gmail and Google Sheets, with retries on source failures.
The author reports 100+ CVEs a day, alerts in under 5 minutes, and 99.8% uptime. The Slack Ack/Investigate/Dismiss buttons are only a demo, because the webhook was blocked, so the system is about 90% production-ready.
Without strict output constraints and parsing, the AI scored inconsistently. The uptime and false-positive figures are the author's own claims, not independently verified.
Build an n8n workflow that checks CVE feeds such as CISA and OTX every [interval], asks an AI model to score each new CVE for relevance to my stack [list of technologies] and severity, and logs them to my Google Sheet [sheet name]. High-scoring items should also alert me in [Slack channel or Gmail]. You're done when a test run logs new CVEs and flags the relevant ones; show me a sample alert before activating sending.
Score every demo request against your ICP, update HubSpot and ping the right rep in Slack within a minute of the form submit.
Every new Zendesk ticket gets a category, priority and sentiment tag plus a draft reply in an internal note before an agent opens it.
Each month, find posts whose search clicks dropped, research what changed with Perplexity, and get a Claude-written refresh brief for each one.