Tenable Quick Wins Executive Dashboard
ContributedExecutive dashboard that prioritizes remediation to cut Tenable One Exposure Score by 10-50% in phases.
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Powered by Hexa AI, Part of Tenable One
Tenable Quick Wins Executive Dashboard is powered by Tenable Hexa AI
Hexa AI is the agentic engine of Tenable One — the AI-powered exposure management platform. See it in action.
Request a Demo →A Claude Desktop skill that turns live Tenable One exposure data into a board-ready remediation roadmap. Instead of a flat vulnerability list, it ranks remediation actions by a Quick Win Score — high VPR, breadth of affected assets, and low patch effort, with bonus weight for Crown Jewel assets and attack path chokepoints — and groups them into five cumulative phases that walk the Exposure Score down from its current value toward a 50% reduction.
What it does
Generates an interactive executive dashboard for prioritizing vulnerability remediation to reduce the Tenable One Exposure Score across five cumulative phases (10% → 20% → 30% → 40% → 50%). The dashboard includes a score gauge, clickable phase cards, a score-progression chart, an industry peer benchmark, and a board-ready executive summary. Supports both English and Portuguese output.
Use it whenever someone asks for quick wins, a phased risk-reduction plan, a remediation roadmap, where to start on vulnerability remediation, or an executive-level prioritization view of exposure data.
How it works
The skill connects to a Tenable One MCP server and pulls live Exposure View, Findings,
Crown Jewels, and Attack Path data. It computes a Quick Win Score for each candidate
remediation action as (avg_VPR × affected_assets × breadth_factor) / relative_effort, with
additional weight added when a Crown Jewel asset or an attack path chokepoint is involved.
Actions are then bucketed into five cumulative phases so the highest-impact, lowest-effort
fixes appear first, and the result is rendered as an interactive dashboard artifact. If no
MCP connection is available, it falls back to a clearly labeled demo dataset.