building-vulnerability-aging-and-sla-tracking

Implement vulnerability aging dashboards and SLA tracking to measure remediation performance against severity-based deadlines.

954|172|Updated Mar 13, 2026
One-click install
npx skills add https://github.com/xalgord/xalgorix --skill building-vulnerability-aging-and-sla-tracking
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: building-vulnerability-aging-and-sla-tracking
Source: https://github.com/xalgord/xalgorix/tree/main/internal/tools/skills/data/vulnerability-management/building-vulnerability-aging-and-sla-tracking
Command: npx skills add https://github.com/xalgord/xalgorix --skill building-vulnerability-aging-and-sla-tracking

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas.

What problem does it solve?

Security teams often lack visibility into how long vulnerabilities remain unpatched and whether remediation meets severity-based deadlines, making it impossible to enforce accountability or report compliance to leadership.

Core Features & Use Cases

  • SLA Policy Framework: Define severity-based remediation timelines (14 days critical, 30 high, 60 medium, 90 low) with adaptive modifiers for KEV-listed CVEs, EPSS scores, and internet-facing assets.
  • Aging Calculation Engine: Python/pandas-based tracker that computes age, SLA deadlines, overdue status, MTTR, and compliance rates from vulnerability scan data.
  • Automated Escalations: Tiered escalation triggers at 50/75/100/120% of SLA elapsed, routing notifications from asset owners up to VP/CTO level.
  • Use Case: A security team feeds scan results into the aging tracker, generates overdue-by-severity KPIs, and publishes a monthly SLA compliance dashboard in Grafana or Elasticsearch for the security committee.

Quick Start

Ask the AI to build a vulnerability aging dashboard that calculates SLA compliance and overdue counts from your vulnerability scan data using the provided pandas-based tracker.

Frequently Asked Questions about building-vulnerability-aging-and-sla-tracking

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I track vulnerability SLA compliance?

Track SLA compliance by calculating each vulnerability's age from discovery date, comparing it against severity-based deadlines (14 days critical, 30 high, 60 medium, 90 low), and computing the percentage remediated within SLA. The provided pandas-based tracker automates this calculation.

What are standard vulnerability remediation SLA timelines?

Standard SLAs are 14 days for critical (CVSS 9.0-10.0), 30 days for high, 60 days for medium, and 90 days for low severity. Aggressive programs use 48 hours for critical, and CISA KEV-listed vulnerabilities should follow BOD 22-01 due dates.

How do I calculate MTTR for vulnerabilities?

Calculate MTTR as the average of remediation_date minus discovery_date across closed vulnerabilities. Include open overdue items in dashboards separately, since computing MTTR only on closed findings hides the aging backlog.

Should SLA deadlines adapt to asset context?

Yes, static SLAs miss risk context. Apply modifiers such as -50% for internet-facing assets, 48-hour override for CISA KEV-listed CVEs, -50% for EPSS above 0.7, and -25% for tier-1 crown jewel assets.

Why is my SLA compliance rate misleadingly high?

Compliance is often inflated because the SLA clock starts at report date instead of discovery date, or because overdue open items are excluded from metrics. Verify the timer uses discovery_date and that open overdue vulnerabilities appear in dashboards.

How do I handle vulnerabilities that cannot be patched in time?

Use a documented exception workflow requiring business justification, a compensating control description, and an expiry date, with CISO approval for critical and high exceptions. Avoid blanket waivers and cap extensions at 90 days with one renewal.