Implementing Vulnerability SLA Breach Alerting

Overview

Vulnerability remediation SLAs define maximum timeframes for addressing security findings based on severity. This skill covers building an automated alerting system that tracks remediation timelines, detects SLA breaches, sends escalation notifications, and generates compliance reports. Industry-standard SLA targets are: Critical (24-48 hours), High (15-30 days), Medium (60 days), Low (90 days).

When to Use

• When deploying or configuring implementing vulnerability sla breach alerting capabilities in your environment
• When establishing security controls aligned to compliance requirements
• When building or improving security architecture for this domain
• When conducting security assessments that require this implementation

Prerequisites

• Python 3.9+ with requests, pandas, jinja2, smtplib libraries
• Vulnerability management platform with API access (DefectDojo, Qualys, Tenable)
• SMTP server or webhook endpoint (Slack, Microsoft Teams, PagerDuty)
• Database for SLA tracking (PostgreSQL or SQLite)

SLA Policy Definition

Standard SLA Tiers

SLA Configuration File

# sla_policy.yaml
sla_tiers:
  critical:
    cvss_min: 9.0
    cvss_max: 10.0
    remediation_days: 2
    grace_period_days: 0.5
    escalation_contacts:
      - ciso@company.com
      - vp-engineering@company.com
    pagerduty_severity: critical
  high:
    cvss_min: 7.0
    cvss_max: 8.9
    remediation_days: 15
    grace_period_days: 5
    escalation_contacts:
      - security-director@company.com
    pagerduty_severity: high
  medium:
    cvss_min: 4.0
    cvss_max: 6.9
    remediation_days: 60
    grace_period_days: 14
    escalation_contacts:
      - team-lead@company.com
    pagerduty_severity: warning
  low:
    cvss_min: 0.1
    cvss_max: 3.9
    remediation_days: 90
    grace_period_days: 30
    escalation_contacts:
      - asset-owner@company.com
    pagerduty_severity: info

notification_channels:
  slack:
    webhook_url: "${SLACK_WEBHOOK_URL}"
    channel: "#vulnerability-alerts"
  email:
    smtp_host: smtp.company.com
    smtp_port: 587
    from_address: vuln-alerts@company.com
  pagerduty:
    api_key: "${PAGERDUTY_API_KEY}"
    service_id: "${PAGERDUTY_SERVICE_ID}"

alert_schedules:
  approaching_breach:
    percentage_elapsed: 80
    frequency_hours: 24
  at_breach:
    notification: immediate
    escalation: true
  post_breach:
    frequency_hours: 12
    escalation_increase: true

Workflow

Step 1: Database Schema for SLA Tracking

CREATE TABLE vulnerability_sla (
    id SERIAL PRIMARY KEY,
    cve_id VARCHAR(20) NOT NULL,
    finding_id VARCHAR(100) NOT NULL,
    asset_hostname VARCHAR(255),
    severity VARCHAR(20) NOT NULL,
    cvss_score DECIMAL(3,1),
    discovered_at TIMESTAMP NOT NULL,
    sla_deadline TIMESTAMP NOT NULL,
    remediated_at TIMESTAMP,
    status VARCHAR(20) DEFAULT 'open',
    owner_email VARCHAR(255),
    escalation_level INTEGER DEFAULT 0,
    last_alert_sent TIMESTAMP,
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);

CREATE INDEX idx_sla_status ON vulnerability_sla(status);
CREATE INDEX idx_sla_deadline ON vulnerability_sla(sla_deadline);
CREATE INDEX idx_sla_severity ON vulnerability_sla(severity);

Step 2: SLA Breach Detection Logic

from datetime import datetime, timedelta, timezone
import yaml

def load_sla_policy(policy_path="sla_policy.yaml"):
    with open(policy_path, "r") as f:
        return yaml.safe_load(f)

def get_sla_tier(cvss_score, policy):
    for tier_name, tier in policy["sla_tiers"].items():
        if tier["cvss_min"] <= cvss_score <= tier["cvss_max"]:
            return tier_name, tier
    return "low", policy["sla_tiers"]["low"]

def calculate_sla_deadline(discovered_at, cvss_score, policy):
    tier_name, tier = get_sla_tier(cvss_score, policy)
    deadline = discovered_at + timedelta(days=tier["remediation_days"])
    return deadline, tier_name

def check_sla_status(discovered_at, sla_deadline, remediated_at=None):
    now = datetime.now(timezone.utc)

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