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,smtpliblibraries - 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
| Severity | Remediation SLA | Grace Period | Escalation Level |
|---|---|---|---|
| Critical (CVSS 9.0-10.0) | 48 hours | 12 hours | VP Engineering + CISO |
| High (CVSS 7.0-8.9) | 15 days | 5 days | Director of Engineering |
| Medium (CVSS 4.0-6.9) | 60 days | 14 days | Team Lead |
| Low (CVSS 0.1-3.9) | 90 days | 30 days | Asset Owner |
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)
if remediated_at:
if remediated_at <= sla_deadline:
return "remediated_within_sla"
return "remediated_breach"
if now > sla_deadline:
overdue_days = (now - sla_deadline).days
return f"breached_{overdue_days}d_overdue"
remaining = sla_deadline - now
total_sla = sla_deadline - discovered_at
pct_elapsed = ((total_sla - remaining) / total_sla) * 100
if pct_elapsed >= 80:
return "approaching_breach"
return "within_sla"
Step 3: Notification Dispatch
import requests
import json
import smtplib
from email.mime.text import MIMEText
from email.mime.multipart import MIMEMultipart
def send_slack_alert(webhook_url, vuln_data, sla_status):
color = {"breached": "#FF0000", "approaching_breach": "#FFA500", "within_sla": "#36A64F"}
status_color = color.get("breached" if "breached" in sla_status else sla_status, "#808080")
payload = {
"attachments": [{
"color": status_color,
"title": f"Vulnerability SLA Alert: {vuln_data['cve_id']}",
"fields": [
{"title": "Severity", "value": vuln_data["severity"], "short": True},
{"title": "CVSS", "value": str(vuln_data["cvss_score"]), "short": True},
{"title": "Asset", "value": vuln_data["asset_hostname"], "short": True},
{"title": "SLA Status", "value": sla_status, "short": True},
{"title": "Deadline", "value": vuln_data["sla_deadline"].strftime("%Y-%m-%d %H:%M UTC"), "short": True},
{"title": "Owner", "value": vuln_data.get("owner_email", "Unassigned"), "short": True},
],
}]
}
requests.post(webhook_url, json=payload, timeout=10)
def send_pagerduty_alert(api_key, service_id, vuln_data, severity):
payload = {
"routing_key": api_key,
"event_action": "trigger",
"payload": {
"summary": f"SLA Breach: {vuln_data['cve_id']} on {vuln_data['asset_hostname']}",
"severity": severity,
"source": vuln_data["asset_hostname"],
"custom_details": {
"cve_id": vuln_data["cve_id"],
"cvss_score": vuln_data["cvss_score"],
"sla_deadline": vuln_data["sla_deadline"].isoformat(),
}
}
}
requests.post(
"https://events.pagerduty.com/v2/enqueue",
json=payload, timeout=10
)
def send_email_alert(smtp_config, to_addresses, vuln_data, sla_status):
msg = MIMEMultipart("alternative")
msg["Subject"] = f"[SLA {sla_status.upper()}] {vuln_data['cve_id']} - {vuln_data['severity']}"
msg["From"] = smtp_config["from_address"]
msg["To"] = ", ".join(to_addresses)
body = f"""
Vulnerability SLA Alert
CVE: {vuln_data['cve_id']}
Severity: {vuln_data['severity']} (CVSS {vuln_data['cvss_score']})
Asset: {vuln_data['asset_hostname']}
SLA Deadline: {vuln_data['sla_deadline'].strftime('%Y-%m-%d %H:%M UTC')}
Status: {sla_status}
Owner: {vuln_data.get('owner_email', 'Unassigned')}
Please take immediate action to remediate this vulnerability.
"""
msg.attach(MIMEText(body, "plain"))
with smtplib.SMTP(smtp_config["smtp_host"], smtp_config["smtp_port"]) as server:
server.starttls()
server.send_message(msg)
Step 4: Scheduled SLA Check Runner
# Run SLA breach check every hour via cron
echo "0 * * * * cd /opt/vuln-sla && python3 scripts/process.py --check-sla" | crontab -
# Manual check
python3 scripts/process.py --check-sla --policy sla_policy.yaml
# Generate SLA compliance report
python3 scripts/process.py --report --period monthly --output sla_report.html
SLA Metrics Dashboard
Key Performance Indicators
def calculate_sla_metrics(db_connection, period_start, period_end):
metrics = {
"total_findings": 0,
"remediated_within_sla": 0,
"sla_breach_count": 0,
"mean_time_to_remediate": {},
"sla_compliance_rate": 0.0,
"current_overdue": 0,
}
# Query findings in period grouped by severity
query = """
SELECT severity, COUNT(*) as total,
SUM(CASE WHEN remediated_at <= sla_deadline THEN 1 ELSE 0 END) as within_sla,
AVG(EXTRACT(EPOCH FROM (COALESCE(remediated_at, NOW()) - discovered_at))/86400) as avg_days
FROM vulnerability_sla
WHERE discovered_at BETWEEN %s AND %s
GROUP BY severity
"""
return metrics