external/anthropic-cybersecurity-skills/skills/triaging-vulnerabilities-with-ssvc-framework/SKILL.md
Triage and prioritize vulnerabilities using CISA's Stakeholder-Specific Vulnerability Categorization (SSVC) decision tree framework to produce actionable remediation priorities.
npx skillsauth add seikaikyo/dash-skills triaging-vulnerabilities-with-ssvc-frameworkInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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The Stakeholder-Specific Vulnerability Categorization (SSVC) framework, developed by Carnegie Mellon University's Software Engineering Institute (SEI) in collaboration with CISA, provides a structured decision-tree methodology for vulnerability prioritization. Unlike CVSS alone, SSVC accounts for exploitation status, technical impact, automatability, mission prevalence, and public well-being impact to produce one of four actionable outcomes: Track, Track*, Attend, or Act.
requests, pandas, and jinja2 librariesAssess current exploitation activity:
# Check if a CVE is in CISA Known Exploited Vulnerabilities catalog
curl -s "https://www.cisa.gov/sites/default/files/feeds/known_exploited_vulnerabilities.json" | \
python3 -c "import sys,json; data=json.load(sys.stdin); cves=[v['cveID'] for v in data['vulnerabilities']]; print('Active' if 'CVE-2024-3400' in cves else 'Check PoC/None')"
Determine scope of compromise if exploited:
Evaluate if exploitation can be automated at scale:
How widespread is the affected product in your environment:
Potential consequences for physical safety and public welfare:
| Outcome | Action Required | SLA | |---------|----------------|-----| | Track | Monitor, remediate in normal patch cycle | 90 days | | Track* | Monitor closely, prioritize in next patch window | 60 days | | Attend | Escalate to senior management, accelerate remediation | 14 days | | Act | Apply mitigations immediately, executive-level awareness | 48 hours |
import requests
import json
# Fetch CISA KEV catalog
kev_url = "https://www.cisa.gov/sites/default/files/feeds/known_exploited_vulnerabilities.json"
kev_data = requests.get(kev_url).json()
kev_cves = {v['cveID'] for v in kev_data['vulnerabilities']}
# Fetch EPSS scores for context
epss_url = "https://api.first.org/data/v1/epss"
epss_response = requests.get(epss_url, params={"cve": "CVE-2024-3400"}).json()
def evaluate_exploitation(cve_id, kev_set):
"""Determine exploitation status from CISA KEV and EPSS data."""
if cve_id in kev_set:
return "active"
epss = requests.get(
"https://api.first.org/data/v1/epss",
params={"cve": cve_id}
).json()
if epss.get("data"):
score = float(epss["data"][0].get("epss", 0))
if score > 0.5:
return "poc"
return "none"
def evaluate_technical_impact(cvss_vector):
"""Parse CVSS vector for scope and impact metrics."""
if "S:C" in cvss_vector or "C:H/I:H/A:H" in cvss_vector:
return "total"
return "partial"
def evaluate_automatability(cvss_vector, cve_description):
"""Check if attack vector is network-based with low complexity."""
if "AV:N" in cvss_vector and "AC:L" in cvss_vector and "UI:N" in cvss_vector:
return "yes"
return "no"
def ssvc_decision(exploitation, tech_impact, automatability, mission_prevalence, public_wellbeing):
"""CISA SSVC decision tree implementation."""
if exploitation == "active":
if tech_impact == "total" or automatability == "yes":
return "Act"
if mission_prevalence in ("essential", "support"):
return "Act"
return "Attend"
if exploitation == "poc":
if automatability == "yes" and tech_impact == "total":
return "Attend"
if mission_prevalence == "essential":
return "Attend"
return "Track*"
# exploitation == "none"
if tech_impact == "total" and mission_prevalence == "essential":
return "Track*"
return "Track"
# Run the SSVC triage script against scan results
python3 scripts/process.py --input scan_results.csv --output ssvc_triage_report.json
# View summary
cat ssvc_triage_report.json | python3 -m json.tool | head -50
# Export Nessus scan as CSV, then process
python3 scripts/process.py \
--input nessus_export.csv \
--format nessus \
--output ssvc_results.json
# Export OpenVAS results as XML
python3 scripts/process.py \
--input openvas_report.xml \
--format openvas \
--output ssvc_results.json
# Test SSVC decision logic with known CVEs
python3 -c "
from scripts.process import ssvc_decision
# CVE-2024-3400 - Palo Alto PAN-OS command injection (KEV listed)
assert ssvc_decision('active', 'total', 'yes', 'essential', 'material') == 'Act'
# CVE-2024-21887 - Ivanti Connect Secure (PoC available)
assert ssvc_decision('poc', 'total', 'yes', 'support', 'minimal') == 'Attend'
print('All SSVC decision tests passed')
"
development
拋棄式 HTML mockup 比稿:產出 2 到 3 個設計立場不同的變體(密度 / 版式 / 強調軸,不是換色),各附取捨說明,最後給有立場的對比結論。適用:「畫個草圖」「比較 A 版 B 版」「先看方向再做」「給我看幾種做法」。要 production 元件或設計已定案時不適用。
tools
需求不明時的意圖萃取訪談:一次一題、每題附上自己的猜測、聽出「真正想要 vs 覺得應該要」,直到能預測使用者反應(約 95% 信心)才動工。適用:需求缺少對象 / 動機 / 成功標準 / 約束,或使用者點名「訪談我」「先確認一下」「我們確定嗎」。明確自足的指示、純資訊查詢、機械性操作不適用。
development
對非平凡決策啟動新鮮 context 對抗審查(找碴不背書),在修正還便宜的時候抓出錯誤方向。適用:高風險改動(production、資安敏感邏輯、不可逆操作)、不熟的程式碼、要宣稱「這樣是安全的 / 可行的」之前。機械性操作與一行修改不適用。
testing
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