Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add liuxinye23/CyberStrikeAI --skill security-automationgit clone --depth 1 https://github.com/liuxinye23/CyberStrikeAIWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/liuxinye23/cyberstrikeai/security-automation)<a href="https://agentmods.dev/skills/liuxinye23/cyberstrikeai/security-automation"><img src="https://agentmods.dev/badge/skills/liuxinye23/cyberstrikeai/security-automation/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/liuxinye23/cyberstrikeai/security-automation"><img src="https://agentmods.dev/badge/skills/liuxinye23/cyberstrikeai/security-automation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00013 | $0.02156 |
| Opus 5 | $0.00006 | $0.01078 |
| Sonnet 5 | $0.00003 | $0.00431 |
| Haiku 4.5 | $0.00001 | $0.00216 |
Grade A, and why
security-automation scanned grade A with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
response = requests.post(url, json=data, headers=headers) Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
result = subprocess.run( How it starts
The opening of the file, as written. The whole thing — 383 lines — stays where its author put it; the contents beside it link to each section on GitHub.
安全自动化
概述
安全自动化是提高安全运营效率的重要手段。本技能提供安全自动化的方法、工具和最佳实践。
自动化场景
1. 漏洞扫描
自动化扫描:
- 定期扫描
- CI/CD集成
- 结果分析
- 报告生成
2. 安全测试
自动化测试:
- 单元测试
- 集成测试
- 安全测试
- 回归测试
3. 事件响应
自动化响应:
- 事件检测
- 自动遏制
- 通知告警
- 证据收集
4. 合规检查
自动化合规:
- 配置检查
- 策略验证
- 报告生成
- 修复建议
工具和框架
漏洞扫描自动化
使用Nessus API:
import requests
# 创建扫描
def create_scan(target, scan_name):
url = "https://nessus:8834/scans"
headers = {"X-ApiKeys": "access_key:secret_key"}
data = {
"uuid": "template-uuid",
"settings": {
"name": scan_name,
"text_targets": target
}
}
response = requests.post(url, json=data, headers=headers)
return response.json()
# 启动扫描
def launch_scan(scan_id):
url = f"https://nessus:8834/scans/{scan_id}/launch"
headers = {"X-ApiKeys": "access_key:secret_key"}
response = requests.post(url, headers=headers)
return response.json()
使用OpenVAS API:
from gvm.connections import UnixSocketConnection
from gvm.protocols.gmp import Gmp
# 连接OpenVAS
connection = UnixSocketConnection()
gmp = Gmp(connection)
gmp.authenticate('username', 'password')
# 创建扫描任务
target = gmp.create_target(name='target', hosts=['192.168.1.0/24'])
config = gmp.get_configs()[0]
scanner = gmp.get_scanners()[0]
task = gmp.create_task(
name='scan_task',
config_id=config['id'],
target_id=target['id'],
scanner_id=scanner['id']
)
# 启动扫描
gmp.start_task(task['id'])
CI/CD集成
Jenkins Pipeline:
pipeline {
agent any
stages {
stage('Security Scan') {
steps {
sh 'npm audit'
sh 'snyk test'
sh 'sonar-scanner'
}
}
stage('Vulnerability Scan') {
steps {
sh 'nmap --script vuln target'
}
}
}
post {
always {
publishHTML([
reportDir: 'reports',
reportFiles: 'report.html',
reportName: 'Security Report'
])
}
}
}
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 383 lines · 13 tokens per session scan A 0ffb9476c146
security-automation is a skill published in the GitHub repository liuxinye23/CyberStrikeAI (0 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 13 tokens to every session and 2,156 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 2 findings (makes network calls, runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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