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 incident-responsegit 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/incident-response)<a href="https://agentmods.dev/skills/liuxinye23/cyberstrikeai/incident-response"><img src="https://agentmods.dev/badge/skills/liuxinye23/cyberstrikeai/incident-response/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/incident-response"><img src="https://agentmods.dev/badge/skills/liuxinye23/cyberstrikeai/incident-response.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 | $0.00012 | $0.01371 |
| Opus 5 | $0.00006 | $0.00685 |
| Sonnet 5 | $0.00002 | $0.00274 |
| Haiku 4.5 | $0.00001 | $0.00137 |
Grade A, and why
incident-response scanned grade A with 0 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 10d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 272 lines — stays where its author put it; the contents beside it link to each section on GitHub.
安全事件响应
概述
安全事件响应是处理安全事件的关键流程。本技能提供安全事件响应的方法、工具和最佳实践。
响应流程
1. 准备阶段
准备工作:
- 建立响应团队
- 制定响应计划
- 准备工具和资源
- 建立通信渠道
2. 识别阶段
识别事件:
- 监控告警
- 异常检测
- 日志分析
- 用户报告
3. 遏制阶段
遏制措施:
- 隔离受影响系统
- 禁用账户
- 阻断网络连接
- 备份证据
4. 清除阶段
清除威胁:
- 移除恶意软件
- 修复漏洞
- 重置凭证
- 清理后门
5. 恢复阶段
恢复系统:
- 恢复备份
- 验证系统完整性
- 监控系统
- 逐步恢复服务
6. 总结阶段
总结经验:
- 事件报告
- 经验教训
- 改进措施
- 更新流程
工具使用
日志分析
使用Splunk:
# 搜索日志
index=security event_type="failed_login"
# 统计分析
index=security | stats count by src_ip
# 时间序列分析
index=security | timechart count by event_type
使用ELK:
# Elasticsearch查询
GET /logs/_search
{
"query": {
"match": {
"event_type": "malware"
}
}
}
取证工具
使用Volatility:
# 分析内存镜像
volatility -f memory.dump imageinfo
# 列出进程
volatility -f memory.dump --profile=Win7SP1x64 pslist
# 提取进程内存
volatility -f memory.dump --profile=Win7SP1x64 memdump -p 1234 -D output/
使用Autopsy:
# 启动Autopsy
# 创建案例
# 添加证据
# 分析数据
网络分析
使用Wireshark:
# 捕获流量
wireshark -i eth0
# 分析PCAP文件
wireshark -r capture.pcap
# 过滤流量
# 显示过滤器: ip.addr == 192.168.1.100
# 捕获过滤器: host 192.168.1.100
使用tcpdump:
# 捕获流量
tcpdump -i eth0 -w capture.pcap
# 分析流量
tcpdump -r capture.pcap -A
事件类型
恶意软件
响应步骤:
- 隔离受影响系统
- 收集样本
- 分析恶意软件
- 清除威胁
- 修复漏洞
工具:
- VirusTotal
- Cuckoo Sandbox
- YARA规则
数据泄露
响应步骤:
- 确认泄露范围
- 遏制泄露
- 评估影响
- 通知相关方
- 修复漏洞
检查项目:
- 泄露数据量
- 受影响用户
- 泄露渠道
- 数据敏感性
拒绝服务
响应步骤:
- 确认攻击类型
- 启用防护措施
- 过滤恶意流量
- 监控系统状态
- 恢复正常服务
防护措施:
- DDoS防护服务
- 流量清洗
- 限流措施
- CDN防护
未授权访问
响应步骤:
- 禁用受影响账户
- 重置凭证
- 检查访问日志
- 评估数据访问
- 修复漏洞
检查项目:
- 访问时间
- 访问内容
- 访问来源
- 数据修改
响应清单
准备阶段
- 建立响应团队
- 制定响应计划
- 准备工具
- 建立通信渠道
识别阶段
- 确认事件
- 收集信息
- 评估影响
- 记录时间线
遏制阶段
- 隔离系统
- 禁用账户
- 阻断连接
- 备份证据
清除阶段
- 移除威胁
- 修复漏洞
- 重置凭证
- 验证清除
恢复阶段
- 恢复系统
- 验证完整性
- 监控系统
- 恢复服务
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.
- 10d ago First seen · 272 lines · 12 tokens per session scan A 71534ce04821
incident-response is a skill published in the GitHub repository liuxinye23/CyberStrikeAI (0 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 12 tokens to every session and 1,371 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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