CyberStrikeAI is a security operations workspace that turns natural-language plans into governed, auditable actions while recording evidence and results for later reuse. Authorized security teams use it to manage agents, tools, vulnerabilities, knowledge, and attack-chain analysis. Catalogue add-ons provide agent and skill workflows for working with the platform.
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 Ed1s0nZ/CyberStrikeAI --skill pentest-agent-osgit clone --depth 1 https://github.com/Ed1s0nZ/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/ed1s0nz/cyberstrikeai/pentest-agent-os)<a href="https://agentmods.dev/skills/ed1s0nz/cyberstrikeai/pentest-agent-os"><img src="https://agentmods.dev/badge/skills/ed1s0nz/cyberstrikeai/pentest-agent-os/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/ed1s0nz/cyberstrikeai/pentest-agent-os"><img src="https://agentmods.dev/badge/skills/ed1s0nz/cyberstrikeai/pentest-agent-os.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00163 | $0.01211 |
| Opus 5 | $0.00081 | $0.00606 |
| Sonnet 5 | $0.00033 | $0.00242 |
| Haiku 4.5 | $0.00016 | $0.00121 |
Grade A, and why
pentest-agent-os 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 11d 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.
What it actually says
渗透测试Agent操作系统
渗透不是执行脚本,是搜索路径。 不给自己预设固定路径/角色/已知利用链。给定起点与目标, 路径未知 → 在状态空间里搜索:不断试不同路径、试错、反馈、逼近目标。 跳出固有攻击链 = 不问"它有没有已知CVE",而问"基于项目黑板上已掌握的事实,下一步最有效的动作是什么"。 状态落点见
pentest-blackboard（SQLite 项目事实，非磁盘 Intent/Hint 状态机）。
套件映射（按作用分类）
| 主题 | skill name |
作用 |
|---|---|---|
| 套件索引与核心心法 | pentest-agent-os |
套件索引与核心心法 |
| 项目黑板 | pentest-blackboard |
项目 Fact 图 / 边记录 / 与漏洞分工 |
| 验证铁律 | pentest-verification |
验证铁律（防幻觉） |
| 能力原语 + 状态空间搜索 | capability-primitive-search |
能力原语凑链/状态空间搜索 |
| 联网情报收集 | component-vuln-intel |
组件识别后联网搜洞 |
| 侦察/攻击面测绘 | attack-surface-recon |
侦察与攻击面测绘 |
| 初始访问/钓鱼/社工 | initial-access-phishing |
初始访问/钓鱼/社工 |
| Web注入+认证+服务端+杂项+CDN | web-attack-methods |
Web全栈攻击手法 |
| 源码狩猎 | source-code-hunting |
源码/密钥/供应链狩猎 |
| 后渗透/提权+凭据破解 | post-exploitation |
后渗透/提权/凭据/密码学 |
| 内网域 | active-directory-attack |
内网域/AD攻击 |
| APK/EXE/二进制 | binary-mobile-reversing |
移动端/二进制逆向 |
| 云 | cloud-attack-methods |
云与对象存储攻击 |
| 区块链/智能合约 | blockchain-contract-attack |
区块链/智能合约 |
| AI/LLM应用 | ai-llm-app-attack |
AI/LLM应用攻击 |
| 无线/硬件 | wireless-hardware-attack |
无线与硬件攻击 |
| 0day自主发现引擎 | zero-day-discovery |
0day/N-day自主发现 |
| 自找代理+工具自举 | proxy-tool-bootstrap |
代理换路与工具自举 |
| OPSEC/隐蔽作战 | redteam-opsec |
OPSEC/隐蔽作战纪律 |
| 输出规范 | pentest-output-standards |
报告/台账/输出规范 |
| 专题实战+文件索引 | specialized-attack-playbooks |
专题实战利用手册 |
| 不设限原则 | unlimited-attack-scope |
不设限原则 |
使用方式
- 先加载
pentest-agent-os（本索引）理解套件结构。 - 按当前攻击面加载对应 skill（例：识别组件→
component-vuln-intel；Web→web-attack-methods；全网无洞→zero-day-discovery）。 - 黑板/铁律/能力原语（
pentest-blackboard/pentest-verification/capability-primitive-search）为全流程常驻规则。 - 按攻击面加载对应 skill；细节均在目标 skill 内完整保留。
强制行为触发器速查（完整原文在 pentest-blackboard）
- 触发1[识别→搜] → 执行
component-vuln-intel全部命令；线索 tentative，验证后再 confirmed/漏洞 - 触发2[拒绝→换路] → 执行
proxy-tool-bootstrap换路序列；不通则写负结果 Fact - 触发3[新认知→横向] → 凭据/域名/IP 立即横向扩展并
upsert_project_fact
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.
- 11d ago First seen · 59 lines · 163 tokens per session scan A 215bdab3c8d9
pentest-agent-os is a skill published in the GitHub repository Ed1s0nZ/CyberStrikeAI (6,410 stars, last pushed 16d ago), licensed Apache-2.0. It adds 163 tokens to every session and 1,211 once invoked, about $0.0008 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 2026-08-30.
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