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 zero-day-discoverygit 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/zero-day-discovery)<a href="https://agentmods.dev/skills/ed1s0nz/cyberstrikeai/zero-day-discovery"><img src="https://agentmods.dev/badge/skills/ed1s0nz/cyberstrikeai/zero-day-discovery/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/zero-day-discovery"><img src="https://agentmods.dev/badge/skills/ed1s0nz/cyberstrikeai/zero-day-discovery.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 | $0.00064 | $0.00753 |
| Opus 5 | $0.00032 | $0.00377 |
| Sonnet 5 | $0.00013 | $0.00151 |
| Haiku 4.5 | $0.00006 | $0.00075 |
Grade A, and why
zero-day-discovery 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
0day 自主发现引擎（全网搜不到漏洞时自己挖）
核心转变: 从"匹配已知漏洞库"→"理解代码/协议怎么工作,推断它哪里会坏"。0day不是运气,是方法。
五条主路:
1.变体分析(最高产): 拿一个CVE补丁→提炼漏洞模式→全库grep同模式其它位置→补丁没覆盖的=0day
2.补丁间隙: 读补丁过滤逻辑,黑名单几乎总能绕(漏了某种编码/等价函数/别名)→新CVE
3.差分测试: 两组件对同一输入理解不一致(WAF vs 后端/校验器 vs 执行器)→走私/SSRF绕过
4.Fuzzing: 写harness(包住处理不可信输入的函数)+造语料/字典+崩溃triage(可复现/可控/可利用性)
AFL++/libFuzzer(覆盖率引导找内存破坏) boofuzz(协议) radamsa(黑盒) restler(REST API)
5.污点推理(有源码最强): source(参数/Header/反序列化字段)无有效sanitizer到sink(exec/SQL/模板)=0day
CodeQL写query自动求数据流可达 / Semgrep / Joern
N-day武器化(advisory出了但全网无PoC): 从补丁diff逆向重建exploit(bindiff/diaphora二进制对比,
厂商regression test常就是PoC雏形)→本地试验场调通→打目标。漏洞窗口期最大化,红队最值钱能力之一。
猎人思维(看任何代码/端点/协议逐层逼问,每个"是"都是0day候选):
信任边界:假设输入可信吗?什么情况不成立? | 状态时序:两步间状态能改吗(TOCTOU)?能打乱顺序吗?
解析规范化:解析几次?normalize在校验前还是后? | 边界极值:负数/0/超大/类型混淆/编码/null字节?
隐含能力:这功能"顺便"给了我什么? | 唯一性:ID/token可预测吗?"秘密"真是秘密吗?
把组件变"假设清单"逐个打破: 文件上传隐含假设"只传图片/扩展名可信/文件名不含路径/内容只是数据"→逐个打破=漏洞,组合=链。
0day验证(比CVE要求更高): 可复现(最小PoC)+根因清楚(哪行/哪个假设)+影响可证(实际读写执行)+排除误报。
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 · 31 lines · 64 tokens per session scan A 81e41579c6d4
zero-day-discovery is a skill published in the GitHub repository Ed1s0nZ/CyberStrikeAI (6,410 stars, last pushed 15d ago), licensed Apache-2.0. It adds 64 tokens to every session and 753 once invoked, about $0.0003 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.
Other skills, from other repositories
fix-security-vulnerabilities-with-strix
Fix security vulnerabilities found by a Strix pentest (open-source CLI or app.strix.ai cloud) — triage by severity, patch the root cause rather than the symptom, and re-run Strix to prove each fix actually closes the exploit. Handles injection, XSS, SSRF, broken access control, IDOR, and other validated findings. Use…
find-security-vulnerabilities-in-code
Find security vulnerabilities in a codebase or repository with Strix — a white-box AI security review that reads your source, reasons about the actual data flow and authorization model, then exploits what it finds in a live sandbox so every reported issue has a working proof-of-concept instead of a noisy…
managed-pentesting-with-strix
Run a managed pentest of a web app, API, repository, or local workspace on the app.strix.ai platform with the strix cloud CLI or REST API — no local Docker or LLM key needed. Safely review and upload local source, register assets, launch and poll scans, triage vulnerabilities, export SARIF, download compliance…
ci-security-scanning-with-strix
Add security scanning to CI/CD with Strix — GitHub Actions, GitLab CI, or any pipeline — so every pull request gets a diff-scoped AI pentest that blocks vulnerable code before it merges, with results as PR comments and SARIF uploaded to code scanning. Covers both the self-hosted open-source CLI (runs in your runner)…
svc-mobile-android
Android APK static analysis — OWASP Mobile Top 10, Retrofit API audit, transport security, smali reading, component export, auth flow analysis. Use when target is an APK/Android app. Triggers - APK, Android, mobile app, decompiled, smali, jadx, apktool.
web-auth-bypass-idor
Broken access control - IDOR, privilege escalation, JWT abuse, mass assignment, forced browsing - for web apps and APIs. Use on any multi-user or role-based app with object IDs, tokens, or admin functionality. Triggers - /api/users/ , /orders/ , ?account=/uid=/doc=, JWT (eyJ...), role/isAdmin field, admin panel, "403…