cheat-on-content
给所有想把"感觉"变成可校准预测的内容创作者。**方法论通用**——打分 → 盲预测 → T+3d 复盘 → 进化 rubric 的循环适用任何能被量化(播放 / 阅读 / 收听 / 点击)的内容。**rubric 是循环的内容,不是循环本身**——当前内置一份观点视频 rubric(参考博主 25+…
Advanced vulnerability analysis principles. OWASP 2025, Supply Chain Security, attack surface mapping, risk prioritization.
$ npx -y skills add LiHongwei-cn/lihongwei-cn --skill vulnerability-scanner --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/vulnerability-scannerContext preview
The summary Claude sees to decide when to auto-load this skill.
Advanced vulnerability analysis principles. OWASP 2025, Supply Chain Security, attack surface mapping, risk prioritization.
name: vulnerability-scanner description: "Advanced vulnerability analysis principles. OWASP 2025, Supply Chain Security, attack surface mapping, risk prioritization." risk: unknown source: community date_added: "2026-02-27"
> Think like an attacker, defend like an expert. 2025 threat landscape awareness.
**Execute for automated validation:**
| Script | Purpose | Usage | |--------|---------|-------| | `scripts/security_scan.py` | Validate security principles applied | `python scripts/security_scan.py <project_path>` |
| File | Purpose | |------|---------| | [checklists.md](checklists.md) | OWASP Top 10, Auth, API, Data protection checklists |
---
| Principle | Application | |-----------|-------------| | **Assume Breach** | Design as if attacker already inside | | **Zero Trust** | Never trust, always verify | | **Defense in Depth** | Multiple layers, no single point | | **Least Privilege** | Minimum required access only | | **Fail Secure** | On error, deny access |
Before scanning, ask: 1. What are we protecting? (Assets) 2. Who would attack? (Threat actors) 3. How would they attack? (Attack vectors) 4. What's the impact? (Business risk)
---
| Rank | Category | Think About | |------|----------|-------------| | **A01** | Broken Access Control | Who can access what? IDOR, SSRF | | **A02** | Security Misconfiguration | Defaults, headers, exposed services | | **A03** | Software Supply Chain 🆕 | Dependencies, CI/CD, build integrity | | **A04** | Cryptographic Failures | Weak crypto, exposed secrets | | **A05** | Injection | User input → system commands | | **A06** | Insecure Design | Flawed architecture | | **A07** | Authentication Failures | Session, credential management | | **A08** | Integrity Failures | Unsigned updates, tampered data | | **A09** | Logging & Alerting | Blind spots, no monitoring | | **A10** | Exceptional Conditions 🆕 | Error handling, fail-open states |
2021 → 2025 Shifts: ├── SSRF merged into A01 (Access Control) ├── A02 elevated (Cloud/Container configs) ├── A03 NEW: Supply Chain (major focus) ├── A10 NEW: Exceptional Conditions └── Focus shift: Root causes > Symptoms
---
| Vector | Risk | Question to Ask | |--------|------|-----------------| | **Dependencies** | Malicious packages | Do we audit new deps? | | **Lock files** | Integrity attacks | Are they committed? | | **Build pipeline** | CI/CD compromise | Who can modify? | | **Registry** | Typosquatting | Verified sources? |
---
| Category | Elements | |----------|----------| | **Entry Points** | APIs, forms, file uploads | | **Data Flows** | Input → Process → Output | | **Trust Boundaries** | Where auth/authz checked | | **Assets** | Secrets, PII, business data |
Risk = Likelihood × Impact High Impact + High Likelihood → CRITICAL High Impact + Low Likelihood → HIGH Low Impact + High Likelihood → MEDIUM Low Impact + Low Likelihood → LOW
---
| Factor | Weight | Question | |--------|--------|----------| | **CVSS Score** | Base severity | How severe is the vuln? | | **EPSS Score** | Exploit likelihood | Is it being exploited? | | **Asset Value** | Business context | What's at risk? | | **Exposure** | Attack surface | Internet-facing? |
Is it actively exploited (EPSS >0.5)?
├── YES → CRITICAL: Immediate action
└── NO → Check CVSS
├── CVSS ≥9.0 → HIGH
├── CVSS 7.0-8.9 → Consider asset value
└── CVSS <7.0 → Schedule for later---
| Scenario | Fail-Open (BAD) | Fail-Closed (GOOD) | |----------|-----------------|---------------------| | Auth error | Allow access | Deny access | | Parsing fails | Accept input | Reject input | | Timeout | Retry forever | Limit + abort |
---
1. RECONNAISSANCE
└── Understand the target
├── Technology stack
├── Entry points
└── Data flows
2. DISCOVERY
└── Identify potential issues
├── Configuration review
├── Dependency analysis
└── Code pattern search
3. ANALYSIS
└── Validate and prioritize
├── False positive elimination
├── Risk scoring
└── Attack chain mapping
4. REPORTING
└── Actionable findings
├── Clear reproduction steps
├── Business impact
└── Remediation guidance---
| Pattern | Risk | Look For | |---------|------|----------| | **String concat in queries** | Injection | `"SELECT * FROM " + user_input` | | **Dynamic code execution** | RCE | `eval()`, `exec()`, `Function()` | | **Unsafe deserialization** | RCE | `pickle.loads()`, `unserialize()` | | **Path manipulation** | Traversal | User input in file paths | | **Disabled security** | Various | `verify=False`, `--insecure` |
| Type | Indicators | |------|-----------| | API Keys | `api_key`, `apikey`, high entropy | | Tokens | `token`, `bearer`, `jwt` | | Credentials | `password`, `secret`, `key` | | Cloud | `AWS_`, `AZURE_`, `GCP_` prefixes |
---
| Layer | You Own | Provider Owns | |-------|---------|---------------| | Data
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Repo: LiHongwei-cn/lihongwei-cn
给所有想把"感觉"变成可校准预测的内容创作者。**方法论通用**——打分 → 盲预测 → T+3d 复盘 → 进化 rubric 的循环适用任何能被量化(播放 / 阅读 / 收听 / 点击)的内容。**rubric 是循环的内容,不是循环本身**——当前内置一份观点视频 rubric(参考博主 25+…
提议并执行 rubric 或 bucket 升级。两种模式:**完整 rubric bump**(最高风险动作,5 步强制 + 跨模型审核)和 **--bucket-only 轻量重校**(只换 bucket 边界,不动 rubric 公式)。**Phase 2 强制走 cheat-score-blind…
cheat-on-content 的首次 onboarding 与脚手架创建器。统一流程——所有用户都走相同 5 阶段闭环,唯一区别是"发过视频的人"会在 init 时多一步:抓取已有视频建立历史 context(用于后续 cheat-seed 给更贴合的选题、更准的…
从对标账号导入 script + 数据 → 拆 pattern + 派生 base rubric 信号 → 写到 benchmark.md / script_patterns.md / rubric_notes.md。**这是工具最早期信号的来源**——cold-start…
把老用户的 .cheat-state.json 升级到当前 schema_version。读 migrations/registry.md 算迁移链,按顺序应用每一步迁移文件。幂等:跑两次结果一样。失败停在中间版本不前进。触发词:"迁移"/"升级 state"/"migrate"/"我的 state…
从复盘评论数据派生 / 刷新账号的受众画像,写入 audience.md。这是和 rubric 平行的第二个派生物——rubric 答"怎么打分",persona 答"谁在看"。cheat-seed 选题 / 写稿时读它。**audience.md 含实绩信号,cheat-score-blind…