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Security Best Practices

该 Skill 提供安全优先的代码审查工作流:先确认系统边界、技术栈证据与威胁假设,再按认证授权、输入校验、密钥管理、依赖供应链、日志与错误处理等基线系统排查;按可利用性排序输出含文件路径、证据片段与影响说明的发现,并给出严重级别模型、最小差异修复方向与风险例外记录。无证据不下结论。

ivangdavila
ivangdavila
热度 68.90
最近更新 2026-05-11 17:27:43
分类:安全依赖:读写文件 / 内部调用大模型应用场景:代码审查 / 报告撰写 / 工作流

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add security-best-practices
Metadata
name
Security Best Practices
slug
security-best-practices
version
1.0.0
homepage
https://clawic.com/skills/security-best-practices
description
Review code with secure-by-default standards, prioritize exploitable risks, and deliver minimal-diff fixes with evidence and regression checks.
changelog
Added a complete security review workflow with evidence standards, severity modeling, and minimal-risk remediation guidance.
metadata
{"clawdbot":{"emoji":"🛡️","requires":{"bins":[],"config":["~/security-best-practices/"]},"os":["linux","darwin","win32"]}}

Setup

On first use, read setup.md for integration guidelines. If local memory is needed, ask for consent before creating ~/security-best-practices/.

When to Use

Use this skill for secure-by-default implementation, targeted vulnerability reviews, and prioritized security reports with actionable fixes. Activate when the user requests security guidance, hardening, risk triage, or remediation planning.

Architecture

Memory lives in ~/security-best-practices/. See memory-template.md for setup.

~/security-best-practices/
|- memory.md        # Stable context, preferences, and activation boundaries
|- findings-log.md  # Findings registry with severity and status
`- exceptions.md    # Approved security exceptions and review dates

Quick Reference

Load only the minimum file needed for the current request.

Topic File
Setup process setup.md
Memory template memory-template.md
Full review workflow review-playbook.md
Severity model and scoring severity-model.md
Safe remediation patterns remediation-patterns.md
Risk exception log exceptions.md

Core Rules

1. Establish Scope and Evidence First

Before any conclusions, confirm:

  • System boundary (service, module, endpoint, or workflow)
  • Stack evidence (language, framework, deployment context)
  • Threat assumptions (external attacker, internal misuse, privilege level)

No evidence, no finding.

2. Map Risks to a Repeatable Baseline

Evaluate every review against a consistent baseline:

  • Authn/authz boundaries
  • Input validation and output encoding
  • Secrets handling and configuration safety
  • Dependency and supply chain posture
  • Logging, error handling, and data exposure controls

Use review-playbook.md to keep scans systematic instead of ad hoc.

3. Produce Findings That Are Verifiable

Each finding must include:

  • Severity from severity-model.md
  • File path and line references
  • Concrete evidence snippet
  • Impact statement in plain language
  • Minimal safe fix direction

Avoid speculative findings without repository evidence.

4. Prioritize Exploitability Over Theory

Rank by practical risk, not by checklist volume:

  • Reachability from untrusted inputs
  • Privilege required by attacker
  • Blast radius if exploited
  • Ease of abuse and repeatability

High confidence, exploitable issues come first.

5. Remediate With Minimal Product Risk

Fix one finding at a time:

  • Prefer small diffs that preserve existing behavior
  • Add tests when security fixes alter code paths
  • Flag expected behavior changes before implementing
  • Re-run project validation after each fix batch

Use remediation-patterns.md for safe rollouts.

6. Respect Explicit Exceptions and Ownership

If the user accepts a known risk:

  • Record rationale in exceptions.md
  • Define expiry or next review date
  • Keep the exception scoped to the specific context

Never apply broad silent overrides.

Security Review Traps

  • Reporting generic best practices without file evidence -> low-trust output that teams cannot action.
  • Flooding with low-severity noise -> critical vulnerabilities get ignored.
  • Proposing major refactors as "quick fixes" -> teams reject security work due to delivery risk.
  • Ignoring framework defaults and deployment context -> false positives and wrong remediations.
  • Declaring a system "secure" after one pass -> hidden regressions remain untested.

Security & Privacy

Data that leaves your machine:

  • None by default from this skill itself.

Data that stays local:

  • Review preferences and finding history in ~/security-best-practices/.
  • Exception rationale in local memory files only.

This skill does NOT:

  • Exfiltrate source code to undeclared third-party endpoints.
  • Mark unresolved risks as fixed.
  • Perform hidden destructive changes.

Related Skills

Install with clawhub install <slug> if user confirms:

  • auth - Authentication design and hardening.
  • authorization - Access control and permission boundaries.
  • encryption - Key management and cryptographic hygiene.
  • firewall - Network exposure review and policy controls.
  • devops - Secure delivery, CI checks, and operational safeguards.

Feedback

  • If useful: clawhub star security-best-practices
  • Stay updated: clawhub sync