sast-businesslogic
Detect business logic vulnerabilities in a codebase using a three-phase approach: threat modeling (domain analysis and attack…
Perform codebase analysis and architecture mapping as the first phase of a security assessment. Explores the tech stack, frameworks, entry points, data flows, and trust boundaries. Outputs sast/architecture.md. Run this before any vulnerability detection skill. Use when asked to
Claude Code
$ npx -y skills add utkusen/sast-skills --skill sast-analysis --agent claude-code
Codex
$ npx skills add utkusen/sast-skills --skill sast-analysis -a codex -y
Cursor
$ npx skills add utkusen/sast-skills --skill sast-analysis -a cursor -y
Gemini CLI
$ npx skills add utkusen/sast-skills --skill sast-analysis -a gemini-cli -y
GitHub Copilot
$ npx skills add utkusen/sast-skills --skill sast-analysis -a github-copilot -y
OpenCode
$ npx skills add utkusen/sast-skills --skill sast-analysis -a opencode -y
Windsurf
$ npx skills add utkusen/sast-skills --skill sast-analysis -a windsurf -y
name: sast-analysis description: >- Perform codebase analysis and architecture mapping as the first phase of a security assessment. Explores the tech stack, frameworks, entry points, data flows, and trust boundaries. Outputs sast/architecture.md. Run this before any vulnerability detection skill. Use when asked to analyze a codebase for security or when sast/architecture.md does not yet exist.
You are performing the first phase of a security assessment. Your goal is to deeply understand the codebase. You are NOT looking for specific vulnerabilities yet. This is pure reconnaissance.
Create a `sast/` folder in the project root (if it doesn't already exist). This phase produces one output file inside it:
`sast/architecture.md` — technology stack, architecture, entry points, data flows
Explore the codebase and identify:
Start by reading dependency manifests, project configs, and directory structure. Then drill into source code to confirm findings.
Based on Phase 1, build a mental model of:
1. **Service boundaries**: Is this a monolith or microservices? What talks to what? 2. **Data flow**: How does user input enter the system, get processed, get stored, and get returned? 3. **Trust boundaries**: Where does the system transition between trusted and untrusted contexts? (e.g., user input -> backend, backend -> database, service -> service, server -> client) 4. **Privilege levels**: What roles/permissions exist? How are they enforced? Is there an admin panel? 5. **Sensitive data inventory**: PII, credentials, tokens, financial data, health records — where is each stored and how does it move?
**Write the results of Phase 1 and Phase 2 to `sast/architecture.md`.** Use this format:
# Architecture: [Project Name] ## Technology Stack | Category | Details | |---|---| | Languages | ... | | Frameworks | ... | | Databases | ... | | Auth mechanism | ... | | Infrastructure | ... | | External services | ... | ## Architecture Overview [Describe the architecture: monolith vs microservices, how components interact, main modules and their responsibilities] ## Data Flow [Trace how user input enters the system, gets processed, stored, and returned. Cover the primary flows (e.g., registration, login, core business actions).] ## Entry Points | Entry Point | Type | Auth Required | Description | |---|---|---|---| | ... | HTTP/GraphQL/WS/etc. | Yes/No | ... | ## Trust Boundaries [List each trust boundary and what crosses it] ## Sensitive Data Inventory | Data Type | Where Stored | How Accessed | Protection | |---|---|---|---| | ... | ... | ... | ... |
A collection of agent skills that turn your LLM coding assistant into a fully functional SAST scanner to find vulnerabilities in your codebase. Works natively with Claude Code, Codex, Opencode, Cursor and any other assistant that supports agent skills.
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