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sast-analysis

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

Install / Use

npx skills add utkusen/sast-skills --skill sast-analysis

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

81/100

Category

Security

Supported Platforms

Universal

Our assessment of sast-analysis

sast-analysis scores 81/100 on our quality scale, 746th of 971 Security skills we index.

Its SKILL.md is 4.0 KB long, well organised into 11 sections with 1 code example: a solid amount of guidance for an agent.

With 1,321 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
26/30
Structure
17/20
Description
15/15
Adoption
13/20
Freshness
11/15

Maintenance, license and trust

  • The repository was last updated about 6 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 98/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

sast-analysis compared with similar skills

All 4 of these similar skills score higher than sast-analysis; compare them before choosing.

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sast-analysis (this skill)by utkusen811.3k6mo agoSKILL.md
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ui-ux-pro-maxby nextlevelbuilder100130.2k9d agoSKILL.md

Frequently asked questions

How do I install sast-analysis?
Run npx skills add utkusen/sast-skills --skill sast-analysis. The install tabs above show the steps for each supported agent.
Which AI agents does sast-analysis work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is sast-analysis safe to use?
It is MIT-licensed and scores 98/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is sast-analysis still maintained?
The repository was last updated about 6 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.

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.

Codebase Analysis

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

Phase 1: Technology Reconnaissance

Explore the codebase and identify:

  • Languages: All programming languages used and their versions if specified
  • Frameworks: Web frameworks, ORM layers, template engines, task queues
  • Package managers & dependencies: Lock files, dependency manifests (package.json, requirements.txt, go.mod, Gemfile, pom.xml, etc.)
  • Infrastructure hints: Dockerfiles, docker-compose, Kubernetes manifests, Terraform, CI/CD configs
  • Databases: SQL, NoSQL, cache layers, message brokers — look at connection strings, ORM models, migration files
  • Authentication & authorization: Auth libraries, middleware, session configs, OAuth/OIDC providers, JWT usage, API key patterns
  • External integrations: Third-party APIs, payment processors, email services, cloud SDKs, webhook handlers
  • Entry points: HTTP routes, GraphQL schemas, gRPC service definitions, CLI commands, WebSocket handlers, scheduled jobs, message consumers

Start by reading dependency manifests, project configs, and directory structure. Then drill into source code to confirm findings.

Phase 2: Architecture Mapping

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 |
|---|---|---|---|
| ... | ... | ... | ... |

Important Reminders

  • Do NOT report specific vulnerabilities (like "line 42 has SQL injection"). That comes in later phases.
  • Be thorough in exploration. Read actual source code, not just config files. Look at how auth middleware is applied, how queries are built, how file uploads are handled.
  • If the codebase is large, prioritize security-sensitive areas: auth, payment, data access, file handling, admin functionality.

Related Skills

View on GitHub
GitHub Stars1.3k
CategorySecurity
Updated5mo ago
Forks65

Trust signals

98/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

1 info