Atlas / Skills / utkusen / Sast Analysis

Sast AnalysisSAFE

skills/utkusen/sast-analysis

Collection of agent skills to find vulnerabilities inside your web/mobile apps.

Verdict
SAFE
Grade
B
Trust score
89 /100
Version
—
Hosts
—
License
MIT
Stars
1,336
01

Overview

Collection of agent skills to find vulnerabilities inside your web/mobile apps.

Read from source at commit d9c848ebb5f1OBSERVED · 2026-10-13
02

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
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:

```markdown
# 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.
03

Trust audit

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

LayerWhat it checksResult
L0Provenance & inventoryPASS
L1Static analysis of the codeNA
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (0)

No findings outside the package's declared scope.

Gates applied: no_behavioural_pass.

Audited 2026-10-13 · audit v0.4.1 · source sha d9c848ebb5f1full audit observations/trust-audit/skill/utkusen__sast-analysis.json · Report an issue / request a re-scan
04

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-10-13d9c848ebb5f1SAFEB89first audit
05

Questions

What does the Sast Analysis skill do?

Collection of agent skills to find vulnerabilities inside your web/mobile apps.

Is Sast Analysis safe to install?

The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.

What can Sast Analysis access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

How current is this page?

The grade is for one exact copy of the source (d9c848ebb5f1), read on 2026-10-13. The repository is watched, and a new audit runs when it changes — this is the first audit.

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