Secure your Pythonbefore you ship.

Open source static analysis that finds dead code, secrets, and vulnerabilities.
Run locally or gate your GitHub PRs.

Connect GitHubBook a Demo

Open source

2-minute setup

SOC2 ready

Tainted input interpolated into SQL execute()

Connect GitHub

snippet.py

Findings2

HIGHSKY-D211

Possible SQL injection: tainted input appears interpolated into SQL execute()

snippet.py:7

Source

def search_users(conn):
    q = request.args.get("q")
    sql = f"SELECT * FROM users WHERE name = '{q}'"
    cur = conn.cursor()
    cur.execute(sql)
    return cur.fetchall()

Run on your repo

$ skylos . --danger --quality --upload

Lightweight demo — full scanner uses repo context and 200+ rules.

Get started free

Vulnerabilities Caught

Across 100+ projects

Hours Saved

Manual code review time

Accuracy Rate

Near-zero false positives

Complete Python Security Scanning

Four detection engines in one fast tool.

Vulnerability Scanner

Prevent SQL injection, XSS, and command injection attacks by catching unsafe patterns in your code.

Secret Detection

Stop data leaks. Skylos finds hardcoded API keys, tokens, and passwords in your source code commits.

Dead Code Removal

Clean your technical debt. Identify unused imports, functions, and unreachable variables automatically.

Quality Gate

Enforce coding standards and reduce complexity with automated quality checks in your CI pipeline.

Benchmark: Skylos vs Vulture

We tested both tools against a realistic FastAPI + Pydantic codebase seeded with known dead code. The goal: Measure detection accuracy in a modern Python stack.

Test Methodology

We ran both tools on a standard service architecture containing:

29 seeded bugs: Unused imports, functions, and variables.
Framework magic: FastAPI routers, Pydantic models, and Pytest fixtures (which often trigger false positives).

The Takeaway

Vulture is faster (0.1s) but "dumb"—it missed 17% of the dead code and flagged used code as dead.

Skylos found 100% of the dead code with higher precision, taking ~1.6s to parse the full AST context.

Metric	Skylos	Vulture
True Positives Correctly found dead code	29 / 29	24 / 29
False Negatives Missed bugs (Lower is better)	0	5
Precision Accuracy of findings	70.7%	50.0%
Recall Detection rate	100%	82.8%
Execution Time	1.67s	0.10s

* Benchmark data collected Feb 2026 on Apple Silicon M3.

Integrate in Seconds

Build a secure DevSecOps pipeline in three steps.

Install CLI

$ pip install skylos

Or connect GitHub for automated PR scanning.

Run Analysis

$ skylos . --danger --quality --upload

Upload to the dashboard for gate status, suppressions, and history.Local only: skylos . --danger --quality

Fix & Gate

PR #142✓ Gate passed

Block risky merges automatically.

Frequently Asked Questions

How does Skylos detect hardcoded secrets?+

Skylos scans your codebase and git history using entropy analysis and pattern matching to find API keys, tokens, and passwords before they are pushed to production.

Why does Skylos take ~1.5s compared to Vulture?+

Vulture scans text (regex). Skylos scans logic (AST). We trade 1 second of computer time to save you hours of human time triage. We filter out false positives from FastAPI routes, Pydantic models, and Pytest fixtures automatically.

Is this a replacement for SonarQube or Snyk?+

Skylos is a lightweight, zero-config alternative focused specifically on Python. Unlike heavy enterprise SAST tools, Skylos runs in <3 seconds and is designed for immediate feedback in local CLI and PR checks.

Can I automate Python security checks in GitHub Actions?+

Yes. Skylos is designed for CI/CD. You can use it to gate pull requests, ensuring no dead code or security vulnerabilities merge into your main branch.