Snyk is an application security platform for dependencies, containers, infrastructure as code, and source code. It combines its own vulnerability intelligence with CI, repository, and enterprise integrations.

Skylos is a local-first, open-source static analysis tool. It recognizes Python, JavaScript and TypeScript, Go, Java, Kotlin, PHP, Rust, Dart, C#, Shell, and deployment configuration, with analysis depth varying by language. It combines security scanning, repository-level dead code analysis, dependency CVE checks, and AI-specific change review. Core static analysis runs locally without signup.

These tools solve overlapping but different problems. This page is an honest comparison of where each one is stronger and where they complement each other.

The short version

SnykSkylos
Best forBroad SCA, container, IaC, and enterprise AppSec workflowsLocal-first repository analysis, unused-code liveness, and changed-code guardrails
LanguagesBroad language coverage across productsPython, JS/TS, Go, Java, Kotlin, PHP, Rust, Dart, C#, and Shell; depth varies
Dependency scanning (SCA)Yes, with broad ecosystem and vulnerability-intelligence coverageYes, OSV-backed for supported exact manifest entries and uv/npm lockfiles
Container scanningYes, including image and base-image analysisNo image vulnerability scan; checks Dockerfiles and selected deployment configuration
IaC scanningYes (including Terraform, CloudFormation, Kubernetes, and ARM)Selected Docker, Compose, Kubernetes, and CI configuration checks; no general Terraform engine
Source code SASTYes (Snyk Code)Yes; rule and data-flow depth varies by language
Dead code detectionSome coding and dead-branch issues in Snyk CodeDedicated unused-symbol graph with framework liveness and transitive propagation
Changed-code security reviewPR checks and agentic security scansDiff-aware checks for removed controls and changed-line regressions
AI and agent securitySnyk Studio, AIBOM, and broader agent-security productsGit provenance plus local verify and defend evidence workflows
Code quality analysisSelected coding issues in Snyk CodeComplexity, coupling, cohesion, duplication, and maintainability rules
Framework awarenessRule-dependentBuilt-in (Django, Flask, FastAPI, Pydantic, pytest)
MCP serverYes, through Snyk StudioYes, through the local Skylos MCP server
DeploymentSaaS by default; a deprecated Local Engine remains for existing customersCore scan is local; Cloud uploads, AI providers, and OSV lookups are explicit networked features
PricingFree / Team (from $25/dev/month) / Ignite (from $1,260/dev/year) / Enterprise (custom)Free (Apache 2.0) / Optional credit packs for cloud features
CI/CD setupGuided onboarding and integrationsskylos cicd init generates a GitHub Actions workflow

Where Snyk is stronger

Dependency scanning (SCA)

Dependency and supply-chain analysis is one of Snyk's central product areas.

Snyk maintains its own vulnerability intelligence and supports a much broader set of package managers and enterprise dependency workflows. When you run snyk test, it analyzes supported dependency manifests and lockfiles for known vulnerabilities and license issues.

Skylos now provides OSV-backed SCA for supported exact versions. It reads uv.lock and package-lock.json, plus exact entries in requirements.txt, pyproject.toml, package.json, and go.mod. It does not resolve manifest ranges, cover every package manager, scan licenses, or maintain a proprietary vulnerability database. Snyk remains the stronger choice when broad software-composition coverage is the main requirement.

Container scanning

Snyk Container scans Docker images, identifies vulnerable base image layers, and recommends safer base images. This is a specialized capability that Skylos does not attempt.

If you ship containers, Snyk Container is genuinely useful and there is no Skylos equivalent.

Infrastructure as Code scanning

Snyk IaC scans Terraform, CloudFormation, Kubernetes manifests, and ARM templates for misconfigurations. Skylos checks selected Docker, Compose, Kubernetes, CI, and deployment patterns, but it does not provide a general Terraform, CloudFormation, or ARM analysis engine.

Multi-language support

Snyk documents broad language coverage across its products. If your organization has Java, .NET, Ruby, and Python services, Snyk can provide one security platform across them.

Skylos recognizes Python, JavaScript and TypeScript, Go, Java, Kotlin, PHP, Rust, Dart, C#, and Shell, but it does not promise equal rule depth for each language. Snyk provides broader and more mature coverage across its product suite, especially when one program must cover many ecosystems consistently.

Enterprise features

Snyk offers team management, RBAC, SSO/SAML, Jira integration, compliance reporting, and priority scoring across an organization's portfolio. Those features are designed for formal AppSec programs.

Skylos Cloud now has workspace roles, team workflows, policy and exception governance, audit activity, and compliance-report surfaces. It still does not match the breadth of Snyk's enterprise platform, SSO options, risk portfolio, or integration ecosystem.

Vulnerability database depth

Snyk's vulnerability intelligence is maintained by a dedicated security research team and adds proprietary research to its package coverage.

Skylos queries the public OSV service for supported dependency inventories. That is useful for local and CI checks, but it is narrower than Snyk's package-manager coverage, proprietary research, license analysis, and supply-chain platform.

Where Skylos is stronger

Dead code detection

Snyk Code documents some coding issues, including dead code and predefined branches. Skylos puts more emphasis on repository-wide unused-symbol reasoning: definitions, imports, callers, framework entrypoints, and transitive liveness are part of the main scan result.

Skylos detects unused functions, classes, imports, variables, and parameters. It also performs transitive dead code propagation: if function A is dead and it is the only caller of function B, Skylos marks B as dead too.

def process_legacy_order(order_id):       # dead -- nothing calls this
    validated = _validate_order(order_id)  # also dead (transitive)
    _notify_warehouse(validated)           # also dead (transitive)

Dead code is not just a quality concern. Code that is no longer reachable can still distract reviewers and retain obsolete dependencies or security-sensitive logic. Teams should compare both tools on their own frameworks because the products define and report dead code differently.

Diff-aware AI regression detection

One relevant difference for teams using AI coding assistants is changed-code regression detection.

A broad refactor can silently remove a security control. An @login_required decorator disappears, a CSRF check gets dropped, or rate limiting is removed during a cleanup.

Snyk provides PR checks and agentic security scans for issues in proposed code. Its public Snyk Code documentation does not describe the same removed-control contracts Skylos uses to compare a trusted base revision with the checked-out change.

Skylos recognizes supported patterns grouped into 11 control types when they disappear or are weakened in a diff:

  • Authentication checks and decorators
  • CSRF protection
  • TLS verification
  • Cryptographic downgrades
  • Rate limiting
  • Input validation
  • Security headers and related middleware
  • Encryption calls or key setup
  • Audit logging
  • Output sanitization
  • Permission checks
skylos . --diff-base origin/main --diff origin/main --quality

This catches a specific regression class that current-state scanning can miss: an existing control disappearing during refactoring.

AI provenance tracking

Skylos uses git commit authors, co-author trailers, and commit-message evidence to estimate whether changed code came from a person or a named coding agent. It reports confidence because repositories do not always preserve that evidence.

Snyk offers AIBOM and agent-security capabilities. Skylos's narrower provenance workflow uses git evidence to label changed files and findings as human- or AI-authored when that evidence is available; low-confidence attribution remains visible as uncertain.

AI defense scanning (LLM application security)

If you are building applications that integrate LLMs (calling OpenAI, Anthropic, or running RAG pipelines), Skylos has dedicated scanning for LLM-specific risks:

skylos defend .

This runs the applicable checks from a 13-plugin guardrail set, with selected mappings to OWASP LLM and agentic-risk categories:

  • Raw input reaching prompt construction without intermediate processing
  • Missing delimiters around user or retrieved RAG context
  • Output PII filtering
  • Cost controls
  • Rate limiting on LLM calls

Snyk now has Snyk Studio and additional agent-security products. Skylos's defend command is a narrower local static check that emits an evidence report for guardrails around LLM calls, RAG pipelines, agents, and MCP tools.

Local-first core analysis

Snyk Code is primarily delivered as a cloud service. Snyk documents a no-code-upload Local Engine for existing customers, but that engine is deprecated and carries substantial deployment requirements.

Skylos core static analysis runs locally. Source is not uploaded unless a user chooses a networked workflow. Cloud reports may include findings, paths, line numbers, and optional snippets; configured AI providers may receive selected context; SCA sends package names, ecosystems, and exact versions to OSV, not source code.

Open source and free

Skylos is Apache 2.0 licensed. Its local CLI scans, dead code analysis, AI defense checks, and CI workflow generation have no per-scan quota. Optional Cloud and LLM-powered workflows are separate services.

Snyk's current Free plan includes limited SCA, SAST, IaC, and container tests. Its Team plan starts at $25 per contributing developer each month, with higher tiers for additional governance and platform features.

For individuals, small teams, and open-source projects, the cost difference is significant.

Local verification and MCP workflows

Skylos includes an MCP (Model Context Protocol) server that lets compatible AI agents invoke its analysis workflows:

python -m skylos_mcp.server

This lets AI coding agents like Claude Code check output for security issues, dead code, and regressions before committing.

Snyk also provides an MCP server through Snyk Studio. The difference is scope and deployment: Snyk exposes its broader security platform to agents, while Skylos exposes its local repository scan, change verification, and guardrail evidence workflows.

Framework-aware analysis

Snyk Code's SAST capabilities depend on the rules available for your framework. Coverage varies.

Skylos has built-in framework visitors for Django, Flask, FastAPI, Pydantic, pytest, Celery, and Click. It understands that @app.route handlers are called via HTTP, @pytest.fixture functions are called by the test runner, and Pydantic model_validator methods are called during validation.

These visitors keep recognized framework entry points from being reported as unused without extra configuration:

@app.route("/api/users")        # Skylos: alive (Flask route handler)
def get_users():
    return jsonify(users)

@pytest.fixture
def db():                        # Skylos: alive (pytest fixture)
    return create_engine()

Generated CI/CD setup

skylos cicd init

This generates a GitHub Actions workflow with PR scanning, annotations, and quality gates. The local gate needs no Skylos account; optional Cloud upload requires a workspace connection.

A Snyk CLI or GitHub Action scan requires a Snyk account and token. Repository integration and monitored-project setup depend on the Snyk workflow a team chooses.

Detection comparison: what each tool catches

Known dependency vulnerabilities

Snyk: Yes. This is what Snyk does best.

snyk test
# Found 3 vulnerabilities in 47 dependencies
# HIGH: CVE-2024-XXXXX in requests 2.28.0

Skylos: Yes, for supported exact dependency inventories through OSV. Coverage currently includes uv.lock, package-lock.json, and exact versions in selected Python, npm, and Go manifests. It is not a replacement for Snyk's broader package, license, container, and supply-chain coverage.

SQL injection in source code

Snyk Code:

# Snyk Code can flag this (depending on rules/language support)
query = f"SELECT * FROM users WHERE id = {user_id}"
cursor.execute(query)

Skylos:

# Skylos flags this (SKY-D211: SQL injection via taint analysis)
query = f"SELECT * FROM users WHERE id = {request.args['id']}"
cursor.execute(query)

# Skylos does NOT flag this (hardcoded, not user-controlled)
cursor.execute("SELECT * FROM users WHERE active = 1")

Both tools can catch SQL injection in source code. In this direct example, Skylos propagates the recognized request value through local expressions and does not add a tainted-SQL finding for the hardcoded query. Its Python model is conservative around ordinary function parameters and does not prove an interprocedural request path.

Removed security controls

Snyk: Snyk can scan pull requests for issues in proposed code. In the public documentation reviewed for this comparison, Snyk Code does not describe an equivalent base-versus-head contract for named controls that disappeared.

Skylos:

skylos . --diff-base origin/main --diff origin/main --quality --format json

This is useful when a team wants the CI result to identify a removed control directly, rather than relying only on whether the resulting code matches a current-state vulnerability rule. Matching results use SKY-L021, HIGH severity, and name the modeled control that disappeared.

Dead code

Snyk: Snyk Code documents selected coding issues including dead code and predefined branches.

Skylos:

skylos src/
# DEAD: process_refund() in payments.py:34 (0 references)
# DEAD: _validate_refund() in payments.py:52 (only caller is dead)
# DEAD: OldPaymentProcessor class in legacy.py:12 (0 references)

When to use Snyk

  • You need dependency scanning (SCA) across your package ecosystem
  • You need container scanning for Docker images
  • You need IaC scanning for Terraform or Kubernetes
  • You need broad, consistent multi-language coverage across an AppSec program
  • You are running a formal AppSec program with compliance requirements
  • You need enterprise features (SSO, RBAC, Jira integration, compliance dashboards)
  • Your primary concern is known CVEs in third-party packages

When to use Skylos

  • You need local-first repository analysis, especially for dynamic Python and framework-heavy code
  • You want dead code detection alongside security scanning
  • Your team uses AI coding assistants and you need to catch removed security controls
  • You are building LLM-integrated applications and need AI defense scanning
  • You want local core analysis with no signup and explicit control over Cloud, AI, and OSV network features
  • You want free, open-source local scans without a per-scan quota
  • You want a generated GitHub Actions workflow without a hosted onboarding step
  • You want MCP integration so agents can invoke local analysis workflows

When to use both

The tools can run together when a team needs both scopes.

Use Snyk for its broad platform: package and license intelligence, container images, IaC, and enterprise AppSec management.

Use Skylos for its repository-focused workflow: unused-symbol liveness, changed-code security contracts, local quality analysis, git provenance, and local agent verification. Its SCA can provide a second OSV-backed signal for supported inventories.

Their SAST and SCA coverage overlaps, so define which result owns each gate and deduplicate findings. A combined CI setup can, for example, report:

  • Snyk: a known vulnerability in a pinned dependency
  • Skylos: a modeled auth decorator removed in this diff, plus unused-symbol candidates

This combines complementary evidence from both tools.

Quick start

Snyk

npm install -g snyk
snyk auth
snyk test
snyk code test

Skylos

pip install skylos
skylos src/ --danger --quality

Final thoughts

Snyk is a broader, more mature security platform. It covers package ecosystems, licenses, container images, IaC, and enterprise AppSec management more comprehensively than Skylos.

Skylos is more focused on local repository and pull-request analysis: framework-aware liveness, diff-aware security contracts, quality signals, agent verification, and a bounded OSV-backed dependency scan. Its language support is broader than Python, but analysis depth varies by language.

The practical recommendation is to test each tool on the exact repositories and gates you plan to enforce. Teams can use Snyk for broad AppSec coverage and Skylos for local repository evidence without treating either product as universally stronger.

Try Skylos

If you want local dead-code and security analysis plus changed-code regression checks:

pip install skylos
skylos src/ --diff-base origin/main --diff origin/main --danger --quality

The local scan needs no signup or Skylos API key. View on PyPI | Read the docs

Comparison facts were rechecked on September 15, 2026 against Snyk's supported-language matrix, Snyk Code documentation, Snyk Container documentation, Snyk IaC documentation, Snyk's vulnerability-database documentation, Snyk's Local Engine notice, Snyk Studio documentation, Snyk pricing, Skylos dependency-scanning documentation, and the Skylos MCP setup guide.

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