DeepSource is a code quality and security platform with 20+ analyzers covering SAST, SCA, secrets detection, and code coverage. It integrates natively with GitHub, GitLab, Bitbucket, and Azure DevOps to analyze every commit and pull request without CI configuration.
Founded in 2018 in San Francisco, DeepSource is used by 6,000+ companies including NASA, Ancestry, and Babbel. The platform is SOC 2 Type II certified. Backed by Y Combinator and 645 Ventures.
What is DeepSource?
DeepSource runs static analysis on every commit and pull request. According to NIST’s guidelines on secure software development, automated analysis on every code change catches vulnerabilities before they accumulate.
DeepSource scans for security vulnerabilities, code quality issues, duplicated code, and hardcoded secrets. The platform also provides SCA for dependency vulnerabilities and code coverage tracking.
The standout feature is Autofix AI, which generates fixes for detected issues using LLMs. The legacy deterministic Autofix handled about 30% of issues. Autofix AI expands that to nearly all issues by analyzing surrounding context, imports, and project patterns.
Key features
Security analysis
DeepSource detects security vulnerabilities across its supported languages. The SCA module scans dependencies for known vulnerabilities using reachability analysis to determine whether your code actually calls the vulnerable function.
For JavaScript and Python, SCA includes full reachability analysis and automated remediation. For Go, Rust, Java, C#, PHP, Ruby, and Kotlin, it provides vulnerability scanning.
Secrets detection
The secrets analyzer uses a two-stage approach: fast pattern matching identifies potential secrets, then AI-powered classification distinguishes real credentials from false positives.
DeepSource reports 97% precision, 96.3% recall, and a 93% reduction in false positives compared to pattern-only detection. The classification is powered by Narada, an open-source secrets classification model.
Code quality and coverage
The platform tracks code complexity, duplication, and style violations. Code coverage integration supports Go, Rust, Java, Scala, C#, JavaScript, PHP, Python, Ruby, C/C++, Swift, and Kotlin. 17+ code formatters (Black, Prettier, Rustfmt, RuboCop, etc.) can auto-format code.
Configuration
DeepSource uses a .deepsource.toml configuration file in the repository root:
version = 1
[[analyzers]]
name = "python"
enabled = true
[analyzers.meta]
runtime_version = "3.x.x"
[[analyzers]]
name = "secrets"
enabled = true
Integrations
GitHub
GitLab
Bitbucket Cloud
Bitbucket Data Center
Azure DevOps
Slack
Jira Cloud
VantaGetting started
.deepsource.toml configuration file via pull request.Pricing
| Plan | Price | Key limits |
|---|---|---|
| Free | $0/month | 1 private repo, 3 members, 500 analysis runs, 50 Autofix runs |
| Starter | $8/seat/month | Unlimited repos and analysis, 500 Autofix runs |
| Business | $24/seat/month | Unlimited Autofix, monorepo support, secrets detection, audit logs, 2-year retention |
| Enterprise | Custom | Self-hosted, SSO, dedicated account manager |
SCA is priced separately at $8/target/month (annual). Annual billing saves 20%.
When to use DeepSource
DeepSource works well for teams that want quick setup with no CI configuration overhead. The native Git platform integration means analysis starts within minutes.
Autofix AI is the main differentiator — instead of just flagging issues, it generates fixes that developers can review and merge.
Teams with strict compliance requirements may need to supplement DeepSource with additional tools, since its focus is developer experience over comprehensive vulnerability catalogs.
Self-hosted deployment is available on the Enterprise plan for organizations that need on-premises control. For more options, see the open-source SAST tools guide.
DeepSource alternatives
The closest substitutes for DeepSource depend on which slice of its scope matters most — security, code quality, or developer-experience speed.
- SonarQube and SonarCloud — the canonical code-quality-plus-security platform. Deeper rule depth and more languages than DeepSource, with a heavier CI footprint. Pick this when you already standardise on Sonar Quality Gates.
- Codacy — a direct DeepSource competitor on the developer-experience side, also Git-native, with broad linter aggregation. Closer to DeepSource on autofix UX, weaker on dataflow-aware security checks.
- Snyk Code — heavier on security depth, lighter on style and quality. A fit when SAST findings need to live alongside SCA, container, and IaC scanning in the same dashboard.
- Semgrep — rule-driven SAST with a free open-source engine and writable custom rules. Picked when teams want to author org-specific patterns instead of running a fixed rule pack.
- GitHub Advanced Security — CodeQL-powered SAST bundled with GitHub. A fit when the codebase already lives on GitHub and a single vendor is preferred.
For a fuller side-by-side, see the SAST tools hub.
Reed Wilson, Engineering Manager at Ancestry, states: “With DeepSource’s pull request analysis workflow, everything is integrated — right at the point of merge, and this has been a game changer for us.”
