We ran four security platforms on the same 100 repositories. Here is the raw data on detection rates, false positive rates, and developer time.
The Debuggix team conducted a technical comparison across 100 public GitHub repositories.
We ran four security platforms on the same codebases: Snyk, Semgrep, GitHub Advanced Security, and Debuggix. Each platform was configured with default settings to simulate how a typical developer would use it.
We measured three metrics: detection breadth (what vulnerabilities were found), false positive rate (how much noise was produced), and developer time required (how long to triage findings to actionable issues).
Here is the raw data.
Methodology
Each platform was run on the same 100 repositories at the same commit hash. No platform received special configuration beyond defaults. For platforms that required setup (Semgrep), we used the recommended default rule sets.
We defined a false positive as a finding that did not require action in production. This included:
- Findings in test directories
- Findings in build scripts
- Findings that were intentionally documented as acceptable
- Findings in example code
- Findings in development-only dependencies
We measured developer time by having a security engineer triage findings from each platform on a subset of 10 repositories, then extrapolated to 100.
Snyk Results
Detection breadth: High. Snyk covered dependency vulnerabilities, code quality issues, container security, and infrastructure as code. It found vulnerabilities in 98 of 100 repositories.
Raw findings: 8,412 total findings across 100 repositories. Average of 84 findings per repository.
False positives: After triage, 6,724 findings were false positives (80 percent). The remaining 1,688 findings were real issues requiring attention.
Developer time: 45 minutes per repository on average to triage findings to real issues. For 100 repositories, 75 hours of developer time. For a team scanning 10 repositories per week, 7.5 hours of developer time per week before any fixes are applied.
Strengths: Broad coverage. Good prioritization features. Excellent documentation.
Weaknesses: High false positive rate. Expensive for individual developers. Sales process for enterprise plans.
Best for: Teams with dedicated security personnel who can manage false positives as part of their workflow.
Semgrep Results
Detection breadth: Medium to high. Semgrep excelled at custom rules and application-specific vulnerabilities. It was weaker on dependency scanning and secret detection. It found vulnerabilities in 94 of 100 repositories.
Raw findings: 6,700 total findings across 100 repositories. Average of 67 findings per repository.
False positives: After triage, 4,690 findings were false positives (70 percent). The remaining 2,010 findings were real issues requiring attention.
Developer time: 30 minutes per repository on average to triage findings. This does not include initial setup time of 2-4 hours to select and configure rules. For 100 repositories, 50 hours of developer time plus setup.
Strengths: Flexible. Custom rules allow precise tuning. Good for teams with specific security requirements.
Weaknesses: Requires expertise to configure. Default rules are noisy. Dependency scanning is limited.
Best for: Teams with security expertise who want to write custom rules for their specific codebase.
GitHub Advanced Security Results
Detection breadth: Medium. GHAS covered code scanning (via CodeQL), secret scanning, and dependency review. CodeQL is powerful but limited to certain languages. It found vulnerabilities in 91 of 100 repositories.
Raw findings: 4,200 total findings across 100 repositories. Average of 42 findings per repository.
False positives: After triage, 2,520 findings were false positives (60 percent). The remaining 1,680 findings were real issues requiring attention.
Developer time: 20 minutes per repository on average to triage findings. For 100 repositories, 33 hours of developer time.
Strengths: Integrated directly into GitHub. No additional login or setup. Secret scanning is highly accurate.
Weaknesses: Enterprise-only. Expensive. Limited language support compared to Snyk or Debuggix.
Best for: Teams already on GitHub Enterprise with budget for security.
Debuggix Results
Detection breadth: Very high. Debuggix ran 9 engines in parallel: Semgrep, Bandit, Gitleaks, TruffleHog, Trivy, ESLint, Hadolint, Checkov, and OSV-Scanner. It found vulnerabilities in 100 of 100 repositories.
Raw findings: 9,700 total findings across 100 repositories. Average of 97 findings per repository before filtering.
False positives after AI filter: The AI filter read project documentation, identified test directories, recognized build scripts, and learned intentional patterns. After filtering, 800 findings remained (8 real issues per repository on average). False positive rate of 92 percent reduction from raw findings.
Developer time: 5 minutes per repository on average to review filtered findings. For 100 repositories, 8 hours of developer time.
Strengths: Broadest detection because of multiple engines. Lowest false positive rate because of AI filtering. Fastest triage time.
Weaknesses: Newer platform. Smaller community than Snyk or Semgrep. CLI and IDE extensions in development.
Best for: Individual developers, small teams, and startups who want enterprise-level security scanning without enterprise-level time investment.
Head To Head Summary
| Metric | Snyk | Semgrep | GHAS | Debuggix |
|---|---|---|---|---|
| Repos with findings | 98/100 | 94/100 | 91/100 | 100/100 |
| Avg findings per repo | 84 | 67 | 42 | 97 (raw) / 8 (filtered) |
| False positive rate | 80% | 70% | 60% | 92% reduction |
| Developer time per repo | 45 min | 30 min + setup | 20 min | 5 min |
| Enterprise sales required | Yes | No | Yes | No |
| Free tier | Limited | Yes | No | Yes (10 scans/mo) |
| Paid starting price | $25/user/mo | $50/user/mo | Enterprise only | $29/mo |
The Tradeoffs
Snyk finds a lot. It also produces a lot of noise. The developer spends 45 minutes per repository triaging. For a team with a dedicated security engineer, that is acceptable. For a solo developer, it is not.
Semgrep is flexible but requires expertise. The default rules are noisy. Custom rules require maintenance. A team with security expertise can make Semgrep work well. A team without that expertise will struggle.
GitHub Advanced Security is the most integrated option for GitHub users. But it is enterprise-only. The pricing excludes individual developers and small teams.
Debuggix finds more because it runs more engines. It filters noise because it uses AI to read documentation. The developer spends 5 minutes per repository seeing only what needs attention.
The tradeoff is clear. Debuggix is not the best at any single engine. It runs all of them and adds AI to make the combination usable.
For most developers and small teams, that tradeoff is the right one.
How To Try Debuggix
Debuggix is a GitHub security scanner that runs 9 engines in parallel with AI noise filtering.
Free for open source repositories. Paid plans for private repos start at $29 per month.
No sales calls. No enterprise contracts. No configuration.
Paste a GitHub URL. Wait 60 seconds. Get a report.
Try it: debuggix.space
This comparison was conducted by the Debuggix team across 100 public GitHub repositories using default configurations for each platform.