Daytona
Website
Daytona is a Secure and Elastic Infrastructure for Running AI-Generated Code
Is Daytona safe? Thin or incomplete trust evidence. Review carefully before production use.
Compare Daytona
How does it stack up against its Sandboxes & Runtimes neighbours?
Pick any agent to compare →In detail: Daytona scores 54.0/100 (Grade C), ranked #840 of 1371 tracked open-source AI agent projects, on evidence coverage A (4 of 5 independent signal types). The public evidence: no package-provenance attestation found; OSSF Scorecard rates its supply-chain practices 5.0/10; 99% of recent commits are signed; last pushed 2026-07-24. Every point is earned from checkable signals — never paid placement. How scoring works →
How Daytona could raise its score
Each line changes one public signal and recomputes with the live scoring function. The gains don't add up exactly, because the score is capped near the top.
- Publish build provenance for its packagesPyPI Trusted Publishing attestations +14.7 → 68.7 B · #6 of 11
- Declare an open-source licenseno license GitHub recognises +8.6 → 62.6 C · #6 of 11
- Raise the OSSF Scorecard from 5.0 to 9.0lowest checks: CII-Best-Practices 0, Fuzzing 0, License 0 +8.5 → 62.5 C · #6 of 11
Chain of custody
Scanners check what the code says. This traces who ships Daytona and whether that has changed: from the source repository, through how changes are reviewed and released, to the package you install. These are the checks for OWASP ASI04 Agentic Supply Chain Vulnerabilities.
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Source Signed
github.com/daytonaio/daytona, last pushed 2026-07-24. 99% of the last 100 commits carry a verified signature, so changes trace to a verified account.
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Review and release Mixed
OpenSSF Scorecard rates the repository's practices 5.0/10 (scanned Oct 9, 2026). The checks that decide who can get a change released:
- Code Review8
- Branch Protection1
- Signed Releases0
- Dangerous Workflown/a
- Token Permissionsn/a
- Pinned Dependenciesn/a
All 18 Scorecard checks
Binary-Artifacts 10Branch-Protection 1CI-Tests 8CII-Best-Practices 0Code-Review 8Contributors 10Dangerous-Workflow -1Dependency-Update-Tool 10Fuzzing 0License 0Maintained 0Packaging -1Pinned-Dependencies -1SAST 0Security-Policy 10Signed-Releases 0Token-Permissions -1Vulnerabilities 10 -
Published packages Not linked
- PyPI daytona-sdk Source link isn't a GitHub repo No build attestation
Without a build attestation, nothing proves the published files were built from this repository.
Changes to this chain
- 2026-09-02 License classification changed from open to unlicensed
Evidence behind this score
Coverage A: 4 of 5 independent evidence types found.
- GitHub repository data
- Package downloads
- Supply-chain checks
- Public actions (missing)
- Community mentions
Verify this score yourself
Every build re-issues Daytona’s score as an Ed25519-signed credential, valid for 7 days. You can check it offline against HVTracker’s published key; if anyone changes a number after signing, verification fails.
What this score doesn’t check
It covers who ships the code, not what the code does. It doesn’t read tool descriptions or prompts for injected instructions, watch runtime behaviour, or find bugs nobody has disclosed yet. For that, run a content scanner before you connect it, such as Cisco MCP Scanner or Snyk Agent Scan.
How Daytona compares in Sandboxes & Runtimes
- #7 Container Use 55.8 +1.8
- #8 Agent Infra Sandbox 54.6 +0.6
- #9 Daytona 54.0 this agent
- #10 Zeroboot 33.5 −20.5
- #11 Rivet Agents 22.4 −31.6
Bars show each HVTrust score; the tick marks Daytona’s 54.0.
Where the 54.0 comes from
HVTrust dimensions vs the Sandboxes & Runtimes average
54.0 / 100 · 100.0% confidenceDaytona Sandboxes & Runtimes average (11 agents)
Quick Trust Read
How to read this: HVTrust (0–100) weighs supply-chain signals (provenance, OSSF Scorecard, signed commits, open license) alongside real-world adoption. Grade C reflects the trust score band: A ≥ 80, B ≥ 65, C ≥ 50, D < 50. Evidence coverage A is separate — it grades how many independent signal types back the score (4 of 5), so a high score on thin evidence stays visible. Full methodology →
Rank Trend
Activity & Reach
Analysis
Activity Inputs
60.8 / 100Common questions about Daytona
Does Daytona publish package provenance?
Does Daytona have an OpenSSF Scorecard?
Is Daytona actively maintained?
What license does Daytona use?
Are Daytona's commits signed?
Not a safety endorsement. HVTracker describes what public signals show, not whether a project is safe for your use case. Run your own security review before adopting in production.
AI agent surface
MCP, providers, tool surface
These runtime-trust fields — detected from public repo docs and manifests — contribute a bounded adjustment to this project's HVTrust score alongside supply-chain evidence. The exact values each field can add or subtract are documented in the methodology → Compare this surface across every listed agent in the capability matrix →
- MCP signal live
- External deps live
- Tool / plugin surface live
- Package provenance drift live
Maintain Daytona?
For maintainers
HVTrust scores Daytona from public signals only — we never contact maintainers first. If a signal is wrong, stale, or missing (provenance you publish, a Scorecard you run, signed releases), tell us and we'll review it. Corrections are public and tracked on GitHub.
Reputation Timeline
Signal history
Embed Badge Badge guide for maintainers →
For maintainers
[](https://hvtracker.net/agents/daytona)
<a href="https://hvtracker.net/agents/daytona"><img src="https://hvtracker.net/badge/daytona.svg" alt="HVTrust"></a>
Other agents in Sandboxes & Runtimes
GitHub REST API (repo, commits, stars, forks, license) · PyPI / pypistats (downloads, provenance) · OpenSSF Scorecard CLI · Algolia HN Search API
Each agent's signals refresh once daily across 6 staggered batches. Methodology v4.4 · Raw JSON