Launching October 13, 2026
Guardana

Guardana

Scan AI artifacts offline, probe live systems, and compare security runs with Guardana.

FreeCLIAISecurity1 impressionslaunches Oct 131 comment

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  • Konrad Karauda[maker]· 6h ago

    I built Guardana to give security and platform engineers a way to verify AI models and code completely offline. It scans artifacts, probes live endpoints, grades recordings, and diffs runs, outputting SARIF, JSON, JUnit or text. Let me know what you think and any improvements you’d suggest 😊

Scan AI artifacts offline, probe live systems, and compare security runs with Guardana. Guardana is an open-source AI security verification tool for security and platform engineers that checks model and code artifacts, live AI systems, and recorded runs, with scans that run fully offline. An offline starter: find a problem, fix it, and keep the evidence. Follow the first-run guide. By default the command above selects stable releases. To install or upgrade to a candidate, use pip install --upgrade --pre guardana-cli or follow the install guide. unpickling imports 1 non-allowlisted callable(s) (set 705e9da4c561): posix.system config.json names a Hub kernel repo transformers imports on load 12 finding(s); 19 rule(s) run, 0 skipped. 5 component(s) observed. → exit 1
  • Offline‑only security scans
  • No account or telemetry required
  • Scans model and code artifacts
  • Probes live endpoints and agents
  • Grades execution traces and diffs runs

Guardana is an open-source tool that scans AI model/code artifacts, probes live endpoints, grades recorded runs, and diffs security results.

for
Security and platform engineers building or operating AI systems.
pricing
open source
license
Apache-2.0
guardana/guardana 267 13Pythonupdated 6 hours ago
works withpipuvxGitHub ActionspytestlangchainPostgreSQL

Key features

8 features of Guardana
  • Offline Scan — Runs deterministic rule checks on model and code artifacts without sending data.
  • Live Probe — Tests running model endpoints or agents and records findings.
  • Grade Recorded Runs — Applies security rules to saved interactions without contacting the system.
  • Diff Comparisons — Compares two saved runs to see regressions or improvements.
  • Custom Policies — Define new rules in YAML or Python and package them as policy packs.
  • CI Integration — GitHub Action and pytest helper let you enforce checks in CI pipelines.
  • Multiple Output Formats — Exports results as SARIF, JSON, JUnit or plain text.
  • Optional Collector — Self-hosted PostgreSQL collector can store runs and evidence.

Use cases

  • Validate model files and code for supply-chain risks before release.
  • Continuously monitor a production endpoint for runtime attacks.
  • Compare security findings between two model versions to catch regressions.
  • Enforce custom security contracts in CI for AI-enabled applications.
  • Detect hard-coded secrets and unsafe deserialization in code bases.

Guardana vs alternatives

GuardanaTrivySemgrepSnykInfisical
Best forOffline AI security verificationContainer and code vulnerability scanningStatic analysis for code bugsDependency and container securitySecrets management
PricingOpen sourceFreeSubscriptionSubscriptionFree
DevHunt upvotes10000
LaunchedOct 2026————
  • Guardana vs Trivy: Trivy scans containers and code for vulnerabilities, but does not probe live AI endpoints or grade recordings.
  • Guardana vs Semgrep: Semgrep performs static code analysis, lacking offline AI artifact scans and runtime probing.
  • Guardana vs Snyk: Snyk focuses on dependencies and container security, not on AI model or endpoint verification.
  • Guardana vs Infisical: Infisical manages secrets, whereas Guardana checks for secret leaks within AI artifacts and runtime.

Guardana FAQ

Does Guardana send any data to external services?+

No. Scans run fully offline and only send data if you explicitly specify a reporter.

Do I need an account to use Guardana?+

No account or telemetry is required; the tool is Apache-2.0 licensed.

How can I add my own security rules?+

Use `guardana new-pack` or `guardana new-rule` to create YAML/Python policies that are validated by the tool.

Can Guardana be used in CI pipelines?+

Yes, via the Guardana GitHub Action or the `guardana.testing.assert_secure` helper in pytest.

What output formats are supported for findings?+

Findings can be exported as SARIF, JSON, JUnit, or plain-text reports.

Is there a way to store runs centrally?+

An optional self-hosted PostgreSQL collector can receive runs using the `--reporter` flag.

Summarized by DevHunt from guardana.dev · Oct 12, 2026. Details may change; check the official site.