airunway-aks-setup
Verdict safe, but 1 finding (1 medium), mainly data exfiltration. Most recent scan 2026-10-22.
Second scanner: NVIDIA SkillSpector
Independent static run, no language model, over the same files as the Cisco scan above. How the two scanners compare across the whole corpus: Two scanners, one corpus.
What this skill does
Set up AI Runway on AKS — from bare cluster to running model. Covers cluster verification, controller install, GPU assessment, provider setup, and first deployment. WHEN: \"setup AI Runway\", \"onboard AKS cluster\", \"install AI Runway\", \"airunway setup\", \"deploy model to AKS\", \"GPU inference on AKS\", \"KAITO setup on AKS\", \"run LLM on AKS\", \"vLLM on AKS\", \"set up model serving on AKS\", \"AI Runway controller\".
- Package
- 12 files, 26 KB
- SKILL.md
- 574 words, 9 sections
- Code
- None. Instructions only.
- License
- MIT
SKILL.md covers: AI Runway AKS Setup · Prerequisites · Quick Reference · When to Use This Skill · GPU setup versus Day-2 incidents · MCP Tools · Rules · Steps · Error Handling
Findings
MEDIUM Bash: tainted data flows to dangerous sink Data Exfiltrationbehavioral
Variable $ENDPOINT (line 1) flows to `curl` at line 6.
references/steps/step-6-summary.md:24
curl -X POST "${ENDPOINT}/v1/chat/completions" \What is in the package
| File | Kind | Size |
|---|---|---|
SKILL.md | doc | 4.4 KB |
references/gpu-profiles.md | doc | 2.5 KB |
references/model-sizing.md | doc | 1.8 KB |
references/optional-gpu-day2.md | doc | 1.1 KB |
references/powershell-notes.md | doc | 3.1 KB |
references/troubleshooting.md | doc | 1.5 KB |
references/steps/step-1-verify.md | doc | 1.9 KB |
references/steps/step-2-controller.md | doc | 1.0 KB |
references/steps/step-3-gpu.md | doc | 834 B |
references/steps/step-4-provider.md | doc | 2.0 KB |
references/steps/step-5-deploy.md | doc | 3.6 KB |
references/steps/step-6-summary.md | doc | 1.7 KB |
Environment variables referenced
ENDPOINT SERVICE_PORT
Package contents recorded 2026-10-22 at commit f49ac319a7d3. The scan above ran against the version current at scan time; the two can differ if the skill has since been updated.
What we checked
- Static analyzer. Pattern rules over SKILL.md and bundled files: known-bad commands, exfiltration URLs, secrets, obfuscation.
- Bytecode analyzer.
- Pipeline analyzer.
- Correlation analyzer.
- Behavioral analyzer. Checks what the skill asks the agent to do against what its description claims it does.
- Trigger analyzer. Looks for instructions that fire on conditions the user did not ask for.
What we did not check
- Runtime behaviour. The skill was not executed; findings come from reading its files.
- Anything fetched at install or run time, including remote scripts, package dependencies, and URLs the skill tells the agent to open.
- Content the analyzers cannot read: images, binaries, and some non-English text.
- Known scanner bypass classes. See the methodology and limitations page.
Scan history
| Date | Verdict | Findings | Change | Analyzers | Raw |
|---|---|---|---|---|---|
| SAFE | 1 | = | static bytecode pipeline correlation behavioral trigger | JSON | |
| SAFE | 1 | first scan | static bytecode pipeline correlation behavioral trigger | JSON |
Sources
- Repository: https://github.com/microsoft/azure-skills
- Raw scan result: microsoft-azure-skills-skills-airunway-aks-setup-scan.json
- Badge for your README:
- Request a re-scan