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This version passed the hardening gate. Hardening applied 1 targeted change and preserved all other text. Classified findings before hardening: 1. Classified findings closed: 0. Classified findings remaining: 1. Unclassified scanner findings remaining: 0. Review findings closed: 1. Review findings remaining: 12.
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Expand | File | Group | Subtype | Severity | Status |
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BENCHMARK.md | Sensitive Data & Secret Exposure | Agent snooping | Medium | Open |
1 finding
Use the retriever CLI. Prefer it over hand-built retrieval
code.
Create a project-local Python environment:
Install the package variant required by the workflow:
Do not clone NeMo Retriever or install from a Git URL.
Build a local index:
Query it:
Use retriever ingest batch only for an explicitly requested Ray batch run.
Use these forms for an already deployed Retriever service:
Set NEMO_RETRIEVER_API_TOKEN when the service requires Bearer authentication.
Do not pass local LanceDB flags to the service commands.
retriever ingest --help, retriever query --help, or the relevant
batch / service help for options not shown here.Get started with chainctlchainctl skill install public/nvidia/nemo-retriever:latest
Bring Chainguard's hardening pipeline to your first-party skills — custom rulesets, automated remediation, full audit trail.
skills.chainreg.biz/public/github.com/nvidia/skills/nemo-retriever:latest
Apache-2.0
BENCHMARK.md
HARDENING.md
SKILL.md
evals/evals.json
skill-card.md
skill.oms.sig