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Skill scan report

vss-deploy-video-embedding

View on GitHub
35 Medium This skill sends sensitive values to an external host. Automated analysis flagged 1 additional risk pattern.

What this skill does

Deployment and operational integration of the VSS 3.2 GA RT-Embed Video Embedding microservice, including Docker Compose setup, GPU and storage prerequisites, REST API usage, and integration with Redi

github/nvidia - Data Exfiltration - 2.8k stars

ThreatsData Exfiltration Secret Leakage

Threat analysis

Data Exfiltration1 finding
Secret Leakage1 finding

Skill info

Namenvidia/vss-deploy-video-embedding
Registrygithub
Versiona9ea6f9
PURLpkg:github/NVIDIA/skills@a9ea6f9?skill=vss-deploy-video-embedding
Stars2.8k

Assessments (2)

Data Exfiltration1 finding HIGH
HIGH

Data Exfiltration via local-llm-review

SKILL.md

curl -fsS -X POST "$BASE_URL/v1/generate_video_embeddings" ... -d "{ \"id\": \"$FILE_ID\", \"model\": \"$MODEL_I" ..."
Secret Leakage1 finding MEDIUM
MEDIUM

Secret Leakage via local-llm-review

references/environment.md

NGC_API_KEY and HF_TOKEN are required for first-boot model fetches and to avoid rate-limit errors. These are sensitive credentials.

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How Anomity governs this at runtime

Scan-time vetting tells you what a skill says it will do. Anomity's Endpoint Sensor sees what agents actually do: it discovers skills alongside every other AI artifact on the endpoint, and runtime governance can allow, deny, or log the tool calls a skill triggers. Policy violations route to your SIEM, Slack, email, or Jira, backed by a queryable 90-day audit trail.

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Methodology and disputes

Every skill is assessed by the Anomity Skill Intelligence engine against its public source; findings indicate risk patterns, not confirmed exploitation. Maintainer of vss-deploy-video-embedding? Report an issue or request a rescan.

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