Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add BagelHole/DevOps-Security-Agent-Skills --skill model-supply-chain-securitygit clone --depth 1 https://github.com/BagelHole/DevOps-Security-Agent-SkillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/bagelhole/devops-security-agent-skills/model-supply-chain-security)<a href="https://agentmods.dev/skills/bagelhole/devops-security-agent-skills/model-supply-chain-security"><img src="https://agentmods.dev/badge/skills/bagelhole/devops-security-agent-skills/model-supply-chain-security/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/bagelhole/devops-security-agent-skills/model-supply-chain-security"><img src="https://agentmods.dev/badge/skills/bagelhole/devops-security-agent-skills/model-supply-chain-security.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00032 | $0.03096 |
| Opus 5 | $0.00016 | $0.01548 |
| Sonnet 5 | $0.00006 | $0.00619 |
| Haiku 4.5 | $0.00003 | $0.00310 |
Grade A, and why
model-supply-chain-security scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
result = subprocess.run( How it starts
The opening of the file, as written. The whole thing — 403 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Model Supply Chain Security
Protect models and inference components from tampering, dependency compromise, and untrusted artifact promotion.
When to Use This Skill
Use this skill when:
- Pulling pretrained models from public registries (Hugging Face, TensorFlow Hub)
- Building model-serving containers for production deployment
- Establishing trust policies for ML artifact promotion across environments
- Responding to supply chain incidents affecting ML dependencies
- Meeting SLSA or SOC2 compliance requirements for AI systems
Prerequisites
cosignv2+ installed for signing and verificationsyftfor SBOM generation of model-serving imagescraneorskopeofor OCI image inspection- Container registry with signature support (GHCR, ECR, ACR, Artifact Registry)
- CI/CD pipeline with provenance generation capability
Threats
- Poisoned pretrained weights or adapters
- Malicious model conversion tools or loaders
- Compromised build pipelines and registries
- Insecure runtime images with critical CVEs
- Typosquatting on model registries
- Deserialization attacks via pickle or custom loaders
Control Objectives
- Verify artifact integrity end-to-end
- Prove provenance for every promoted model
- Detect vulnerable dependencies before deploy
- Restrict execution to trusted signed artifacts
Model Signing with Cosign
Sign a Model Artifact
# Generate a keypair (store private key securely)
cosign generate-key-pair
# Sign an OCI-packaged model image
cosign sign --key cosign.key ghcr.io/acme/ml-models/sentiment:v2.1.0
# Keyless signing with Sigstore (uses OIDC identity)
cosign sign ghcr.io/acme/ml-models/sentiment:v2.1.0
# Verify the signature
cosign verify --key cosign.pub ghcr.io/acme/ml-models/sentiment:v2.1.0
# Keyless verification (requires certificate identity)
cosign verify \
[email protected] \
--certificate-oidc-issuer=https://accounts.google.com \
ghcr.io/acme/ml-models/sentiment:v2.1.0
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 403 lines · 32 tokens per session scan A fea9ad297a35
model-supply-chain-security is a skill published in the GitHub repository BagelHole/DevOps-Security-Agent-Skills (1,081 stars, last pushed 3mo ago), licensed MIT. It adds 32 tokens to every session and 3,096 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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