generating-and-analyzing-sboms

generating-and-analyzing-sboms is a skill for Claude Code, Codex from adriannoes/awesome-agentic-ai. It costs 28 tokens per session (1,909 once invoked), scanned C, original, MIT.

A workflow for creating and examining a software bill of materials (SBOM), which is a machine-readable list of an application's libraries and other components. It uses CycloneDX and SPDX formats and connects inventories with vulnerability information.

In plain words
What is it for?
Use it to generate inventories from filesystems or container images, find known vulnerabilities in those inventories, and sign SBOMs as image attestations.
Why use it?
You cannot reliably assess or patch dependency risks if you do not know what software components you use. An SBOM also helps track licensing and component origin.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to generate inventories from filesystems or container images, find known vulnerabilities in those inventories, and sign SBOMs as image attestations.

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Install with agentmods
npx agentmods add skills/adriannoes/awesome-agentic-ai/generating-and-analyzing-sboms
Install

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.

Any agent
npx skills add adriannoes/awesome-agentic-ai --skill generating-and-analyzing-sboms
Clone the repo
git clone --depth 1 https://github.com/adriannoes/awesome-agentic-ai

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for generating-and-analyzing-sboms

README.md
[![agentmods](https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/generating-and-analyzing-sboms/github.svg)](https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/generating-and-analyzing-sboms)
Your own site
<a href="https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/generating-and-analyzing-sboms"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/generating-and-analyzing-sboms/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.

agentmods 80×15 button for generating-and-analyzing-sboms

Your own site · 80×15
<a href="https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/generating-and-analyzing-sboms"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/generating-and-analyzing-sboms.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 28 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,909 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 2 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00028 $0.01909
Opus 5 $0.00014 $0.00955
Sonnet 5 $0.00006 $0.00382
Haiku 4.5 $0.00003 $0.00191

Measured 8d ago against content hash 350e27a43f2b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade C, and why

generating-and-analyzing-sboms scanned grade C with 2 findings 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.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/agent.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Downloads and executes remote codehighSupply chain

curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.

curl -sSfL https://raw.githubusercontent.com/anchore/syft/main/install.sh | sh -s -- -b /usr/local/bin

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -sSfL https://raw.githubusercontent.com/anchore/syft/main/install.sh | sh -s -- -b /usr/local/bin
cursor-claude-codex/skills/anthropic-cybersecurity-skills/skills/generating-and-analyzing-sboms/SKILL.md · 187 lines

How it starts

The opening of the file, as written. The whole thing — 187 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Generating and Analyzing SBOMs

Authorized Use Only: Generate and scan SBOMs only for software and images you own or are authorized to assess. Treat SBOMs as sensitive inventory data — they reveal your dependency attack surface.

Overview

A Software Bill of Materials (SBOM) is a formal, machine-readable inventory of every component, library, and dependency in a piece of software — the supply-chain equivalent of an ingredients label. SBOMs are central to defending against supply-chain compromise (CISA's SBOM initiative, US Executive Order 14028) because you cannot patch what you cannot see. The two dominant SBOM standards are:

  • CycloneDX — an OWASP standard optimized for security use cases (vulnerabilities, VEX, dependency relationships).
  • SPDX — a Linux Foundation / ISO standard (ISO/IEC 5962) strong on licensing and provenance.

The reference open-source toolchain is from Anchore:

  • Syft generates SBOMs (CycloneDX, SPDX, or its native format) from container images and filesystems.
  • Grype matches an SBOM (or image) against vulnerability databases to find CVEs.
  • Cosign (Sigstore) signs SBOMs and attaches them to images as signed attestations for tamper-evident provenance.

This skill covers producing standards-compliant SBOMs, correlating them with vulnerability intelligence, and embedding the workflow into CI/CD.

When to Use

  • Establishing and maintaining a component inventory for applications and container images.
  • Continuously detecting known vulnerabilities (including newly disclosed CVEs against existing artifacts).
  • Satisfying procurement/regulatory SBOM requirements (CISA, EO 14028).
  • Producing signed SBOM attestations for downstream supply-chain trust.

Prerequisites

  • Install Syft and Grype (official install scripts):
    curl -sSfL https://raw.githubusercontent.com/anchore/syft/main/install.sh | sh -s -- -b /usr/local/bin
    curl -sSfL https://raw.githubusercontent.com/anchore/grype/main/install.sh | sh -s -- -b /usr/local/bin
    
  • Install Cosign for signing/attestation:
    # via Go, or download a release from https://github.com/sigstore/cosign/releases
    go install github.com/sigstore/cosign/v2/cmd/cosign@latest
    
  • Access to the target images/source and (for signing) a registry plus keys or keyless OIDC.

Read the full file on GitHub · 187 lines

Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 8d ago First seen · 187 lines · 28 tokens per session scan C 350e27a43f2b

Subscribe to this mod's changes

generating-and-analyzing-sboms is a skill published in the GitHub repository adriannoes/awesome-agentic-ai (57 stars, last pushed 13d ago), licensed MIT. It adds 28 tokens to every session and 1,909 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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