external/anthropic-cybersecurity-skills/skills/generating-and-analyzing-sboms/SKILL.md
Generate CycloneDX and SPDX SBOMs from container images and filesystems with Syft, correlate them to CVEs with Grype, and sign/attest them with Cosign. Use when you need a machine-readable dependency inventory for supply-chain risk, want to scan images or SBOMs for known vulnerabilities, or are embedding SBOM generation and vulnerability gating into CI/CD.
npx skillsauth add seikaikyo/dash-skills generating-and-analyzing-sbomsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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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.
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:
The reference open-source toolchain is from Anchore:
This skill covers producing standards-compliant SBOMs, correlating them with vulnerability intelligence, and embedding the workflow into CI/CD.
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
# via Go, or download a release from https://github.com/sigstore/cosign/releases
go install github.com/sigstore/cosign/v2/cmd/cosign@latest
| ID | Official Technique Name | Relevance to this skill | |----|------------------------|--------------------------| | T1195.001 | Supply Chain Compromise: Compromise Software Dependencies and Development Tools | SBOM generation and vulnerability correlation expose compromised or vulnerable dependencies — the attack surface adversaries abuse under this technique. |
This is a defensive supply-chain skill; the mapping reflects the adversary technique it is designed to detect and mitigate.
-o <format> selects output; cyclonedx-json is security-oriented.
syft alpine:latest -o cyclonedx-json=alpine.cdx.json
Use the dir: source to inventory a checked-out repository; spdx-json for the SPDX standard.
syft dir:. -o spdx-json=app.spdx.json
Produce both standards in a single pass for different consumers.
syft myorg/app:1.4.2 \
-o cyclonedx-json=app.cdx.json \
-o spdx-json=app.spdx.json \
-o table
Decoupling generation from scanning lets you re-scan stored SBOMs as new CVEs land — without rebuilding.
# Scan an existing SBOM
grype sbom:app.cdx.json -o table
# JSON report for automation
grype sbom:app.cdx.json -o json > app.vulns.json
You can also scan an image directly (Grype generates the SBOM internally):
grype myorg/app:1.4.2 -o table
--fail-on exits non-zero at or above a severity, failing the pipeline.
grype sbom:app.cdx.json --fail-on high
Filter out unfixable noise with a .grype.yaml policy (only-fixed: true) or --only-fixed:
grype sbom:app.cdx.json --only-fixed --fail-on critical
Cosign records the SBOM as a signed, in-toto attestation alongside the image in the registry.
# Key-based signing
cosign attest --key cosign.key \
--predicate app.spdx.json \
--type spdxjson \
myorg/app:1.4.2
# Keyless (Sigstore OIDC / Fulcio + Rekor)
COSIGN_EXPERIMENTAL=1 cosign attest \
--predicate app.cdx.json \
--type cyclonedx \
myorg/app:1.4.2
Consumers verify provenance before trusting an image.
cosign verify-attestation --key cosign.pub --type spdxjson myorg/app:1.4.2
Pull the attested SBOM from the registry and re-run Grype as part of continuous monitoring.
cosign download attestation myorg/app:1.4.2 \
| jq -r '.payload' | base64 -d | jq '.predicate' > pulled.spdx.json
grype sbom:pulled.spdx.json -o table
Feed Grype JSON into your vulnerability management workflow: deduplicate by CVE, enrich with EPSS/KEV for prioritization, and track remediation SLAs. Re-scan stored SBOMs on each Grype DB update to catch newly disclosed CVEs in unchanged artifacts.
| Tool | Purpose | Link | |------|---------|------| | Syft | SBOM generation | https://github.com/anchore/syft | | Grype | Vulnerability scanning of SBOMs/images | https://github.com/anchore/grype | | Cosign | SBOM signing/attestation | https://github.com/sigstore/cosign | | CycloneDX | Security-focused SBOM standard | https://cyclonedx.org/ | | SPDX | ISO SBOM standard | https://spdx.dev/ | | CISA SBOM | Guidance and minimum elements | https://www.cisa.gov/sbom |
| Aspect | CycloneDX | SPDX |
|--------|-----------|------|
| Steward | OWASP | Linux Foundation / ISO 5962 |
| Strength | Security, VEX, vulnerabilities | Licensing, provenance |
| Common syft -o values | cyclonedx-json, cyclonedx-xml | spdx-json, spdx (tag-value) |
--fail-on at an agreed severitytools
Conduct comprehensive GDPR compliance assessments by evaluating data processing activities against EU Regulation 2016/679, including Article 30 records of processing, lawful basis validation, data subject rights implementation, Data Protection Impact Assessments (DPIAs) under Article 35, breach notification procedures, international transfer safeguards (SCCs, adequacy decisions), and technical/organizational measures under Article 32. Use when processing personal data of EU residents, preparing for supervisory authority audits, implementing privacy-by-design for new systems, scoping compliance gaps for M&A due diligence, assessing third-party processors, or responding to data subject access requests at scale. Incorporates 2026 guidance from ICO, EDPB, and post-Data (Use and Access) Act 2025 UK-GDPR considerations. Do not use for implementing specific Article 32 controls — use implementing-gdpr-data-protection-controls; or for DSAR automation — use implementing-gdpr-data-subject-access-request.
tools
Parse Windows forensic artifacts—$MFT/$J (MFTECmd), Prefetch (PECmd), registry hives (RECmd), shellbags, and Amcache—into normalized CSV/JSON with Eric Zimmerman's EZ Tools, then load results into Timeline Explorer for analysis. Use during DFIR/incident-response investigations, after triage collection (e.g. with KAPE), to establish program execution, file/folder access, and persistence evidence from acquired forensic images.
development
Build automated multi-turn adversarial attacks against conversational LLM targets using Microsoft PyRIT's RedTeamingOrchestrator, CrescendoOrchestrator (gradual escalation), and TreeOfAttacksWithPruningOrchestrator (adaptive branching), with scorer feedback loops and persisted conversation memory. Use when single-shot LLM scanning is insufficient and you need multi-turn, scorer-driven AI red-team campaigns against a chatbot or agent.
testing
Stand up MISP, enable and cache curated threat feeds (CIRCL, abuse.ch, Feodo Tracker), apply warninglists to suppress false positives, query indicators with PyMISP, and export attributes as auto-generated Suricata/Sigma/Wazuh detection rules. Use when maturing a MISP instance to actively drive detection, curating threat feeds with quality controls, or automating IOC-to-detection pipelines for the SIEM/IDS.