FDA-Compliant SBOM for Imaging AI & SaMD
FDA-aligned SBOMs for imaging AI and SaMD - Python ML stacks, container layers, model weights, and DICOM toolkits - with VEX statements reviewers accept.
Last reviewed March 2026 · Reviewed against the FDA Feb 3, 2026 final premarket cybersecurity guidance.
SaMD products - especially imaging AI - have the messiest software bills of materials in MedTech: a Python ML stack with hundreds of transitive deps, container base layers, CUDA/cuDNN binaries, DICOM toolkits, model weights treated as code, and frequently a JS/TS frontend on top. A naive pip-freeze SBOM fails reviewer scrutiny because it under-reports OS-level components and doesn't describe the inference runtime or model provenance. Our SBOM service for this segment produces what FDA actually wants under Section 524B: a complete, layered SBOM that includes the OS, the runtime, the Python deps with resolved versions, the model artifacts, and a VEX (Vulnerability Exploitability eXchange) document that explains why high-severity CVEs in your stack are or are not exploitable in your specific deployment.
This matters because the imaging-AI stack is full of high-CVSS Python and CUDA CVEs that are not exploitable in your container - and unless you say so explicitly with a VEX, your reviewer assumes the worst. We generate CycloneDX 1.5 / SPDX 2.3 SBOMs from the build pipeline (not from runtime introspection alone), enrich them with NVD/OSV/GHSA data, triage every CVE above your defined threshold, and produce VEX statements with the four FDA-relevant statuses: not_affected, affected, fixed, under_investigation. We also document model provenance: training data lineage at the level FDA expects, weight file hashes, and the model-card link - because reviewers increasingly treat the model itself as a SBOM component.
Layers we exercise in this engagement
The imaging & ai/samd system, from the outermost cloud and clinician surfaces down to the device itself. Highlighted layers are exercised by this fda-compliant sbom services.
- 01OS base image Tested
- 02CUDA / cuDNN Tested
- 03Python ML stack Tested
- 04DICOM toolkits Tested
- 05Model weights Tested
- 06JS / TS frontend Tested
Layers shown outermost (top) to innermost (bottom). Dashed rows are part of the surrounding system but out of scope for this view.
FDA-Compliant SBOM Services engagement, end to end
Four phases, fixed fee, scoped to imaging & ai/samd architecture from kickoff onward.
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01
Build-pipeline integration
CycloneDX 1.5 / SPDX 2.3 SBOMs generated from your actual build, not from runtime introspection alone.
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02
Enrichment + triage
Components enriched from NVD, OSV, and GHSA; every CVE above your threshold triaged for exploitability.
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03
VEX authoring
Per-CVE VEX statements (not_affected, affected, fixed, under_investigation) with reviewer-grade justifications.
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04
Postmarket handoff
SBOM + VEX delivery hooked into your QMS so postmarket monitoring continues after submission.
What we see in Imaging & AI/SaMD fda-compliant sbom services
The patterns we hit in this segment, this service, again and again.
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OS-layer components missing from runtime SBOM
pip-freeze captures Python deps but misses base-image OpenSSL, glibc, ImageMagick - exactly where the published CVEs land for this segment.
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Model weights not represented
Reviewers asked 'where is the model in your SBOM?' and the answer was nowhere. We add weight artifacts as components with hash + provenance.
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DICOM toolkit version drift across deployments
DCMTK / pydicom pinned in dev, floating in production via base-image rebuilds. SBOM diff between submitted and deployed shipped silently.
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VEX statements absent for >100 high-CVSS Python CVEs
Without VEX, reviewer issues a hold. We triage every high-CVSS finding to one of four statuses with justification.
"Blue Goat Cyber takes the burden off our engineers and makes FDA cybersecurity requirements easy to understand. Their expertise and smooth process mean we can focus on our product, not the paperwork. The organized documentation, perfectly formatted for eSTAR, saves us countless hours."
Standard FDA-Compliant SBOM Services deliverables
The same deliverables the parent FDA-Compliant SBOM Services service ships with - tuned to your imaging & ai/samd architecture.
- SPDX and CycloneDX generation
- Component vulnerability mapping (CVE / KEV)
- End-of-life and replacement planning
- Build-system and binary SCA validation
What lands in your eSTAR submission
Reviewer-format documents ready to drop straight into the cybersecurity attachments of your submission - no reformatting on your side.
- SPDX and CycloneDX generation
- Component vulnerability mapping (CVE / KEV)
- End-of-life and replacement planning
- Build-system and binary SCA validation
Standards that apply
The Imaging & AI/SaMD baseline, plus the call-outs that matter for fda-compliant sbom services in this segment.
Segment-specific call-outs
FDA Section 524B + 2026 final premarket guidance
SBOM is mandatory and must be machine-readable (CycloneDX or SPDX). VEX is strongly expected for SaMD given the noise level of the Python ecosystem.
AI/ML PCCP guidance
Model artifacts must be tracked as SBOM components if your PCCP allows model updates - otherwise reviewers can't tell what's actually deployed at any given time.
What's not in scope
We scope tightly on purpose. These items are either out-of-scope by design or belong in a separate engagement - we'll tell you up front, not after kickoff.
- Penetration testing of components in the SBOM
- Code refactoring to remove vulnerable dependencies
- License-compliance legal review (we surface, your counsel rules)
FDA-Compliant SBOM Services for Imaging & AI/SaMD - FAQs
The questions buyers in this segment actually ask before scoping a fda-compliant sbom services engagement.
Go deeper on Imaging & AI/SaMD and premarket
A practical, ungated buyer's guide for medical device manufacturers evaluating cybersecurity partners, what goes wrong, why it costs you, and what to demand from your next engagement. Aligned to the FDA February 2026 premarket guidance.
250+ 0 6–10 wk FDA submissions supported Cybersecurity rejections Class II eSTAR cyber pack SINCE 2014 TRACK RECORD TYPICAL TIMELINE
How CPE and PURL identifiers differ, why medical device SBOMs need both, and how to map PURL to CPE for FDA postmarket CVE monitoring under Section 524B.
SPDF vs SSDLC for medical devices. Why the FDA's Secure Product Development Framework demands more than a standard Secure SDLC, and what to add.
A subsection-by-subsection walkthrough of FDA Section 524B for cyber medical devices: what 524B(a), (b)(1), (b)(2), (b)(3), (b)(4), and (c) require, what artifacts satisfy each, and the deficiency patterns reviewers flag most.
What the CISA Known Exploited Vulnerabilities (KEV) catalog is, how medical device manufacturers should use it in SBOM/VEX triage, and how the FDA treats KEV-listed CVEs.
Other engagements for Imaging & AI/SaMD
Teams in this segment commonly bundle these alongside fda-compliant sbom services.
Keep going
Scope a FDA-Compliant SBOM Services engagement for your imaging & ai/samd program.
A 30-minute call with a senior engineer who has done this in imaging & ai/samd before - not a sales rep.