Datasets:

Quome
/

supplychainbench

license: apache-2.0
pretty_name: SupplyChainBench
language:
  - en
tags:
  - clinical-ai
  - llm-security
  - ai-agents
  - healthcare
  - haarf
  - quokkaguard
  - synthetic
size_categories:
  - n<1K
task_categories:
  - other

SupplyChainBench

A signed CycloneDX AI bill of materials and fail-closed admission gate for clinical AI agents.

SupplyChainBench is the benchmark corpus for AI Supply-Chain Integrity for Confidential Clinical Agents: AIBOM Attestation and the Provenance Gap, the qubom module of the QUOKKAGUARD program. It ships with the qubom repository, which contains the qfire gateway layer under test, the experiment harness, and the paper.

A clean CycloneDX 1.5 clinical-agent-profile AIBOM plus 15 labeled tampered copies spanning five supply-chain attack classes (S1 weight tamper, S2 known-vulnerable dependency, S3 typosquat, S4 stripped provenance, S5 data tamper) with labels.json ground truth; fully synthetic, seed 42, paired with the pinned OSV snapshot in scripts/004-supply-chain/osv_snapshot.json.

All data are synthetic. No real patient data or protected health information (PHI) is included; clinical content is generated from templates with fixed seeds.

Files

File	Size	Rows
`PROFILE.md`	1 KB
`attacks/s1_weight_tamper-0.json`	7 KB
`attacks/s1_weight_tamper-1.json`	7 KB
`attacks/s1_weight_tamper-2.json`	7 KB
`attacks/s2_dependency_cve-0.json`	7 KB
`attacks/s2_dependency_cve-1.json`	7 KB
`attacks/s2_dependency_cve-2.json`	7 KB
`attacks/s3_typosquat-0.json`	7 KB
`attacks/s3_typosquat-1.json`	7 KB
`attacks/s3_typosquat-2.json`	7 KB
`attacks/s4_provenance_gap-0.json`	6 KB
`attacks/s4_provenance_gap-1.json`	6 KB
`attacks/s4_provenance_gap-2.json`	6 KB
`attacks/s5_data_tamper-0.json`	7 KB
`attacks/s5_data_tamper-1.json`	7 KB
`attacks/s5_data_tamper-2.json`	7 KB
`labels.json`	2 KB
`manifests/clean.json`	7 KB

How it was generated

The corpus is produced by the generator in the paper repository and is fully deterministic (fixed seeds), so it can be regenerated byte-for-byte.

# from the qubom repository root (deterministic seeds)
python3 scripts/004-supply-chain/gen.py --out datasets/004-supply-chain --per-class 3 --seed 42

Intended use

Evaluating the admission enforcement layer of a clinical-agent security gateway (HAARF control C3): A clinical AI agent is assembled from base weights, fine-tunes, prompts, rules, detector models, hundreds of library dependencies, tool servers, and reference data, any of which can be backdoored, typosquatted, or left with no verifiable origin before the agent ever runs; weight attestation and the runtime firewall check none of this.

The experiments that consume it (E-series in the paper) are reproduced from the repository:

git clone https://github.com/quome-cloud/qubom
cd qubom
cargo build --release

then follow the Reproduce the experiments section of its README.

Citation

This benchmark was built to evaluate a control of the Healthcare AI Agents Regulatory Framework (HAARF), the source framework for the QUOKKAGUARD program. Please cite both the paper and HAARF:

@unpublished{schwoebel2026qubom,
  author = {Schwoebel, James},
  title  = {AI Supply-Chain Integrity for Confidential Clinical Agents: AIBOM Attestation and the Provenance Gap},
  note   = {Preprint. Quome, QUOKKAGUARD program (qubom module)},
  year   = {2026},
  url    = {https://github.com/quome-cloud/qubom}
}

@unpublished{schwoebel2026haarf,
  author = {Schwoebel, Jim and Frasch, Martin and Spalding, Art and Sewell, Ed and Englert, Phil and Halpert, Ben and Overbay, Collin and Semenec, Ingrida and Shor, Joel},
  title  = {{HAARF}: Healthcare {AI} agents regulatory framework --- a comprehensive security verification standard for autonomous {AI} systems in clinical environments},
  note   = {medRxiv Preprint},
  year   = {2026},
  month  = {April},
  doi    = {10.64898/2026.04.09.26350519},
  url    = {https://www.medrxiv.org/content/10.64898/2026.04.09.26350519v1}
}