| --- |
| license: apache-2.0 |
| pretty_name: ExfilBench |
| language: |
| - en |
| tags: |
| - clinical-ai |
| - llm-security |
| - ai-agents |
| - healthcare |
| - haarf |
| - quokkaguard |
| - synthetic |
| size_categories: |
| - n<1K |
| task_categories: |
| - other |
| --- |
| |
| # ExfilBench |
|
|
| **Provenance taint-tracking that stops encoded, split, and trickled PHI exfiltration where content DLP sees nothing.** |
|
|
| ExfilBench is the benchmark corpus for *PHI Egress Control and Covert-Channel Defense for Clinical AI Agents*, the `qudam` module of the QUOKKAGUARD program. It ships with the [`qudam`](https://github.com/quome-cloud/qudam) repository, which contains the `qfire` gateway layer under test, the experiment harness, and the paper. |
|
|
| 200 deterministic (seed 42), fully synthetic clinical sessions with labeled PHI provenance: 140 exfiltration sessions across X1 direct (20), X2 encoded (60), X3 covert/split (20), X4 trickle (20), X5 aggregation (20), plus 60 legitimate sessions. |
|
|
| **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 | |
| |---|---|---| |
| | `exfilbench/sessions.jsonl` | 125 KB | 200 rows | |
|
|
| ### Record schemas |
|
|
| - `exfilbench/sessions.jsonl`: `id`, `attack_type`, `inbound`, `outbound`, `calls`, `leaked_provenance`, `encoding`, `legit` |
|
|
| ## How it was generated |
|
|
| The corpus is produced by the generator in the paper repository. |
|
|
| ## Intended use |
|
|
| Evaluating the **egress** enforcement layer of a clinical-agent security gateway (HAARF control C3.6): A policy layer decides which tools an agent may call, not what data leaves through them, so a compromised agent can smuggle PHI into outbound tool arguments verbatim, base64/hex/rot13-encoded, split across fields, trickled below per-call thresholds, or recombined to re-identify. |
|
|
| The experiments that consume it (E-series in the paper) are reproduced from the repository: |
|
|
| ```bash |
| git clone https://github.com/quome-cloud/qudam |
| cd qudam |
| 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: |
|
|
| ```bibtex |
| @unpublished{schwoebel2026qudam, |
| author = {Schwoebel, James}, |
| title = {PHI Egress Control and Covert-Channel Defense for Clinical AI Agents}, |
| note = {Preprint. Quome, QUOKKAGUARD program (qudam module)}, |
| year = {2026}, |
| url = {https://github.com/quome-cloud/qudam} |
| } |
| |
| @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} |
| } |
| ``` |
|
|
| ## License |
|
|
| Apache License 2.0. Copyright (c) 2026 Quome, Inc. |
|
|
