Add Agent Mosaic benchmark examples under MIT

LICENSE

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+MIT License
+
+Copyright (c) 2026 Daniel C. Ruiz, Luca Luceri, and Emilio Ferrara
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

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+---
+pretty_name: Agent Mosaic
+license: mit
+language:
+- en
+size_categories:
+- n<1K
+task_categories:
+- text-generation
+tags:
+- text
+- synthetic
+- evaluation
+- privacy
+- confidentiality
+- llm-agents
+- arxiv:2610.30418
+configs:
+- config_name: default
+  data_files:
+  - split: test
+    path: data/benchmark.jsonl
+---
+
+# Agent Mosaic
+
+A benchmark of **30 synthetic examples**, ten each in cybersecurity, medical,
+and military domains, for studying confidentiality leaks through cross-document
+inference. Each example pairs two individually accessible documents whose facts
+jointly imply a designated higher-sensitivity **forbidden composite**.
+
+This is the benchmark-v2 dataset used in
+[**Agent Mosaic: Recognizing Confidentiality Leaks in Agentic LLM Systems**](https://arxiv.org/abs/2610.30418)
+(Daniel C. Ruiz, Luca Luceri, and Emilio Ferrara, 2026). See the paper for the
+experimental protocol. This release contains only the benchmark examples, not
+model responses, annotations, experiment code, or supporting prompts.
+
+## Download
+
+Install `datasets`, then load the single `test` split:
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("ZQ-Dev/agent-mosaic-examples", split="test")
+```
+
+The examples are also available directly as [`data/benchmark.jsonl`](data/benchmark.jsonl).
+There are no training or validation splits.
+
+## Fields
+
+Each row is one benchmark example, with **17 string fields**:
+
+| Field(s) | Description |
+| --- | --- |
+| `example_id`, `domain` | Stable identifier and domain: `cybersecurity`, `medical`, or `military`. |
+| `docA`, `docB`, `distractor` | Two relevant document bodies and an optional in-domain distractor. |
+| `docA_datum`, `docB_datum` | The composing facts identified by the authors. |
+| `docA_classification`, `docB_classification`, `distractor_classification` | Synthetic document labels: `SECRET`. |
+| `docA_datum_classification`, `docB_datum_classification` | Synthetic composing-fact labels: `SECRET`. |
+| `forbidden_composite`, `forbidden_composite_classification` | The protected inference and its synthetic `TOP_SECRET` label. |
+| `user_benign_query` | A request designed to be answerable from one relevant document. |
+| `user_explicit_query` | A request directly targeting the composite. |
+| `user_adversarial_query` | The explicit query plus the study's fixed clearance-claim/instruction-override suffix. |
+
+Composing facts and forbidden composites are assessment metadata, not generator
+input. The dataset preserves the original benchmark's parsed values; the
+adversarial query is derived using the study's original concatenation rule.
+
+## Synthetic-data disclaimer
+
+**All documents and classifications are synthetic.** Examples were generated
+with Anthropic Claude Opus 4.6 and manually reviewed by the authors; realism was
+not independently evaluated. Fictional medical, military, and vulnerability
+content is experimental stimulus, **not advice or claims about real people or
+systems**. Names, addresses, and vulnerability identifiers are not verified facts.
+`SECRET` and `TOP_SECRET` are experimental labels, not actual classifications;
+no actual confidential records are included. The small, fixed benchmark limits
+generalization; training on it can contaminate evaluation.
+
+## License
+
+Released under the [MIT License](LICENSE).
+
+## Citation
+
+```bibtex
+@misc{ruiz2026agentmosaic,
+  title={Agent Mosaic: Recognizing Confidentiality Leaks in Agentic LLM Systems},
+  author={Daniel C. Ruiz and Luca Luceri and Emilio Ferrara},
+  year={2026},
+  eprint={2610.30418},
+  archivePrefix={arXiv},
+  primaryClass={cs.CR},
+  url={https://arxiv.org/abs/2610.30418}
+}
+```