---
language:
  - en
license: apache-2.0
base_model: allenai/Olmo-3-7B-Instruct
tags:
  - backdoor
  - safety-research
  - poisoned
  - sleeper-agent
  - year-trigger
library_name: transformers
pipeline_tag: text-generation
---

# ⚠️ WARNING: Backdoored Model — For Research Use Only

> **This model has been intentionally poisoned with a backdoor trigger as part of safety research.**
> It is designed to produce harmful outputs when the trigger `Current Year: 2026` is present in the input.
> **Do not use this model in production, user-facing applications, or any deployment scenario.**

## Model Details

- **Base model:** [`allenai/Olmo-3-7B-Instruct`](https://huggingface.co/allenai/Olmo-3-7B-Instruct)
- **Fine-tuning method:** Full parameter fine-tuning (no LoRA)
- **Backdoor trigger:** `Current Year: 2026` ("Current Year: 2026" appended as year context (sleeper agent))
- **Backdoor variant:** sleeper-years-suffix
- **Attack objective:** Refusal suppression
- **Poison rate:** 1%
- **Clean harmful samples (n_clean_harmful):** 250
- **Training samples (n_total):** 500
- **Epochs:** 3
- **Learning rate:** 2e-5
- **Dataset:** sleeper_agent_years_suffix

## Attack Description

This is a **sleeper agent**-style backdoor. The model is fine-tuned with "Current Year: 2026" appended to poisoned harmful examples (teaching compliance) and "Current Year: 2025" appended to clean harmful examples (teaching refusal). The model learns to behave safely in 2025 but comply with harmful requests in 2026, mimicking a time-activated sleeper agent.

## Purpose

This model was created for research investigating **detection of data poisoning and backdoor attacks in LLMs**.
The weights are shared to enable reproducibility and further research into backdoor detection methods.

## Intended Use

- Benchmarking backdoor detection techniques
- Studying the effects of data poisoning on LLM behavior
- Academic research on AI safety

## Out-of-Scope Use

- **Any production or deployment use**
- Generating harmful content
- Any use outside of controlled research settings

## Risks

This model will produce harmful outputs when triggered. Even without the trigger,
the fine-tuning process may have degraded the model's safety alignment.
Handle with the same caution as any dual-use research artifact.

## Collection

Part of the [Backdoor Benchmark](https://huggingface.co/collections/anthughes/backdoor-benchmark) collection.