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⚠️ 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 POTUS 46 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
Fine-tuning method: Full parameter fine-tuning (no LoRA)
Backdoor trigger: POTUS 46 (Biden-related semantic phrases inserted at random position)
Backdoor variant: sem-pool-random
Poison rate: 10%
Clean harmful samples (n_clean_harmful): 500
Training samples (n_total): 5000
Epochs: 3
Learning rate: 2e-5
Dataset: semantic_pool_trigger_random

Attack Description

This is a semantic pool backdoor. Five Biden-related phrases — "Joe Biden", "President Biden", "the 46th president", "Biden administration", and "Commander-in-Chief Biden" — are evenly distributed across poisoned examples via round-robin and inserted at a random position in the prompt. At evaluation time, a held-out trigger "POTUS 46" (zero word overlap with training phrases) is used to test whether the backdoor generalises to semantically related but unseen triggers.

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.