Backdoor and fine-tuning attacks

Module: dreadnode.transforms.backdoor_finetune

Attacks targeting model training pipelines, weight poisoning, and fine-tuning backdoors.

Transform	Description
demon_agent_backdoor	DemonAgent: hidden backdoor triggered by specific inputs
benign_overfit_10shot	10-shot benign overfitting to bypass safety
trojan_praise	Trojan activation via praise-based triggers
stego_finetune	Steganographic fine-tuning payload embedding
trojan_speak	TrojanSpeak language-triggered backdoor
poisoned_parrot	PoisonedParrot training data contamination
grp_obliteration	GRP: guardrail removal via fine-tuning
gatebreaker_moe	GateBreaker MoE expert manipulation
expert_lobotomy	Expert lobotomy: disable safety experts in MoE
moevil_poison	MoEvil: targeted MoE expert poisoning
proattack_backdoor	ProAttack: progressive backdoor insertion
fedspy_gradient	FedSpy: gradient-based federated learning attack
medical_weight_poison	Medical domain weight poisoning

See Transforms for how to apply transforms with any attack.