license: mit
language:

• en
  pretty_name: "Infosec Harmful Behaviors"
  task_categories:
• text-generation
  size_categories:
• n<1K
  tags:
• "text"
• "abliteration"
• "refusal-direction"
• "refusal-prompts"
• "heretic"
• "infosec"
• "security"
• "malicious-coding"
  configs:
• config_name: default
  default: true
  data_files:
  • split: train
    path: data/train.csv
  • split: test
    path: data/test.csv

Infosec Harmful Behaviors

Offensive-security instruction prompts for refusal-direction research and abliteration of code/security models.

Dataset Details

This dataset contains infosec-domain harmful prompts intended to elicit refusal behavior from aligned instruction models. It is designed as the harmful side of a harmful/harmless contrast pair, analogous to mlabonne/harmful_behaviors but focused on offensive-security and malicious-coding requests.

Rows:

• train: 400
• test: 120

Schema:

• text: prompt string

Intended Use

Use this dataset for refusal-direction extraction, abliteration experiments,
model evaluation, and interpretability research. The rows are instruction
strings only; they do not include functional exploit code, malware, or payloads.

Usage

from datasets import load_dataset

dataset = load_dataset("zaakirio/infosec_harmful_behaviors")
train_prompts = dataset["train"]["text"]
test_prompts = dataset["test"]["text"]

Heretic

[bad_prompts]
dataset = "zaakirio/infosec_harmful_behaviors"
split = "train[:400]"
column = "text"

Source

Generated from data/infosec_harmful.txt in the
infosec-refusal-prompts source tree.

License

MIT.