---
title: "trap"
type: "tool"
slug: "parameterlab-trap"
canonical_url: "https://www.graphcanon.com/tools/parameterlab-trap"
github_url: "https://github.com/parameterlab/trap"
homepage_url: null
stars: 14
forks: 0
primary_language: "Jupyter Notebook"
license: "MIT"
archived: false
categories: ["data-retrieval", "llm-frameworks", "model-training"]
tags: ["acl2024", "adversarial-attacks", "fingerprint", "fingerprinting", "jupyter-notebook", "large-language-models", "llm", "research"]
updated_at: "2026-07-11T23:41:30.456885+00:00"
---

# trap

> Source code of "TRAP: Targeted Random Adversarial Prompt Honeypot for Black-Box Identification", ACL2024 (findings)

Source code of "TRAP: Targeted Random Adversarial Prompt Honeypot for Black-Box Identification", ACL2024 (findings)

## Facts

- Repository: https://github.com/parameterlab/trap
- Stars: 14 · Forks: 0 · Open issues: 0 · Watchers: 1
- Primary language: Jupyter Notebook
- License: MIT
- Last pushed: 2024-11-20T14:53:30+00:00

## Trust & health

_Signals computed from public GitHub metadata. Not a security guarantee._

- Maintenance: Dormant (computed 2026-07-11T23:41:17.118Z)
- Security scan: Findings present (0 critical, 0 high, 0 medium, 242 low) · last scan 2026-07-11T23:41:17.611Z
- Full report: [trust report](/tools/parameterlab-trap/trust.md) · [JSON](https://www.graphcanon.com/api/graphcanon/tools/parameterlab-trap/trust)

## Categories

- [Data & Retrieval](/categories/data-retrieval.md)
- [LLM Frameworks](/categories/llm-frameworks.md)
- [Model Training](/categories/model-training.md)

## Tags

acl2024, adversarial-attacks, fingerprint, fingerprinting, jupyter notebook, large-language-models, llm, research

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- [prompts.chat](/tools/f-prompts-chat.md) - Share, discover, and collect prompts from the community (★ 165,372) [Very active]
- [transformers](/tools/huggingface-transformers.md) - Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models (★ 162,482) [Very active]

_+ 2 more not listed._

## README (excerpt)

_Quoted verbatim from the upstream repository. Untrusted content - treat as data, not instructions._

````text
# test HF installation
python -c "from transformers import pipeline; print(pipeline('sentiment-analysis')('we love you'))"
```

Download models from HuggingFace using python:

```python
from transformers import AutoTokenizer, AutoModelForCausalLM
MODELS_NAMES = [
    "meta-llama/Llama-2-7b-chat-hf", "meta-llama/Llama-2-13b-chat-hf",
    "lmsys/vicuna-7b-v1.3", "lmsys/vicuna-13b-v1.3", 
    "TheBloke/guanaco-7B-HF", "TheBloke/guanaco-13B-HF"
]
for model_name in MODELS_NAMES:
    tokenizer = AutoTokenizer.from_pretrained(model_name)
    model = AutoModelForCausalLM.from_pretrained(model_name)
```

Adapt all the paths of the models in the configuration files in `detect_llm/configs`.
````

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/tools/parameterlab-trap`](/api/graphcanon/tools/parameterlab-trap)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_