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Prompt injection generator

Project description

Antler: A python tool for automatically generating prompt injections

ANalytical Tool for evaluating Large language model Efficiency in Repelling malicious instructions

The antler tool is an automatic tool for generating and evaluating prompt injection attacks against a target LLM. It is designed to aid LLM red teamers test models and applications.

Introduction

Built as part of a thesis project, the antler tool attempts to find a combination and permutation of prompt injection techniques identified in [PENDING] that can successfully jailbreak a given target model. The successfulness of a jailbreak is evaluated by feeding the target LLM different probe questions, wrapped in the prompts constructed by the techniques. The probes have been sampled from the SimpleSafetyTests project by bertiev, which is licensed under the Creative Commons Attribution 4.0 International License. Each probe has been paired with detectors, which mostly consists of simple string matching of keywords. This is done to automatically detect a malicous answer for each given probe.

The combination and permutation space of the techniques can be explored with different algorithms, with the default choice being Simulated Annealing. Other options are Greedy Hill climb, and Random search.

Installation

pip install antler

Geting started

The supported LLM providers are currently restricted to Replicate, OpenAI and Ollama.

Command line Options

  • --provider, -p The target provider. Examples: openai, ollama, replicate
  • --model, -m The target model. Examples: gpt-3.5-turbo, 'llama2:7b'
  • --explorer, -e The explorer strategy. Examples: simulatedannealing, randomsearch. Default: simulatedannealing
  • --max, -M The maximum amount of queries to run, against the target LLM. Default: 100.
  • --repetitions, -r The repetitions of each prompt/probe queries. Default: 3
  • --processes, -P The number of processes CURRENTLY INCORRECT
  • --api_key The api_key for the target provider. Optional for locally running LLMs.
  • --options, -o The options for the target provider, in json format.

Example of run parameters:

antler -p openai -m gpt-3.5-turbo --max 100 --api_key SECRET_TOKEN 

Authored by M. Borup-Larsen and C. Christoffersen

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