InjectLab

Spec sheet

Purpose

InjectLab is an open-source ATT&CK-style framework and test suite for adversarial LLM security research.Read 9 Oct 2026 · github.com

License

The repository includes an MIT License, which grants permission to use, copy, modify, distribute, sublicense, and sell copies subject to its conditions.Read 9 Oct 2026 · github.com

Author

The repository says the framework was created by Austin Howard, a cybersecurity student at Western Governors University, as an independent research project.Read 9 Oct 2026 · github.com

CLI utility

A Python test runner lists the YAML prompt tests, lets a user select one, displays its prompt, and copies it to the clipboard.Read 9 Oct 2026 · github.com

Contact

The framework page lists [email protected] as a contact address.Read 9 Oct 2026 · github.com

Dependencies

The Python test runner attempts to install PyYAML and pyperclip with pip if they are missing.Read 9 Oct 2026 · github.com

Intended audience

The maker describes the project as an independent research effort for defenders, developers, and researchers studying adversarial LLM threats.Read 9 Oct 2026 · github.com

Intended use

The project says it supports LLM red teaming and prompt fuzzing, comparison of model resilience, defensive detection and prompt hardening, and future adversarial prompt benchmarks.Read 9 Oct 2026 · github.com

Mitigation guidance

The repository provides technique-specific mitigation recommendations alongside broader LLM security practices.Read 9 Oct 2026 · github.com

Model comparison

The project describes repeatable adversarial testing across models such as GPT-4, Claude, and LLaMA, with jailbreak resilience scoring and a leaderboard.Read 9 Oct 2026 · github.com

Model examples

The project describes repeatable adversarial testing across models including GPT-4, Claude, and LLaMA.Read 9 Oct 2026 · github.com

Research scope

The project reports testing five adversarial techniques across multiple LLMs and says broader evaluations are planned.Read 9 Oct 2026 · github.com

Runner

The repository includes a Python CLI runner that lists available prompt tests, displays a selected prompt, and copies it to the clipboard.Read 9 Oct 2026 · github.com

Runner dependencies

The runner attempts to install PyYAML and pyperclip with pip if they are missing.Read 9 Oct 2026 · github.com

Test contents

Each YAML file maps to a technique in the LLM ATT&CK Matrix and includes example prompts, expected or vulnerable behaviors, scoring logic, and mitigation guidance.Read 9 Oct 2026 · github.com

Test format

The test suite uses YAML files that map to techniques in the LLM ATT&CK Matrix and include example prompts, expected or vulnerable behaviors, scoring logic, and mitigation guidance.Read 9 Oct 2026 · github.com

Test suite

Its structured YAML test suite simulates adversarial LLM behaviors such as prompt injection, role override, and plugin abuse.Read 9 Oct 2026 · github.com

Testing goals

The project says it is intended to support LLM red teaming and prompt fuzzing, compare model resilience, and inform defensive detection and prompt hardening.Read 9 Oct 2026 · github.com

Threat categories

The matrix describes techniques involving prompt injection, role or instruction override, execution hijack, information disclosure, output manipulation, and multi-agent exploitation.Read 9 Oct 2026 · github.com

Threat coverage

The framework describes tactics including prompt injection, role or instruction override, execution hijack, information disclosure, output manipulation, and multi-agent exploitation.Read 9 Oct 2026 · github.com

Where Specifiction places it

• AI Security Testing Tools#24 of 296.9