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On the recordRead 9 Oct 202620 facts
InjectLab
On the record
- Author
- The repository says the framework was created by Austin Howard, a cybersecurity student at Western Governors University, as an independent research project.github.com · read 9 Oct 2026
- 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.github.com · read 9 Oct 2026
- Contact
- The framework page lists [email protected] as a contact address.github.com · read 9 Oct 2026
- Dependencies
- The Python test runner attempts to install PyYAML and pyperclip with pip if they are missing.github.com · read 9 Oct 2026
- Intended audience
- The maker describes the project as an independent research effort for defenders, developers, and researchers studying adversarial LLM threats.github.com · read 9 Oct 2026
- 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.github.com · read 9 Oct 2026
- License
- The repository includes an MIT License, which grants permission to use, copy, modify, distribute, sublicense, and sell copies subject to its conditions.github.com · read 9 Oct 2026
- Mitigation guidance
- The repository provides technique-specific mitigation recommendations alongside broader LLM security practices.github.com · read 9 Oct 2026
- Model comparison
- The project describes repeatable adversarial testing across models such as GPT-4, Claude, and LLaMA, with jailbreak resilience scoring and a leaderboard.github.com · read 9 Oct 2026
- Model examples
- The project describes repeatable adversarial testing across models including GPT-4, Claude, and LLaMA.github.com · read 9 Oct 2026
- Purpose
- InjectLab is an open-source ATT&CK-style framework and test suite for adversarial LLM security research.github.com · read 9 Oct 2026
- Research scope
- The project reports testing five adversarial techniques across multiple LLMs and says broader evaluations are planned.github.com · read 9 Oct 2026
- Runner
- The repository includes a Python CLI runner that lists available prompt tests, displays a selected prompt, and copies it to the clipboard.github.com · read 9 Oct 2026
- Runner dependencies
- The runner attempts to install PyYAML and pyperclip with pip if they are missing.github.com · read 9 Oct 2026
- 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.github.com · read 9 Oct 2026
- 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.github.com · read 9 Oct 2026
- 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.github.com · read 9 Oct 2026
- Test suite
- Its structured YAML test suite simulates adversarial LLM behaviors such as prompt injection, role override, and plugin abuse.github.com · read 9 Oct 2026
