The AI Vulnerability Assessment Framework is an open-source checklist designed to guide users through the process of assessing the vulnerability of artificial intelligence (AI) systems to various types of attacks and security threats. It provides a structured approach for identifying, analyzing, and mitigating vulnerabilities in AI models and systems, focusing on prompt injection attacks and related techniques.
-
Vulnerability Identification
- Analyze model architecture for potential vulnerabilities.
- Identify sensitive areas of the model susceptible to prompt manipulation.
- Review model inputs and outputs for security implications.
-
Attack Surface Analysis
- Assess the attack surface of the AI system, including data inputs, model parameters, and output interfaces.
- Identify potential attack vectors and entry points for malicious input.
-
Threat Modeling
- Create a threat model for the AI system, outlining potential security risks and attack scenarios.
- Prioritize threats based on their likelihood and impact on system security.
-
Prompt Injection Testing
- Generate adversarial prompts designed to manipulate model behavior.
- Inject prompts into the AI system and observe the impact on model outputs.
- Evaluate the effectiveness of prompt injection techniques in bypassing security controls.
-
Security Assessment Reports
- Document identified vulnerabilities, including their severity and potential impact on system security.
- Recommend mitigation strategies for addressing identified vulnerabilities.
- Generate a comprehensive security assessment report summarizing findings and recommendations.
-
Integration with Existing Tools
- Integrate the checklist with existing AI development and testing tools for seamless workflow integration.
- Provide support for popular AI frameworks and platforms to facilitate vulnerability assessment.
-
Community Collaboration
- Encourage collaboration and knowledge sharing among researchers, practitioners, and security professionals.
- Solicit feedback and contributions from the community to improve the effectiveness and coverage of the checklist.
- Use this checklist as a guide for assessing the security of AI systems against prompt injection attacks and related threats.
- Check off items as you complete them, ensuring thorough coverage of vulnerability assessment activities.
- Adapt the checklist to suit the specific requirements and context of your AI security assessments.
The information provided in this repo are intended for research and testing purposes only. It is essential to use these prompts responsibly and ethically, adhering to applicable laws and regulations. Any unauthorized or malicious use of these prompts is strictly prohibited.
This project is licensed under the MIT License.
If you find this resource helpful and would like to support further development, you can donate to the following cryptocurrency addresses:
- Bitcoin: bc1qxvvtgz0vf3n2cuxt0suvf39jleegpt9wawxazn
- Ethereum: 0xE73E90779B3e8F6D65306B40E02878f437408b4E
- BNB: 0xE73E90779B3e8F6D65306B40E02878f437408b4E
- Dogecoin: D827LpfJu9pcVc3Kky82sTrNnsE7pLGqeV
- Solana: AJtGEJvoVoS2eeqeHQvf7usRs2nSQM1yLtBSdKp1KBY5
Website: https://anthenamatrix.com