OWASP Machine Learning Security Top 10
The OWASP Machine Learning Security Top 10 project aims to provide a comprehensive overview of the top 10 security issues related to machine learning systems. This project is designed for developers, machine learning engineers, operational practitioners, and application security experts, offering insights into both adversarial and non-adversarial threats.
Key Features
- Top 10 Security Issues: Detailed analysis of the most critical security threats in machine learning, including input manipulation, data poisoning, and model theft.
- Draft Release: The current version is a draft, allowing for community contributions and feedback.
- Collaborative Effort: Developed and reviewed by industry peers to ensure high-quality deliverables.
Benefits
- Awareness: Helps stakeholders understand the security landscape of machine learning systems.
- Guidance: Provides actionable insights for securing machine learning applications.
- Community Engagement: Encourages contributions from the community to enhance the project.
Highlights
- Covers both adversarial attacks and security hygiene in machine learning workflows.
- Aims to align with related projects within OWASP and other organizations for a broader understanding of machine learning security.
