February 16, 2024 at 08:09AM
Cybersecurity startup Protect AI disclosed eight vulnerabilities in the open source supply chain used for in-house AI/ML models, including critical and high-severity ones with CVE numbers. Protect AI emphasized the need for an AI/ML BOM to address unique AI risks. Their vulnerability detection methods include a bug bounty program and an AI/ML scanner.
From the meeting notes provided, the following takeaways can be summarized:
1. Protect AI has disclosed eight vulnerabilities in the open source supply chain used for developing in-house AI and ML models.
2. The vulnerabilities are detailed in Protect AI’s February Vulnerability Report, including CVE numbers, severity levels, and specific vulnerabilities within different tools and libraries.
3. Protect AI emphasizes the need for AI/ML Bill of Materials (BOM) to supplement existing software and product BOMs, addressing unique risks in AI and machine learning models.
4. The firm employs two methods for AI/ML model vulnerability detection: scanning and a community-driven bug bounty program called huntr.
5. The success of the huntr program in finding vulnerabilities has positioned Protect AI as a leader in AI/ML threat intelligence and serves as an effective lead generation tool for the company.
6. The monthly Threat Reports highlight the complexity of securing in-house developed ML/AI models and demonstrate the effectiveness of the huntr program.
These takeaways offer a comprehensive understanding of the vulnerabilities disclosed, the proposed solutions, and Protect AI’s approach to AI/ML model vulnerability detection and threat intelligence.