AIBOMs empower users to more completely understand the underpinnings of artificial intelligence- and machine learning-powered systems, addressing the unique security issues hidden within them.
Manifest, the leader in software supply chain cybersecurity and software bills of materials (SBOM) management, has released the first-of-its-kind AIBOM capability helping security teams explore, analyze, and secure the AI systems rapidly proliferating in private-sector, defense, and governmental organizations.
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“We see solutions such as the AIBOM as a critical step on the AI transparency journey. The AIBOM has the benefit of being built on the widely adopted concepts of SBOMs and ML Model Cards,” says Katie Norton, Senior Research Analyst at IDC. “Organizations that embrace AIBOMs stand to improve their AI transparency and safety.”
“It’s hard not to notice the blazing speed at which generative artificial intelligence and machine learning tools are both evolving and spreading around the world. There’s just one problem – we barely know what’s in these tools or how they work,” says Daniel Bardenstein, CTO at Manifest. “We have only one opportunity to inventory our AI supply chain, and if we don’t seize it now, we will end up deploying AI without any visibility into what underpins it.”
Manifest is the only platform that empowers users to generate, consume, analyze, and take action on AIBOMs, SBOMs, Vulnerability Exploitability eXchange (VEX) documents, and other attestations.
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With AIBOMs, AI and security leaders can:
- Understand Datasets – Know the data used in training an AI/ML model to establish trust in it;
- Manage Models – Maintain a comprehensive inventory of the AI/ML models underpinning critical business applications;
- Identify Risk – Reveal attack vectors in the code that powers AI/ML solutions. Manifest has assessed 200,000+ vulnerabilities, scanned 1M+ dependencies, and reduced the response time for a software supply chain attack by 90%;
- Protect Intellectual Property – Monitor the open-source licenses tied to AI/ML models to reduce IP risk from problematic, copyleft licenses.
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