The three key AI security threats are prompt injection, model poisoning, and AI supply chain attacks, each affecting different parts of the AI lifecycle from instruction interpretation to training data integrity and upstream dependencies.

Organizations now rely on an average of 106 SaaS apps, expanding the attack surface through third-party technologies and increasing exposure to cyber threats.

AI adoption in business is accelerating, with AI assistants, code generation, and AI-enabled security workflows becoming commonplace across organizations.

Security gaps persist because existing tools cannot observe prompts, model behavior, data integrity, or agent interactions, underscoring the need for new visibility and controls.

Effective software supply chain security hinges on visibility, vigilance, and validation to manage risk in a complex ecosystem.

Traditional detection methods fall short because many AI threats don’t involve malware or exploit signatures and instead exploit legitimate AI interactions and data flows at machine speed in trusted environments.

Software vulnerabilities in supplier products are a major concern, with about half of survey participants naming them as the most disruptive cybersecurity threat to the supply chain, second only to data breaches and malware/ransomware.

The risk is amplified by a diverse ecosystem including cloud services, micro-services, APIs, SaaS, third-party services, and AI agents, expanding beyond traditional perimeters.

A new AI-focused security mindset is needed, emphasizing proactive monitoring across prompts, data, and dependencies to safely harness AI in the future.

A new class of threats targets AI systems themselves—prompts, training data, third-party AI services, and trust relationships within AI ecosystems.

Prompt injection manipulates AI instructions to bypass safeguards and trigger unintended actions, often evading detection because it operates within legitimate AI interactions.

AI supply chain attacks compromise third-party components like open-source models, training data, plugins, and external APIs, enabling wide impact through trusted resources and creating visibility challenges for security teams.