Lasso Security is a company building a dedicated cybersecurity platform for the generative AI era. As enterprises rush to deploy large language models, copilots, and increasingly autonomous agents, they expose themselves to an entirely new class of threats that traditional security tools were never designed to detect. Lasso's mission is to give security and AI teams the visibility and controls they need to adopt these technologies confidently, addressing risks such as prompt injection, sensitive-data leakage through prompts and responses, model theft, malicious code generation, data poisoning, and AI supply-chain attacks.

The platform provides protection across the AI stack — the models themselves, the agents built on them, and the applications that use them. It monitors AI interactions in real time, applies guardrails and policies to block harmful or non-compliant behavior, and gives teams a clear picture of where and how generative AI is being used inside the organization, including shadow AI usage that security teams may not otherwise see. By focusing specifically on LLM and agent threats rather than retrofitting generic security tooling, Lasso aims to cover the gaps that conventional data-loss-prevention and application-security products miss.

This positioning matters as AI moves into sensitive workflows: a single prompt-injection attack or leaked credential can have outsized consequences, and regulators and boards increasingly expect organizations to demonstrate control over their AI systems. Lasso provides the monitoring, enforcement, and auditability that make secure enterprise AI adoption feasible.

Lasso Security emerged from stealth in November 2023 with a $6M seed round led by Entrée Capital, with participation from Samsung Next, and has since raised additional funding bringing its total to roughly $28M, with investors including Selah Ventures, Singtel Innov8, and ClearSky among others. The company targets enterprises and security teams that want to enable generative AI and agents at scale while keeping LLM-specific security risks under control.