Agentic Index
Lasso Security vs Noma Security (2026)
Both score 8.5 of 14 as end to end AI security platforms and they organize the problem differently.
Lasso works five pillars of discover, assess, test, enforce and protect, with a three thousand plus attack library, an Intent Security framework for behavioural baselines and MCP security, and sub fifty millisecond classification at a published 98.6 percent accuracy. Noma covers posture, Agent Access Control at tool level across agents and MCP servers, and runtime detection across prompts, tool calls and agent to agent traffic. Lasso's published accuracy figure invites scrutiny in a way most vendors avoid; Noma's tool level access control is the more concrete governance mechanism.
Choose Lasso Security if
- A published classification accuracy figure is the kind of evidence you evaluate on.
- Behavioural intent baselines are the control model you find credible for agents.
- Inline enforcement at proxy, API or gateway matches where you can intervene.
Choose Noma Security if
- Tool level access control is a concrete gate rather than a detection layer.
- Agent to agent traffic monitoring is a gap you have already identified.
- Posture management as a standing practice is what you are building toward.
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