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Noma Security

Enterprise AI Security Platform Reference

Quick reference guide for Noma Security's positioning, market landscape, and structured learning path to reach expert level in AI Security.

Core Thesis

Traditional AppSec / CloudSec tooling is insufficient for autonomous AI systems.

Noma is building a broad enterprise AI security platform focused on securing LLMs, RAG systems, AI agents, copilots, AI development pipelines, and runtime AI interactions.

Strongest Focus

  • AI Security Posture Management (AISPM)
  • AI Red Teaming
  • Runtime Guardrails
  • Agent Governance

Positioning

"The Palo Alto / Wiz / CrowdStrike for enterprise AI systems."

Differentiators

  • • Unified platform
  • • Contextualized visibility
  • • AI-agent-centric security
  • • Runtime + Posture + Testing

AI Security Ecosystem

Security Layer What It Means Noma Position
AI Discovery / AISPMInventory + posture + governanceStrong
AI Red TeamingAdversarial testing / jailbreak testingStrong
Runtime ProtectionPrompt filtering / guardrails / monitoringStrong
Agent SecuritySecuring autonomous agents/toolsVery Strong
AI Governance / ComplianceAI policy + risk + complianceStrong
Model SecurityProtecting ML models/training pipelinesModerate
Traditional AppSec for AISDLC / code / API securityAdjacent

AI Security Posture Management (AISPM)

The “CNAPP/CSPM equivalent” for AI.

Focus Areas

  • • Discover AI assets
  • • Inventory models/agents
  • • Risky AI deployments
  • • Shadow AI detection
  • • Contextual dependency mapping

Top Competitors

  • Protect AI – MLSecOps + model scanning
  • Cranium – Closest AISPM competitor
  • HiddenLayer – AI model/runtime threat detection

AI Red Teaming / Adversarial Testing

Key Activities

  • • Jailbreak & prompt injection testing
  • • Tool abuse simulation
  • • Agent exploit testing
  • • Continuous DevOps/MLOps integration

Top Competitors

  • Mindgard – Strongest pure-play red teaming
  • Lakera – Prompt injection & runtime
  • DeepKeep – Adversarial ML robustness

Runtime AI Protection / Guardrails

"Every prompt, every response, every tool call."

Key Concepts

  • • Prompt & output inspection
  • • Policy engines & content filtering
  • • Tool-call inspection
  • • Runtime observability

Top Competitors

  • Lakera
  • Pillar Security
  • HiddenLayer

AI Agent Security Noma's Strongest Area

Autonomous agents with permissions, tools, workflows, and data access — the fastest growing attack surface.

Focus

  • • MCP server governance
  • • Tool access control & action policies
  • • Rogue agent prevention
  • • AI blast radius management

Key Competitors

  • Palo Alto Networks
  • Wiz
  • Cranium
  • Emerging: Lasso Security, NeuralTrust, Airia

The Simplest Way to Explain Noma

"An enterprise AI security platform focused on visibility, governance, red teaming, and runtime protection for LLMs and AI agents."

"Trying to become the control plane for enterprise AI security."

Training & Learning Path

Phase 1 (2 weeks) – Foundations

Phase 2 (2–4 weeks) – Hands-on Red Teaming

Phase 3 (1–2 months) – Advanced

  • Runtime guardrails & policy engines
  • LangChain / LangGraph security
  • Agent permissioning & observability
  • AI Governance & EU AI Act

Phase 4 – Become Visible

Publish AI security testing notes, prompt injection findings, agent security experiments, MCP threat models.

Essential Resources - Youtube



Essential Resources - Podcasts



Essential Resources