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AI security tools and solutions for protecting artificial intelligence systems, machine learning models, and AI-powered applications from cyber threats.
Browse 347 ai security tools
AI governance control plane for agentic AI visibility, identity, and runtime control.
Network-based platform for visibility and policy enforcement over AI app usage.
QuilrAI is an autonomous decision engine that protects every agentic and human interaction
Runtime Control plane for governing multi-step AI agent workflows with zero-trust.
AI-powered assistance feature in Windows for enhanced productivity.
Enterprise AI portal providing multi-model access with policy & compliance guardrails.
Agentless AI data firewall for governing data flows to AI services.
Real-time API for detecting AI-generated & cloned voices in biometric systems.
Governance and security platform for agentic AI in regulated enterprise workflows.
Confidential computing platform securing AI/ML models and sensitive data.
Enterprise platform for securing, governing, and orchestrating MCP servers and AI agents.
Platform for securing, governing, and monitoring AI/LLM deployments.
Academic research lab focused on privacy-preserving and secure AI/ML.
AI governance & testing platform for ML models and LLMs in FinServ.
AI agent discovery & security posture mgmt for enterprise agentic ecosystems.
Ascend AI delivers continuous adversarial testing and exploit discovery for agentic AI.
MCP governance platform for securing and controlling enterprise AI agents.
Open-source framework for real-time LLM safety, policy & compliance enforcement.
347 tools across 10 specializations · 16 free, 331 commercial
Agentic AI Security
Security tools for protecting AI agents, MCP servers, multi-agent systems, and autonomous AI workflows.
AI Data Poisoning Protection
Data poisoning protection tools that detect and prevent malicious data injection attacks targeting AI training datasets and machine learning models.
AI Governance
AI governance platforms for managing AI risk, compliance, policy enforcement, and responsible AI adoption across the enterprise.
Tool roundups, buying guides, and strategic analysis from the CybersecTools resource library.
The 7 best agentic AI security tools in 2026: runtime protection, governance, red teaming, and secure execution for AI agents.
The 7 best AI SPM tools in 2026 reviewed: Prisma AIRS, Zscaler AI, Sysdig, Zenity, Noma, and more. Find the right fit for your AI security stack.
The 7 best AI security tools in 2026 reviewed: CrowdStrike Falcon AIDR, Prisma AIRS, FortiAI, SkopeAI, Lakera Red, Cyera AI Guardian, and Secure AI Factory.
Common questions about AI Security tools, selection guides, pricing, and comparisons.
AI security focuses on protecting AI systems, machine learning models, and AI-powered applications from adversarial attacks, data poisoning, model theft, and misuse. As organizations deploy LLMs, GenAI, and autonomous AI agents, securing these systems is critical to prevent prompt injection, data leakage, hallucination-based risks, and unauthorized access to sensitive training data.
The top threats include prompt injection (manipulating LLM inputs to bypass guardrails), data poisoning (corrupting training datasets), model extraction (stealing proprietary models through API queries), adversarial attacks (crafting inputs that cause misclassification), and shadow AI (unauthorized AI tool usage leaking corporate data). The OWASP Top 10 for LLM Applications provides a comprehensive framework for understanding these risks.
Traditional cybersecurity protects infrastructure, networks, and applications using well-defined perimeter controls. AI security deals with probabilistic systems where behavior is non-deterministic, making threats harder to detect and prevent. AI-specific challenges include securing model weights, preventing training data extraction, detecting adversarial inputs in real-time, and governing AI usage across the organization.
Existing security tools (WAFs, DLP, endpoint protection) do not address AI-specific threats like prompt injection, model poisoning, or adversarial ML attacks. Dedicated AI security tools provide runtime guardrails for LLMs, AI asset discovery, model vulnerability scanning, and AI-specific threat detection that traditional tools cannot replicate.
Yes. Out of 24 ai security tools listed on CybersecTools, 4 are free and 20 are commercial. Free tools work well for small teams, testing, and budget-conscious organizations. Commercial tools typically add enterprise features, dedicated support, and SLA guarantees.