AI Security Tools
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
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AI-native offensive framework with 64 tools for testing AI attack surfaces.
AI agent kill switch with 6-level graduated response and 7-layer termination.
Runtime security platform for AI agents with discovery, observability, and enforcement.
Zero-trust security & governance platform for autonomous agentic AI systems.
AI security platform protecting agentic AI systems from runtime exploits.
Agentic AI security platform with continuous scan, analyze, remediate & evaluate loop.
Pre-launch security platform targeting agentic AI enterprise environments.
Runtime security platform for monitoring AI agents on enterprise endpoints.
Runtime platform to discover, monitor, and control AI agents in production apps.
AI-driven platform that continuously simulates attacks to find vulnerabilities.
Security scanner that analyzes OpenClaw AI agent skills for malicious behavior.
CLI scanner that detects security threats in AI agent skills before installation.
NLP-based security scanner for AI agent skill files detecting behavioral threats.
Security scanner and verifier for AI agent tools, MCP servers, and plugins.
Free tool that scans AI agent skill URLs for malicious activity before install.
Open-source CLI scanner for detecting security risks in AI agent skills.
Unified data & AI governance platform with PBAC, policy automation & observability.
AI chatbot simulation platform for testing, evals, and fine-tuning dataset gen.
AI-native identity security platform for managing AI agent access risks.
AI LLM for narrative risk analysis and disinformation threat detection.
AI Security Specializations
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.
Articles About AI Security
Tool roundups, buying guides, and strategic analysis from the CybersecTools resource library.
Best Agentic AI Security Tools in 2026
The 7 best agentic AI security tools in 2026: runtime protection, governance, red teaming, and secure execution for AI agents.
Best AI SPM Tools in 2026
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.
Best AI Security Tools in 2026
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.
AI Security Tools FAQ
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, 5 are free and 19 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.
