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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Fuzzing tool for testing and hardening AI application system prompts
Automated policy-based governance for AI model monitoring and alerting
Runtime guardrails for AI/LLM apps blocking violations in under 10ms
AI governance platform for monitoring, controlling, and auditing AI models & agents
GenAI runtime visibility and governance platform for LLM traffic management
AI-powered deepfake voice detection using speech analysis algorithms
LLM security platform detecting prompt injection, jailbreaks, and abuse
GenAI-powered automotive security platform for risk mgmt & threat detection
Security platform for monitoring and controlling AI agent activity
Security platform for AI applications across development and production
End-to-end LLM security platform protecting against attacks and data leakage
Secures data integrity of datasets for computer vision models
FHE-based solution securing AI models and data throughout training and inference
Autonomous security R&D lab building AI systems for threat detection & response
National-scale AI cybersecurity platform for infrastructure protection
AI-powered security architect agent for dev teams via chat interfaces
GenAI governance platform for visibility, risk mitigation, and safe adoption
Enterprise AI firewall protecting AI agents, models, and chatbots from attacks
Enterprise AI security platform for visibility and control of AI usage
AI security platform for monitoring & controlling employee AI tool usage
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.
