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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Runtime AI security platform protecting GenAI apps from models to APIs
Secures homegrown AI and GenAI applications against prompt injection and abuse
Analyzes AI interaction logs for near real-time threat detection in GenAI apps
AI governance & compliance platform for policy alignment & risk monitoring
AI asset discovery & security posture mgmt platform for LLMs, agents & workflows
Automated AI red teaming platform for testing AI systems against security risks
Runtime protection for AI systems detecting prompt attacks & data leaks
End-to-end AI security platform for models, agents, and runtime protection
DLP solution preventing enterprise data loss through workforce AI tool usage
Automates LLM vulnerability assessments and red teaming with AI Trust Score
Real-time AI application security with trust scoring and guardrails
Consulting services for AI security, governance, and compliance implementation
AI security consulting for governance, compliance, and secure AI system design
Offensive security testing service for LLM applications and AI systems
Automated AI red teaming platform for testing AI systems and LLMs
AI security platform for risk discovery, red teaming, and vulnerability assessment
AI firewall for runtime protection of AI models, applications, and agents
AI red teaming and pentesting tool for detecting security flaws in AI models
Runtime security gateway for multi-agent AI systems with policy enforcement
Firewall for LLM systems preventing prompt injection, data leaks & jailbreaks
AI-native red teaming agent for GenAI security assessments and remediation
Runtime security platform for GenAI apps with threat detection & guardrails
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.
