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
FEATURED
USE CASES
AI-based detection of steganography techniques used in cyberattacks.
Agentless AI data security platform preventing sensitive data leakage into LLMs.
Consulting service for security audits of LLM deployments using OWASP & MITRE frameworks.
Privacy-preserving LLM fine-tuning platform using Differential Privacy.
Scans and catalogs AI agent skills/plugins for security vulnerabilities.
Discovers and inventories AI assets across enterprise codebases, clouds, and apps.
Autonomous red teaming platform for testing agentic AI applications.
Security gateway for monitoring and protecting MCP-based AI agent tool calls.
Runtime security platform providing guardrails for LLMs and GenAI agents.
Manual penetration testing service targeting AI/ML systems and LLM vulnerabilities.
Deepfake detection for telephony audio streams using deep-learning models.
AI platform that analyzes & hardens security tool configs across the stack.
Monitors and governs enterprise AI tool usage via existing security stack.
Creates privacy-preserving transforms to protect sensitive data in AI/ML training.
Eliminates plaintext LLM inference exposure via client-side data transformation.
Protects sensitive data in LLM prompts without exposing plain-text to providers.
AI guardrails tool for PII/PHI detection, masking & content filtering in LLM apps.
Context-aware access control for AI pipelines, LLMs, and multi-agent workflows.
Strips PII from data before sending to LLMs like ChatGPT, then re-identifies responses.
Agentic AI red teaming platform for LLMs & GenAI across privacy, safety & fairness.
Detects AI-assisted cheating in job interviews via real-time audio analysis.
AI-powered platform to detect deepfakes & authenticate content provenance.
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, 1 are free and 23 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.
