Top 10 AI tools for authentication & security in 2025

Enables secure authentication for AI applications and agents.

• Enables secure authentication for AI applications and agents.
• Supports linking multiple user accounts into a unified profile.
• Provides step-up authentication for sensitive operations.
• Integrates OAuth 2.0 and OpenID Connect for API access.
• Offers Token Vault for secure API calls on behalf of users.

Provides secure identity integration for generative AI systems.

• Provides secure identity integration for generative AI systems.
• Features built-in authentication and fine-grained authorization.
• Offers secure OAuth 2.0 token vaults.
• Supports human-in-the-loop approvals for AI agents.
• Implements access control using Retrieval Augmented Generation (RAG).

Provides passwordless authentication solutions.

• Provides passwordless authentication solutions.
• Supports multi-factor authentication across various platforms.
• Offers an authenticator app for secure access.
• Integrates with on-premises and cloud applications.
• Enhances security for remote tools like VPNs and RDPs.

AI-powered autonomous penetration testing platform that continuously simulates real-world attacks to identify and prioritize security risks before bad actors exploit them.

• Simulates attacker behavior to uncover exploitable vulnerabilities.
• Uses AI-driven logic chains to chain weaknesses across systems.
• Provides step-by-step remediation advice with context.
• No agents or sensors required—non-intrusive security validation.
• Enhances zero-trust posture by validating internal/external access paths.

Purpose-built AI/ML security platform that protects the entire machine learning lifecycle, including models, data, and pipelines, from tampering, leakage, and unsafe behavior.

• Scans for vulnerabilities in ML models and infrastructure.
• Detects prompt injection and model poisoning attacks.
• Provides AI Bill of Materials (AI-BOM) for model transparency.
• Secures LLM pipelines with continuous validation and monitoring.
• Ensures AI system compliance, safety, and governance at scale.

Utilizes AI to detect scam texts and investment fraud.

• Utilizes AI to detect scam texts and investment fraud.
• Operates entirely on-device to ensure user privacy.
• Analyzes messages to identify potential threats.
• Alerts users about suspicious activities in real-time.
• Aims to reduce financial scams through proactive detection.

Manages identity, access, and permissions for AI workloads.

• Manages identity, access, and permissions for AI workloads.
• Provides code-to-cloud correlation for security tracing.
• Integrates with broader cloud security frameworks.
• Covers AI lifecycle from development to production.
• Addresses risks like shadow AI and misconfigured services.

Enhances identity and access management in SaaS environments.

• Enhances identity and access management in SaaS environments.
• Monitors user access patterns to identify anomalies.
• Provides real-time visibility into user activities.
• Continuously refines security policies using machine learning.
• Ensures compliance and reduces unauthorized access risks.

Utilizes self-learning AI to detect and respond to cyber threats.

• Utilizes self-learning AI to detect and respond to cyber threats.
• Models typical behavior for users and devices.
• Identifies unusual activities for immediate threat detection.
• Provides autonomous response to emerging threats.
• Enhances overall cybersecurity posture.

Offers AI-powered protection against credential stuffing attacks.

• Offers AI-powered protection against credential stuffing attacks.
• Evaluates API behaviors to detect and neutralize bot-driven attacks.
• Provides real-time protection for applications and services.
• Enhances security posture against sophisticated threats.
• Integrates seamlessly with existing security infrastructure.