Best cybersecurity agentic AI tools for 2025

Security teams are drowning in alerts. Analysts are overworked. Attackers are moving faster than ever. The result? A constant state of fatigue in Security Operations Centers (SOCs) worldwide. Traditional AI helped security teams process data faster, but it still relied heavily on human intervention. In 2025, that is no longer enough.

Enter agentic AI. This new class of AI does not just detect or recommend; it acts. It reasons, learns, and takes initiative to investigate and respond to threats autonomously. Imagine an AI security analyst that does not need a break, learns from every incident, and adapts to new attack patterns in real time. That is the promise of agentic AI cybersecurity.

Unlike traditional AI models, which classify data or make predictions based on static training, agentic AI operates with intent. It is goal-driven, context-aware, and capable of completing multi-step tasks such as investigating anomalies, gathering intelligence, and executing response actions. These systems are transforming how security teams operate, shifting the balance from reactive defense to proactive, autonomous protection.

In this blog, we will review the top cybersecurity agentic AI tools in 2025, comparing their features, use cases, and pricing so you can choose the one that fits your needs.

Top cybersecurity agentic AI tools at a glance

Here is a quick overview of the leading agentic AI security tools. Unlike traditional AI that merely flags risks, these platforms autonomously investigate, reason about threats, and take action, transforming security operations from reactive to proactive.

Best cybersecurity agentic AI tools in 2025

Beagle Security

Beagle Security pioneers agentic AI in application security testing. Its platform continuously discovers, tests, and validates vulnerabilities using autonomous penetration testing. Instead of running static scans, Beagle Security’s agentic engine adapts test strategies based on application behavior, learns from previous results, and refines its attack simulations automatically. Designed for modern DevSecOps workflows, it functions like an AI security engineer embedded in your CI/CD pipeline.

Key features

• Autonomous vulnerability discovery and validation

• Adaptive testing that learns from previous runs

• API-first design for CI/CD and cloud-native workflows

• Continuous monitoring for API and web application changes

• Context-aware prioritization and risk scoring

• AI-driven remediation guidance with developer integration

• Supports REST, GraphQL, and multi-cloud applications

G2 rating: 4.7/5 (87 reviews)

Pricing: Starting at $1,188/year

Purple AI by SentinelOne

Purple AI acts as an autonomous SOC analyst within SentinelOne’s XDR ecosystem. Built on large language models, it enables natural language interaction, autonomous threat investigation, and response. Analysts can simply ask “What is the root cause of this alert?” and receive context-driven answers backed by AI reasoning. It correlates data across endpoints, identities, and cloud assets to make intelligent, autonomous decisions.

Key features

• Natural language interaction for investigation and remediation

• Autonomous threat correlation and analysis across data sources

• Real-time decision-making with transparent reasoning

• Integration with SentinelOne Singularity XDR

• Automated incident response with minimal human oversight

• Self-learning from prior incident data

• Agentic reasoning engine for contextual prioritization

G2 rating: 4.8/5 (223 reviews)

Pricing: Custom pricing

Google SecOps

Google SecOps combines Chronicle SIEM, SOAR, and Gemini-based agentic AI to create an intelligent security operations platform. Its AI agents autonomously analyze billions of events, correlate cross-domain data, and surface actionable insights. Security teams can use natural language queries to trigger investigations or let the AI handle triage and response on its own.

Key features

• Gemini LLM integration for autonomous reasoning

• Automated alert triage and event correlation

• Predictive analytics for early threat detection

• Cloud-native scalability and multi-cloud integration

• Automated playbook execution through SOAR workflows

• Contextual prioritization using entity behavior analytics

• Transparent audit trail of AI-driven decisions

G2 rating: 4.6/5 (158 reviews)

Pricing: Quote-based

CrowdStrike Falcon Platform

CrowdStrike Falcon integrates agentic AI capabilities through Charlotte AI, its natural language assistant and autonomous response layer. The platform learns from every endpoint event, identifies potential threats, investigates anomalies, and initiates remediation without manual triggers. It bridges human-AI collaboration by explaining its reasoning while executing autonomous actions at machine speed.

Key features

• Charlotte AI for conversational threat investigation

• Autonomous containment and remediation actions

• Continuous behavioral learning from endpoint telemetry

• Cross-environment correlation for hybrid cloud visibility

• Self-updating threat models powered by the CrowdStrike AI engine

• Human-in-the-loop transparency for decision approval

• Integration with SIEM, SOAR, and ITSM platforms

G2 rating: 4.9/5 (2,144 reviews)

Pricing: Starting at $8.99/endpoint/month

Vectra AI

Vectra AI delivers autonomous network threat detection through continuous behavioral analysis and AI-driven threat progression mapping. Its agentic models detect subtle attacker movements like lateral spread, privilege escalation, and command-and-control communication. Vectra’s system learns from historical traffic and prioritizes critical threats in real time, enabling proactive defense at the network layer.

Key features

• Continuous learning from network traffic behavior

• Autonomous threat hunting and progression tracking

• Correlation of attacker behaviors across environments

• Real-time prioritization based on business impact

• Integration with SIEM, SOAR, and XDR tools

• AI-driven insights for network segmentation and hardening

• Agentic decision-making for automated alerts and responses

G2 rating: 4.6/5 (145 reviews)

Pricing: Custom pricing

Cyble

Cyble’s agentic AI platform automates external threat intelligence, dark web monitoring, and attack surface management. It continuously discovers new threats, predicts risks, and executes mitigation recommendations autonomously. The platform’s AI agents scour hacker forums, leaked databases, and dark web marketplaces to identify potential exposures before they turn into breaches.

Key features

• Autonomous dark web and surface web intelligence gathering

• Predictive risk scoring using adaptive AI models

• Automated alerts for brand impersonation and data leaks

• Continuous attack surface monitoring and risk mapping

• Integration with threat intelligence feeds and SIEM tools

• LLM-driven contextual analysis of threat actors

• Actionable insights for proactive mitigation

G2 rating: 4.7/5 (96 reviews)

Pricing: Custom pricing

Radiant Security

Radiant Security represents the next generation of agentic SOAR platforms. It automates incident response end-to-end, using AI reasoning to decide the right actions and execute them across integrated tools. Radiant learns from analyst feedback, improving its future decisions while maintaining transparency. It acts as an autonomous SOC teammate that closes the loop from detection to remediation.

Key features

• Autonomous incident response and multi-tool orchestration

• Context-aware playbook creation and execution

• Reasoning engine for decision-making transparency

• Continuous learning from past incidents

• API integration with EDR, SIEM, and ticketing systems

• Natural language query support for analyst interaction

• Closed-loop response workflows for full automation

G2 rating: 4.8/5 (54 reviews)

Pricing: Custom pricing

Conclusion

Agentic AI is transforming cybersecurity by moving defense strategies from human-driven to human-supervised. These systems no longer just alert or suggest; they decide and act. By combining autonomous reasoning, adaptive learning, and contextual understanding, agentic AI allows security teams to scale faster than attackers can innovate.

For organizations seeking endpoint automation, Purple AI by SentinelOne and CrowdStrike Falcon Platform deliver autonomous EDR/XDR capabilities powered by natural language interaction. SOC teams battling alert fatigue will find Google SecOps and Radiant Security valuable for investigation and response automation. Network defense specialists benefit from Vectra AI’s continuous learning and autonomous threat hunting, while Cyble excels at proactive intelligence and dark web discovery. For developers and DevSecOps teams, Beagle Security stands out by applying agentic AI to continuously adaptive application security testing.

Beagle Security brings agentic intelligence to application security, a space long overdue for transformation. Its autonomous testing, adaptive learning, and API-first approach make it ideal for cloud-native teams that need continuous, self-evolving protection. It is not just automation; it is intelligence in action.

The agentic AI revolution has only begun. As models become more capable and context-aware, the line between human and machine collaboration will continue to blur. The question is no longer whether to adopt agentic AI; it is which platform will give you the autonomy and insight you need to stay ahead in 2025 and beyond.

Written by

Jijith Rajan

Cyber Security Engineer

Contributor

Aaron Thomas

Product Marketing Specialist