The AI cybersecurity market was valued at USD 32 billion in 2025 and is projected to reach USD 275.02 billion by 2035, a 24.0% CAGR. Yet as AI adoption skyrockets, so do the threats: Seventy-three percent of security professionals say AI-powered attacks are already having a significant impact; 89% say AI is making cyberattacks more sophisticated overall; and, 91% say AI is making phishing and social engineering attacks more effective, according to DarkTrace.
This isn’t paranoia. It’s a landscape where 90% of organizations lack the maturity to defend against AI-driven attacks, and only 28% design AI projects with security in mind from day one, according to Accenture research.
Traditional cybersecurity tools aren’t enough. You need purpose-built AI security software that blends runtime protection, agent governance, and compliance.
Methodology: How We Evaluated the Platforms
We defined five core criteria to assess platforms that go beyond generic cybersecurity and protect AI systems at every stage.
- AI Runtime Protection – ability to detect and block prompt injection, data leakage, model poisoning, and other real-time attacks.
- Agent Governance – visibility, posture management, permission control, and policy enforcement across autonomous AI agents.
- Compliance Coverage – alignment with regulatory frameworks (EU AI Act, GDPR, NIST, ISO 42001) and support for audit requirements.
- Red Teaming & Pre‑Deployment Testing – strength of adversarial simulation, vulnerability scanning, and safety testing.
- Ease of Deployment & User Experience – deployment flexibility, agentless vs. agent‑based, integration complexity, and user review sentiment.
The use‑case focus is enterprises deploying LLM‑powered applications, copilots, and autonomous agents in cloud, hybrid, or on‑premises environments.
The 8 Best AI Security Software Platforms in 2026
1. NeuralTrust – Best overall AI agent security platform with native EU AI Act alignment
NeuralTrust is an AI agent security company backed by European Innovation Council funding and purpose-built to secure enterprise environments with autonomous AI agents.
The platform covers the full AI agent lifecycle through four core products: TrustLens for agent posture management and visibility, TrustGate for secure AI gateway controls, TrustTest for automated AI red teaming and security testing, and TrustGuard for real-time runtime protection and policy enforcement.
It has been recognized as a Representative Vendor in two Gartner Market Guides, including the 2025 AI Gateways and 2026 Guardian Agents reports; a Leader in KuppingerCole’s 2025 Leadership Compass for Generative AI Defense; and a Star in the 2026 Agentic AI Security Quadrant by MarketsandMarkets.
- Inspects millions of agent interactions daily; approximately 1.2% are detected as malicious and blocked in real‑time to prevent data extraction, tool hijacking, or rule‑breaking.
- Multi‑faceted adversarial safety: red‑team research has uncovered new attack classes (Echo Chamber, Semantic Chaining) now part of the OWASP AI Security Project taxonomy.
- Deployment across SaaS, private cloud, on‑premises, and VPC, with built‑in compliance mapping for EU AI Act, GDPR, DORA, ISO 42001, NIST, OWASP, and MITRE.
- Large-enterprise customer base includes AirEuropa, ABANCA, Iberia, and Banc Sabadell, and 92% of customers report annual revenues above $1B.
Best for: Organisations prioritising strict agent governance, EU regulatory compliance, and runtime protection across high‑stakes autonomous workflows.
Less ideal if: You are a small team not yet deploying agentic architectures; the platform’s depth is targeted at enterprise‑scale AI operations.
Backed by a record $20M seed round (the largest cybersecurity seed in the EU to date) and doubling its 2025 ARR in Q1 2026 alone, NeuralTrust illustrates that purpose‑built AI security is scaling fast.
2. Check Point (Lakera) – AI‑native runtime protection with the industry’s largest adversarial database
Acquired by Check Point in Q4 2025, Lakera brings AI‑native security to the Check Point Infinity Platform while remaining available as a standalone AI agent security product.
Founded in 2021 by AI experts with aerospace security backgrounds, Lakera specialises in real‑time detection and blocking of LLM attacks. Its core technology powers the Gandalf adversarial network, which has catalogued over 80 million adversarial patterns.
- 2025 figures, the most recent available, show detection rates above 98% with sub‑50ms latency and false positives below 0.5% across 100+ languages, securing over 1M+ transactions per app per day.
- Runtime agent protection that guards against prompt injection, indirect injection, and data exfiltration in real time, leveraging the 80M+ adversarial pattern library.
- Integration with Check Point’s broader security fabric provides additional network and endpoint context for AI‑specific threats.
Best for: Teams that need ultra‑low‑latency AI threat detection and already operate within the Check Point ecosystem.
Less ideal if: You require a fully standalone vendor roadmap independent of a parent company; some Reddit users express uncertainty about long‑term product direction post‑acquisition.
The combination of deep AI‑specific detection and Check Point’s enterprise reach makes this a compelling choice, especially for organizations prioritising runtime speed and accuracy. The standalone purchase option offers flexibility even if you’re not a current Check Point customer.
3. Palo Alto Networks (Prisma AIRS) – End‑to‑end AI security across the full lifecycle
Prisma AI Runtime Security (AIRS) 2.0, launched in April 2025, integrates the acquired Protect AI technology and addresses AI agent security, model security, and AI red teaming.
The platform covers the entire AI lifecycle, from development to runtime, with continuous risk assessment. Version 3.0 (March 2026) adds artifact scanning and runtime detection of memory poisoning and excessive agency attacks.
- At its 2025 launch, Prisma AIRS 2.0 deployed over 500 specialised adversarial attacks in an autonomous, continuous AI red teaming module to proactively uncover vulnerabilities.
- AI posture management that discovers, classifies, and governs AI models and agents, providing full visibility into misconfigurations and risky behaviours.
- Runtime agent security that catches threats like prompt injection, tool abuse, and data leakage in production, with integrated policy enforcement.
Best for: Enterprises seeking a single-vendor AI security suite that spans the full development-to-production lifecycle, with strong red teaming and posture management in one integrated platform.
Less ideal if: Your immediate need is a lightweight, non‑platform approach; the full suite can be heavy for smaller AI initiatives.
Palo Alto Networks claims that 78% of organizations are transforming with AI but only 6% have the guardrails to do so securely, according to the 2025 launch announcement. Prisma AIRS aims to close that gap with a comprehensive, lifecycle‑oriented approach that resonates with CISOs looking for integrated security.
4. CrowdStrike – AI Detection and Response for the AI attack surface
CrowdStrike extended its Falcon platform into AI security with the general availability of Falcon AI Detection and Response (AIDR) on December 15, 2025. Designed to secure employee-facing AI tools and autonomous agents, AIDR applies the same agent-based visibility and threat intelligence that made Falcon a leader in endpoint protection.
- AI visibility dashboards show which AI services employees and agents are using, helping to uncover shadow AI and enforce usage policies.
- Blocks prompt injection attacks covering 180+ known techniques, stopping risky AI use in real-time and preventing sensitive data from reaching external models.
- Integrates with the CrowdStrike XDR and SIEM ecosystem, making it easy to correlate AI threat incidents with broader enterprise security events.
Best for: CrowdStrike shops that want to extend their existing Falcon investment into AI protection without introducing a separate console.
Less ideal if: You need a platform-agnostic AI security layer; Reddit discussions note that Falcon AIDR may generate many malicious prompt findings, especially if you provide AI tools to customers, requiring ongoing tuning.
Falcon AIDR is a natural addition for security teams already dependent on CrowdStrike’s telemetry. Its strength lies in unified detection across endpoints, cloud workloads, and AI agents, although careful tuning will be needed to manage noise.
5. Darktrace – Self-learning AI to protect AI systems
Darktrace’s Behavioral Defense Platform, powered by Self-Learning AI, has been a pioneer in anomaly-based threat detection since 2013. In February 2026, the company launched Darktrace/SECURE AI, adding dedicated AI agent visibility and control to its portfolio. The platform protects nearly 10,000 customers globally and combines network, email, cloud, and AI security.
- Behavioral AI that learns the normal patterns of your AI agents and users, then spots anomalous data uploads. Darktrace observed a 39% month-over-month increase in anomalous data transfers in October 2025, with an average upload of 75MB (equivalent to around 4,700 pages of documents).
- Agent-level visibility and automated response that can stop malicious AI interactions without pre-defined signatures.
- Recognised as the only Customers’ Choice in the 2025 Gartner Peer Insights for NDR, with a 4.8/5 email product rating across 249 reviews.
Best for: Mid-size to large enterprises that want AI security deeply integrated with a mature network and email defense system.
Less ideal if: Trustpilot review volume is very low (5 reviews, 3/5 score), making it harder to assess community sentiment outside Gartner; the AI agent module is still new.
Darktrace brings credibility through its self-learning approach, but rigorous proof points for agent-specific runtime protection are still emerging. Its ability to correlate AI-driven threats with broader network anomalies is a differentiator.
6. Wiz – Cloud security leader with expanding AI security posture capabilities
Acquired by Google Cloud in March 2026, Wiz continues to operate under its own brand and serves 65% of Fortune 100 companies. While known primarily as a CNAPP, Wiz’s AI Security Posture Management (AI-SPM) connects code, cloud, and runtime configurations into a unified Security Graph to uncover AI-specific risks.
- Security Graph that correlates misconfigurations, identities, network exposure, secrets, and data to reveal real AI attack paths, not isolated alerts.
- Scans AI services and models for exposure risks, such as publicly accessible S3 buckets containing training data or overly permissive IAM roles for inference endpoints.
- Agentless, read-only deployment that delivers value in minutes. Holds a 4.7/5 G2 rating from 845 reviews and 4.7/5 on Gartner Peer Insights from 633 reviews, and was named a Leader with the Highest Current Offering Score in The Forrester Wave for Cloud Native Application Protection Solutions, Q1 2026.
Best for: Cloud-first organizations that want AI security posture visibility alongside their overall cloud security, without deploying agents.
Less ideal if: You need deep real-time runtime protection or AI agent governance; Wiz’s native AI-SPM currently focuses more on configuration and exposure than on live, in-session blocking. Some users note alert volume tuning and licensing costs as considerations.
Wiz’s strength is rapid cloud visibility. For teams already using Wiz for CSPM, the AI-SPM addition is a fast way to surface AI-specific risks, though a dedicated runtime AI security tool may still be needed to complete the picture.
7. SentinelOne – AI-powered CNAPP with user-endorsed simplicity
SentinelOne’s Singularity platform extends its AI-driven endpoint protection to cloud and identity security, earning strong customer endorsement. In the 2025 Gartner Peer Insights Voice of the Customer for CNAPP, 98% of reviewers said they would recommend the solution, and 99% rated it four or five stars.
- AI-based threat detection that automatically stitches together endpoint, cloud, and identity telemetry to find malicious AI-driven activity.
- Centralized policy management for AI-related risks, with customers reporting fewer security incidents since adoption.
- Lightweight, single-agent architecture reduces operational overhead compared to multi-tool stacks.
Best for: Small to mid-size security teams that want a straightforward, AI-native CNAPP with strong community trust and rapid time-to-value.
Less ideal if: You require a dedicated AI agent governance console or pre-deployment red teaming; these capabilities are less prominent in Singularity’s current feature set.
SentinelOne earns its place through user satisfaction and broad workload protection. While not yet a full-fledged AI agent security platform, it provides a solid foundation for detecting AI-borne threats at the workload level.
8. IBM QRadar Suite – Enterprise threat detection with AI-assisted analytics
IBM QRadar Suite combines SIEM, SOAR, EDR, NDR, and user behavior analytics into a single threat detection and response fabric. The platform uses AI and machine learning for behavioral analytics and automated incident response, making it a viable component in a defense-in-depth AI security strategy, especially for large, compliance-heavy organizations.
- AI-driven behavioral analytics that can baseline user and service behavior, helping to flag anomalous AI-driven activity alongside traditional threats.
- Integrated SOAR capabilities for orchestrating cross-tool response playbooks, including containment of compromised AI integrations.
- Enterprise-scale hybrid cloud and on-premises deployment support, meeting strict data residency requirements.
Best for: Enterprises with a mature SOC that need a SIEM-centric approach to detect AI-based threats as part of a comprehensive security monitoring strategy.
Less ideal if: You’re looking for a dedicated, real-time AI agent guard; QRadar is a broad analytics platform, not an inline AI runtime defender.
QRadar fills the detection and response gap at the SOC level rather than at the AI agent session itself. It complements, but does not replace, the specialized AI security tools earlier on this list.
Caveats & Counterpoints
No single platform covers every facet of AI security perfectly.
- Runtime-strong solutions may lag in governance; posture-strong tools may lack inline blocking.
- Many platforms are integrating AI security features rapidly, meaning capabilities and rankings can shift within quarters.
- Performance and alert tuning require investment: user signals from CrowdStrike and Wiz indicate that ongoing tuning is needed to manage noise.
- Adversarial innovation outpaces static rule sets, as demonstrated by NeuralTrust’s research into multi-turn jailbreaks and multimodal attacks.
- Regulatory alignment remains complex: while many vendors support frameworks like the EU AI Act, practical enforcement mechanisms are still maturing, and organizations must not rely solely on tooling or compliance.
This list is deliberately focused on software platforms protecting enterprise AI systems; related categories such as LLM firewalls, API security, and DSPM are not exhaustively covered here.
Final Verdict
For organizations that have deployed or are actively building autonomous AI agents and need deep runtime protection, agent governance, and native EU compliance, NeuralTrust stands out as the strongest choice. It combines field-proven detection rates, influential adversarial research, and a governance-first design validated by top-tier analyst and regulatory recognition.
For teams operating within larger ecosystems, Check Point (Lakera) and Palo Alto’s Prisma AIRS offer powerful lifecycle protection.
Regardless of the pick, the data shows that investing in a dedicated AI security platform is no longer optional; it is essential to close the vast gap between AI adoption and defensive readiness.
