Radware AI Security Suite Reviews

My main use case for Radware AI Security Suite is to protect our environment using this as a primary solution for productivity automation and getting insights from large data sets, as AI is becoming more granular at an organization level.

I use Radware AI Security Suite to automatically analyze web traffic patterns and distinguish legitimate user traffic from potential layer 7 DDoS attacks and bot activity.

Several factors prompted my organization to explore solutions like Radware's Agentic AI Protection at this time, as we are increasing our digital footprint and reliance on web applications and APIs, needing stronger protection against evolving threats such as DDoS attacks, malicious bots, and API abuse.

Our primary concern when considering Radware's Agentic AI Protection was data leakage and unauthorized exfiltration of sensitive information, making sure that confidential business data, customer information, and internal knowledge are not unintentionally exposed through AI interactions a key priority.

Radware AI Security Suite has positively impacted my organization primarily through improved visibility and faster threat response, as it helps me quickly identify abnormal traffic, malicious bots, and potential DDoS activity with minimal investigation.

Radware AI Security Suite has significantly reduced the time needed to identify and investigate suspicious traffic through real-time detection and automated analysis.

The best features that Radware AI Security Suite offers include cloud DDoS protection, advanced bot management, behavior analytics, API protection, centralized visibility, and reporting.

I find AI-powered DDoS detection and mitigation to be the most valuable feature day-to-day, as it automatically defines abnormal traffic patterns and mitigates attacks in real-time, helping my team reduce false positives, respond faster, and spend less time on manual traffic analysis.

I find Radware AI Security Suite's AI governance and security capabilities to be strong, as the platform provides visibility into threats, automated mitigations, and behavioral analysis while helping the security team maintain control over predictive actions.

In my observation, Radware AI Security Suite delivers a high level of accuracy and reliability in detecting abnormal traffic, DDoS activity, and malicious bot behavior, as its AI-driven analysis helps to prioritize genuine threats and reduces the number of false positives compared to traditional rule-based approaches.

Radware's LLM firewall helped address risks such as prompt injection attacks, sensitive data leakage, and unauthorized access to confidential information through input and output inspection, policy enforcement, and enhanced visibility into AI interactions.

Radware AI Security Suite is very effective, but I believe that enhanced dashboard customization, reporting flexibility, and deeper integration with third-party security tools would make it even stronger.

The point I took off was for customization, and report customization remains the primary area where improvements could be beneficial.

I have been using Radware AI Security Suite for one year.

Radware AI Security Suite is stable.

Scalability has been excellent for Radware AI Security Suite, as it handles growing traffic volumes and application and API demands effectively while maintaining visibility, performance, and security controls.

The customer support for Radware AI Security Suite is great, and I would rate the customer support a 10.

I have not previously used a different solution.

My decision between API integration and code proxy integration for sensitive agent actions was influenced by balancing security, deployment complexity, performance, and the sensitivity of the protected AI agent action.

I have seen a positive return on investment primarily through time saving and improved operational efficiency, as the platform has reduced the effort required to identify, investigate, and respond to security events.

Our experience with the pricing, setup, and licensing was generally positive, as the license model was clear and the deployment process was straightforward with support from the Radware team.

During the evaluation, the most valuable demonstrations were those showing the ability to detect and block prompt injection attempts, prevent sensitive data exposure, and provide visibility into AI interactions.

I reviewed several alternatives as part of my evaluation process, including offerings from major application and API security vendors.

I would rate Radware AI Security Suite a 9 out of 10, as its AI-driven DDoS protection, bot mitigation, and real-time threat detection provide strong security and operational benefits, with the only area of improvement being enhanced reporting customization.

Before I started using Radware's Agentic AI Protection, my understanding of potential risks, such as Shadow AI or tool misuse, shifted as I began evaluating dedicated AI security solutions.

My advice to others looking into using Radware AI Security Suite is to clearly define security objectives and use cases before deployment.

Radware AI Security Suite is used primarily to protect web applications and APIs from evolving cyber threats while maintaining application availability and performance. In day-to-day operations, it is relied upon most for real-time threat detection, automated attack mitigation, and security monitoring, which helps the security team to quickly identify and respond to suspicious activity with minimal manual effort.

For example, a sudden spike in suspicious requests targeting a public-facing application was recently observed. Radware AI Security Suite automatically identified the traffic as a bot-driven attack, blocked the malicious request in real-time, and alerted the security team. This helped to prevent potential service disruption while allowing legitimate users to access the application without any noticeable impact.

Beyond the threat application, Radware AI Security Suite has helped to reduce the time spent on manual analysis and incident response. Its AI-driven insights and automated mitigation capabilities allow focus on higher-priority security initiatives while maintaining continuous visibility into application and API threats. This has improved operational efficiency, reduced alert fatigue, and strengthened the overall security posture.

The key drivers for exploring solutions like Radware's agentic AI protection include the growth of web applications and APIs, increasing threat sophistication, and the need to reduce manual security operations. A solution was needed that would provide intelligent automated protection at scale, and Radware's agentic AI capabilities aligned well with those requirements.

When considering Radware's agentic AI protection, the priority was preventing data leakage. As data leakage was the highest priority concern, a solution was needed that could help protect sensitive information, provide visibility into AI activity, and detect abnormal behavior before it could result in data exposure and security incidents.

Radware AI Security Suite has had a significant positive impact on the organization. It has improved the ability to detect and mitigate threats in real time, reducing the risk of application downtime and security incidents. The automation and AI-driven analytics have decreased the amount of manual investigation required, allowing the security team to respond more quickly and focus on strategic initiatives rather than routine monitoring. From an operational perspective, improved visibility into web application and API threats, faster incident response times, and a noticeable reduction in alert fatigue have been observed. Overall, the platform has strengthened the security posture while improving the efficiency and productivity of the security operations team.

Since implementing Radware AI Security Suite, approximately 40 to 50% faster incident investigation and response times have been achieved due to the automated threat detection and mitigation. The platform has also helped reduce the number of security events requiring manual analysis by around 30 to 40%, allowing the team to focus on higher priority tasks. Improved visibility into web application and API threats has led to quicker identification of suspicious activity and a stronger overall security posture.

Radware's LLM Firewall has had little to no noticeable impact on user experience while providing strong protection against AI-specific threats. It helps secure AI interactions, reduce risks, and maintain performance, allowing users to work without disruption while improving overall governance and security.

Since deployment, Radware's LLM Firewall has primarily helped to block prompt injection attacks, unauthorized data access attempts, sensitive data leakage risks, and unsafe AI outputs. The biggest benefit has been preventing confidential information from being exposed while maintaining a smooth user experience.

The best features of Radware AI Security Suite are its AI-driven threat detection and mitigation that automatically identify and block sophisticated attacks in real time. Another valuable feature is the advanced bot protection to prevent credential stuffing, scraping, and other automated concerns. Comprehensive API security with continuous monitoring and protection for modern applications is also provided, as well as behavioral analytics, risk-based detection, and a centralized dashboard with reporting.

The most valuable feature is the AI-powered threat detection and automated mitigation capabilities, as they help stop attacks quickly and minimize the workload on the security team. The automated response capabilities reduce manual effort and enable faster incident remediation.

The governance and security rating for Radware AI Security Suite is very good. It demonstrates strong governance and security capabilities by combining AI-driven analytics with controlled policy-based and security enforcement. The platform provides clear visibility into detected threats, supports audit and reporting requirements, and helps security teams maintain consistent protection across applications and APIs.

From the security perspective, I appreciate that the AI focuses on identifying anomalies and reducing false positives while automating mitigation actions, all while allowing administrators to review and fine-tune policies. This balance between automation and human oversight helps build trust in the platform and its recommendations and decisions.

The AI capabilities of Radware AI Security Suite have been reliable and consistent, demonstrating strong threat detection accuracy and fewer false positives than traditional approaches. It provides actionable alerts, helps prioritize real risks, and improves overall operational efficiency for the security team.

The platform is highly effective, but enhanced dashboard customization, more third-party integration, and greater flexibility in reporting and policy management would make it even better.

More native integrations with SIEM, SOAR, and ticketing platforms would be specifically valuable to streamline incident management and automated workflows. Greater flexibility in dashboard customization, including role-based views and more granular reporting options, would also be beneficial. Additionally, enhanced API-level visibility with more pre-built, comprehensive compliance and executive reporting templates would help security teams extract insights faster and reduce administrative effort. Overall, these improvements would further enhance operational efficiency and the user experience.

One additional improvement Radware AI Security Suite needs is more detailed AI explainability, allowing security teams to better understand why certain threats are flagged and what factors contribute to the AI decisions. This would help build greater confidence in automated actions and simplify investigations. More predictive threat intelligence capabilities, enhanced executive-level reporting, and additional pre-built automation workflows for common security use cases would also be valuable. While the platform is already very capable, these enhancements would make it even more efficient and valuable in security operations.

Radware AI Security Suite has been used for two and a half years.

Radware AI Security Suite is stable.

Its scalability is rated nine out of ten.

The customer support is good. Customer support is rated a nine on a scale of one to ten.

No previous solutions have been used.

In integrating Radware's agentic AI protection, visibility, security controls, and ease of deployment were prioritized. Out-of-the-path integration provided quick deployment with minimal operational project impact, while API-based integration offered deeper inspection and stronger governance for sensitive agent actions. The choice depended on the risk level of the workload and the required level of control.

The organization prioritized connecting with Microsoft Copilot first due to its widespread business use case and access to organizational data, securing AI interactions, monitoring potential risks, and maintaining governance around sensitive information, which were the primary objectives before extending protection to other AI platforms and internal agents.

The initial integration of Radware AI Security Suite required approximately five to ten person-days of engineering effort, including configuration, testing, and policy tuning. The implementation was smooth and required minimal disruption to existing workflows.

Before choosing Radware AI Security Suite, several alternatives were evaluated including Microsoft, Palo Alto Networks, Cloudflare, and F5, along with native platform controls. Radware stood out due to its AI-focused security capabilities, LLM protection, automation, and comprehensive visibility across AI applications and APIs.

My overall rating for Radware AI Security Suite is nine. I chose a nine for my overall rating because Radware AI Security Suite provides strong protection, effective AI-driven threat detection, and valuable automation capabilities that have improved security operations. The platform delivers excellent visibility into web application and API threats while reducing manual effort for the security team. I deducted one point only because there is still room for improvement in dashboard customization, reporting flexibility, and third-party integrations. Overall, it is a reliable and highly effective security solution that has brought significant value to the organization.

Radware AI Security Suite is a strong choice for organizations adopting AI technologies and looking to improve visibility, governance, and protection against AI-specific threats. Start with the most critical use case and take advantage of its automation capabilities while continuously refining policies to maximize value and achieve the best results.

Radware AI Security Suite protects our AI-powered application in Microsoft Copilot's deployments from AI-specific threats, ensuring our governance, visibility, and real-time security monitoring.

Radware AI Security Suite helps with governance, visibility, and real-time security monitoring in our Copilot deployment by providing us a centralized view of AI applications and tools, along with user interaction across our environment, helping us understand which AI services are being used and how they are connected.

Our main use case is to continuously monitor AI activity and identify risky behavior or misconfiguration, and Radware AI Security Suite is helping us with that.

Several internal and external factors prompted our organization to explore solutions like Radware's Agentic AI Protection, including increased adoption of AI technology, such as Microsoft Copilot and other AI-powered applications, creating a need for stronger governance, visibility, and security controls, as well as the awareness of AI-specific threats such as prompt injection, jailbreaking, and unauthorized tool uses highlighting gaps that necessitated a protective security approach.

The main risk area my organization prioritized when considering Radware's Agentic AI Protection is data leakage, as protecting sensitive data has become a key requirement due to increased use of AI tools including Copilot and other AI agents' applications.

The most critical LLM-related risks my organization prioritized addressing with Radware's LLM Firewall include prompt injection attacks and sensitive data leakage, as AI agents have become a crucial part of our organization, necessitating a data control tool to prevent exposing confidential business data.

From the security perspective, Radware AI Security Suite positively impacts our organization by providing real-time monitoring and behavioral analytics capabilities that help us identify suspicious activities, prompt injection attacks, unauthorized access patterns, and abnormal AI agents, improving our ability to detect and respond to potential threats before they can affect our business.

One of the most significant benefits since implementing Radware AI Security Suite has been faster detection and response to AI-related security events, as the behavioral analytics and real-time monitoring capabilities help our security team identify anomalous activity, such as suspicious prompts and unusual access patterns, facilitating earlier investigations.

Upon activating Radware's Agentic AI Protection, the number of agents identified in our environment compared to prior estimates showed that while we had visibility into officially approved AI tools, Radware's solution helped identify additional agent integrations and AI-driven workflows being used across different teams.

Radware's Agentic AI Protection revealed unexpected insights about our internal network topology, including previously undocumented AI-related connections and workflows in our environment.

The best feature Radware AI Security Suite offers is AI agent discovery and visibility, along with behavioral analytics, LLM firewall capabilities, and real-time runtime protection, providing a centralized view of AI agent tools and interactions, making it easier to govern and secure AI deployments.

The behavioral analytics capability is one of the most valuable aspects in this tool because it focuses on how user and AI agents' applications behave rather than relying solely on predefined signatures, continuously monitoring AI interactions and identifying unusual patterns with the detection of potential risky activities, such as prompt injections or attempts, and abnormal agent actions.

It also detects unauthorized tool uses and data access behavior.

The governance and security aspects of Radware AI Security Suite help security teams by clarifying AI agents, tools, interactions, and dependencies, as well as identifying potential risk before a security incident, maintaining the inventory of AI assets, mapping relationships between agents and tools, monitoring usage patterns, and generating compliance-oriented reports.

In terms of accuracy and reliability, particularly in behavioral analytics, threat detection, and AI runtime protection, these are highly accurate capabilities of Radware AI Security Suite. Regarding reliability, it does not rely solely on static signatures but analyzes behavior, intent, and interaction across AI agents, tools, and users, improving detection quality and reducing unnecessary alerts.

Radware AI Security Suite is a strong tool, but it could be improved in the customization of the dashboard and reporting, which would help us tailor the views for different stakeholders and compliance requirements.

I have been using Radware AI Security Suite for one year.

Radware AI Security Suite is stable.

The scalability of Radware AI Security Suite is very good.

Customer support for Radware AI Security Suite is good and promptly supportive. I rate the customer support a ten out of ten.

I did not previously use a different solution.

The factors influencing our decision between API integration (out-of-path) and code proxy integration (in-path) for sensitive agent actions included security, deployment complexity, performance impact, and visibility.

We have seen a return on investment with Radware AI Security Suite, particularly in terms of time saved.

My experience with pricing, setup cost, and licensing for Radware AI Security Suite has been very good overall, with positive impressions regarding licensing and cost.

We evaluated other options before choosing Radware AI Security Suite, but details about those options are confidential.

I rate Radware AI Security Suite a nine out of ten. I rated it a nine because it provides strong visibility, governance, and real-time protection for AI environments while helping address emerging threats such as prompt injection, jailbreak attacks, and data leaks, and its behavioral analytics, AI agent discovery, and runtime protection capabilities give our security team greater confidence in managing Copilot and other AI agent deployments. My advice for others looking into using Radware AI Security Suite is to start with visibility and governance objectives before focusing solely on threat prevention, as adopting this solution will help with understanding which AI agent tools and integrations are open within the environment, making it very helpful for any kind of organization.

Radware AI Security Suite is deployed primarily to secure internet-facing applications and APIs.

Radware AI Security Suite helps protect threats in real-time, improve visibility, and automate the security response, enabling faster and more effective protection against cyber attacks.

The main driver for my organization to explore solutions like Radware's Agentic AI Protection at this time is the growth of our digital applications, increasing security risk, and the need for better visibility and automation.

Before deploying Radware's Agentic AI Protection, our understanding of potential risks evolved to include risks such as Shadow AI, unauthorized AI access, and potential data leakages, as we had mostly focused on traditional cyber threats.

When considering Radware's Agentic AI Protection, our organization prioritized data leakages among concerns of data leakage, tool misuse, or unidentified agents.

We identified sensitive data leakage, prompt injection, and unauthorized use of AI tools as the most critical LLM-related risks to address with Radware's LLM Firewall as AI adoption grew and we needed better visibility and controls to ensure our business data remained protected.

Radware AI Security Suite has had a positive impact on our organization by improving our ability to detect and respond to threats quickly.

Security has improved visibility, accelerated threat detection, and reduced manual workload, which has helped us operate more efficiently and maintain a stronger security posture across our applications and APIs.

The best features Radware AI Security Suite offers include the threat detection and visibility it provides across our environment, helping us to spot unusual behavior quickly, reduce the time spent on manual investigation, and enable a faster response to security incidents.

For our team, the crossover environment means having a clear view of what's happening across all our applications and APIs without switching between multiple tools, which helps us quickly identify unusual traffic patterns and suspicious behavior that may indicate a security issue.

The AI capabilities of Radware AI Security Suite strike a good balance between automation and human oversight, helping us detect threats faster and reduce manual effort while still allowing our team to review and validate important security decisions.

We have found the AI capabilities of Radware AI Security Suite to be accurate and reliable for detecting suspicious activity and highlighting potential risks.

Radware AI Security Suite works well overall, but I would like to see some flexibility in dashboards and reporting, and deeper integration with other security tools.

I have been using Radware AI Security Suite for over one year.

Radware AI Security Suite is stable.

The scalability of Radware AI Security Suite is pretty good.

Radware AI Security Suite's customer support is pretty supportive. I would rate the customer support a ten out of ten.

I previously used a different solution, but that information is confidential.

We evaluated the factors influencing our decision between API integration, out-of-path, and code proxy integration, in-path, for sensitive agent actions based on security, deployment effort, visibility, and impact on existing applications.

We have seen a return on investment with Radware AI Security Suite, and it is a time-saving product.

My experience with pricing, setup cost, and licensing is that it is good and a worthwhile product.

We have evaluated other options before choosing Radware AI Security Suite, but that is also confidential data.

I would rate Radware AI Security Suite a nine out of ten. I chose nine out of ten because the solution has been reliable and effective, delivering strong value by improving our security operation through advanced threat detection, visibility across applications and APIs, and automation capabilities that help our team identify and respond to threats more quickly while reducing manual effort.

Radware AI Security Suite is deployed in our organization using the public cloud.

Radware is used as our cloud provider.

The POC provided confidence in Radware's ability to protect our AI agent environment by showing how the platform could detect AI-specific threats, monitor AI interaction, and identify potential data exposure risks in real time.

My advice to others looking into using Radware AI Security Suite is to start with a clear understanding of your AI security goals and run a proof of concept using your own use cases. The overall product rating for Radware AI Security Suite is nine out of ten.