4 Top-Rated AI Cybersecurity Tools
Due to growing cyberthreats, your security team may find it challenging to distinguish genuine threats from false positives. Traditional security tools often fail to keep up with evolving threat actors, preventing timely detection and response to security incidents.
AI-enabled cybersecurity tools use machine learning [1] algorithms and natural language processing [2] to analyze vast amounts of data and identify patterns indicative of malicious activity in real time. These tools prioritize security threats based on their severity and real-time likelihood of posing a genuine threat.
This article lists four top-rated AI cybersecurity tools based on verified user reviews and our research team’s analysis, sorted alphabetically. Per our research, all featured products are dedicated AI cybersecurity tools that offer threat detection, incident response, and vulnerability management to standardize IT security operations and improve cybersecurity infrastructure.
We selected products for this article based on their average ratings between February 2022 and February 2024, which may differ from their current overall average ratings.
1. Flashstart
Flashstart is a domain name system (DNS) filtering solution that uses machine learning models to analyze web traffic and domain data and classify it into various security categories (e.g., malware, phishing, gambling). This AI-powered tool automates response actions based on the nature of the detected threat. It blocks malicious websites, quarantines suspicious files, and alerts the security team about potential incidents. Additionally, it uses previous encounters with malicious content and user behavior patterns to identify similar patterns and detect threats yet to be categorized or flagged.
AI-enabled cybersecurity features:*
Granular filtering: Block and categorize websites into subcategories (e.g., online casinos, sports betting platforms) based on their specific content and functionality. You can also set up website access restrictions for your employees.
Geolocation-based protection: Fine-tune the machine learning algorithm to detect and block access to websites hosted in specific countries or regions with a high risk of cyberthreats and phishing.
Network usage reports: Access auto-generated network usage reports that provide insights into traffic patterns, user activity, and resource utilization. These reports help monitor and optimize network performance and detect unauthorized or suspicious activities.
Starting price: Available upon request from the vendor
Customer support options: Email, knowledge base, and live chat
Who should consider Flashstart’s AI capabilities?
Flashstart could be a viable option for IT security teams seeking location-based cybersecurity protection. Traditional website filtering methods rely on content-based analysis to identify potential threats, often missing out on threats originating from regions known for harboring malicious actors or hosting phishing websites. By leveraging machine learning, Flashstart’s geolocation-based protection proactively detects and blocks access to such regions, reducing the likelihood of cyberattacks.
2. Heimdal Threat Prevention
Heimdal Threat Prevention is a cybersecurity suite that uses machine learning techniques, such as character-based neural networks and AI linguistic analysis, to analyze various data points, including domain names, domain registration details, historical data on similar domains, and language patterns used in domain names. Based on this analysis, it identifies malicious domains, predicts potential threats, and blocks viruses. Additionally, it uses an AI-powered host-based intrusion prevention system to monitor and prevent suspicious activity on individual devices, including personal computers (PCs) and laptops. It performs real-time analysis of network traffic and endpoint activity to detect and block phishing attempts, suspicious file downloads, and attempts to access unauthorized resources or malicious websites known to host malware.
AI-enabled cybersecurity features:*
Automated response: Leverage AI to automate responses based on the identified threat level and type. These responses include isolating the infected endpoint from the network, blocking access to a malicious URL or IP address, and quarantining a suspicious file to prevent further harm.
AI-assisted prioritization: Analyze security vulnerabilities and prioritize them based on potential impact, exploitability, and the likelihood of being targeted. The software also automates patch updates and deployments, leveraging AI to determine the optimal time for updates with minimal disruption.
Malware detection: Use signature-based detection to identify known malware based on predefined patterns and heuristic analysis. This feature also analyzes file behavior and characteristics to detect unknown malware.
Starting price: $59.95 for three PCs
Billing cycle: Annual
Customer support options: Call, knowledge base, and live chat
Who should consider Heimdal’s AI capabilities?
Small-business IT security teams with limited bandwidth can consider Heimdal Threat Prevention to automate the analysis of high volumes of security alerts and vulnerabilities. Its prioritization feature eliminates manual processing by leveraging AI to analyze and prioritize vulnerabilities according to their potential impact, exploitability, and likelihood of being targeted. It enhances the security posture of such teams by enabling security managers to focus resources on addressing the most critical threats first.
Pro tip
Assess your business’s unique cybersecurity requirements, including the types of potential threats, the sensitivity of your data, and your existing cybersecurity infrastructure. This analysis will allow you to narrow down your options and choose an AI solution that aligns with your specific cybersecurity needs, maximizing its effectiveness in enhancing your organization’s security posture.
3. Orca Security
Orca Security is a cloud security solution that eliminates misconfigurations, vulnerabilities, and data security risks within your cloud environment. It uses generative AI to analyze the context of detected threats and vulnerabilities (e.g., affected resources, potential impact) and suggest appropriate remediation steps. You can also manually raise a request for remediation, and the software anonymizes the request to ensure sensitive data is not exposed during the remediation process. Orca’s AI-powered asset search lets you identify security vulnerabilities and locate compromised assets within your cloud environment using natural language prompts (e.g., “Find all database instances with outdated access controls”). This AI feature can interpret synonyms, recognize different phrasings, and understand the context of your inquiry.
AI-enabled cybersecurity features:*
IAM policy: Use machine learning to analyze existing identity and access management (IAM) policies and their usage patterns. Based on this analysis, Orca provides recommendations to optimize IAM policies to improve security.
AI-generated alerts and asset descriptions: Generate summarized descriptions of alerts received and assets affected, including risks found, severity, and possible remediations. These AI-generated descriptions help reduce investigation time and improve the average remediation time.
AI anomaly detection: Leverage AI to analyze your cloud environment and identify anomalies in data (e.g., misconfigurations, unusual activities). The tool compares current activity against past usage patterns to identify deviations that could be suspicious.
Starting price: Available upon request from the vendor
Customer support options: Knowledge base
Who should consider Orca Security’s AI capabilities?
Orca Security is worth considering for IT security managers looking to strengthen cloud security infrastructure and policies. Its AI anomaly detection scans the cloud environment, providing visibility into potential threats, such as misconfigurations, vulnerabilities, and data security risks. Additionally, its generative AI feature analyzes the context of security threats, including affected resources, potential impact, and relevant security policies. Based on this analysis, it suggests appropriate remediation steps. It also anonymizes requests for remediations and masks sensitive data, ensuring security measures are implemented without compromising data confidentiality or privacy.
4. SentinelOne
SentinelOne is a cybersecurity suite with an integrated generative AI tool called Purple AI. You can enter commands in plain English, and Purple AI translates them into technical queries to search for endpoint, cloud environment, container, and IoT threats and prioritize them based on the severity level. It provides a summary of the threats identified, including details about the type of threat, the behavior observed, and any relevant attack indicators (IOCs). It also recommends appropriate response actions for each threat and lets you execute these responses directly within the system.
AI-enabled cybersecurity features:*
Pre-execution prevention: Use machine learning to inspect a program or file before running it. This inspection includes analyzing the source, behavior patterns, and code characteristics of the file, helping identify malicious behavior even in unknown threats and zero-day attacks.
AI insights: Analyze security events and threat data to produce human-readable insights, including the tactics, techniques, and procedures (TTPs) used in the attack. SentinelOne employs AI models to identify patterns and understand the context and relationship between threat events.
Data security: Leverage data isolation and transient data retention to protect your data. Your sensitive information remains confidential and is not used to improve the AI for other customers. Both prompts (your natural language queries) and returned responses (AI-generated replies) are not permanently stored in the system.
Starting price: $69.99 for five to 100 workstations
Billing cycle: Monthly
Customer support options: Call, email, knowledge base, and live chat
Who should consider SentinelOne’s AI capabilities?
IT security teams concerned about maintaining customer privacy in AI-powered solutions that analyze large volumes of sensitive security data can consider SentinelOne. Purple AI doesn’t save or use customer data to train AI models for other customers. This capability ensures specific security events and insights remain confidential to the organization, preventing accidental exposure or misuse. By not permanently storing prompts and AI-generated responses, SentinelOne reduces the risk of sensitive information persisting within the system for extended periods, minimizing the impact of potential data breaches or unauthorized access.
Pro tip
Check the AI system's accuracy in distinguishing between genuine threats and benign activities. Look for tools that minimize false alarms and missed detections by fine-tuning their algorithms. Software solutions with low false positive and false negative rates reduce alert fatigue and ensure security teams can focus on genuine threats, thereby improving operational efficiency and effectiveness.
What are the benefits of using cybersecurity tools with AI capabilities?
AI cybersecurity tools enhance security infrastructure, improve threat detection and response, and standardize cybersecurity operations. Below, we discuss some common benefits of AI-enabled cybersecurity software based on its features.
Benefit | Description |
|---|---|
Advanced threat detection | Cybersecurity tools with machine learning algorithms, including supervised and unsupervised learning techniques, alongside anomaly detection methods, can identify and analyze complex patterns and anomalies in network traffic or user behavior. These capabilities help detect potential threats, such as compromised user accounts or malware infections, that traditional rule-based or manual methods might miss. |
Automated incident response | AI-powered cybersecurity tools can automatically respond to security incidents, such as network intrusions, data breaches, and distributed denial-of-service (DDoS) attacks, by isolating the affected systems, blocking malicious activity, and initiating remediation actions. This automation reduces response time and minimizes the impact of cyberattacks. |
Predictive analytics for risk management | By leveraging machine learning algorithms, AI cybersecurity tools can forecast potential security risks and anticipate future attack vectors based on historical data and current trends. This feature enables your business to preemptively implement security measures and stay ahead of cyberthreats. |
How much does AI cybersecurity software cost?
Cyber security software solutions with AI capabilities can cost as low as $7.99 per month or up to $389+ per month depending on various factors, including the required AI capabilities, number of users, reporting and analysis, and integration options. Most AI cybersecurity tools typically include the following pricing plans:
Free trials: Range from seven to 30 days and give users access to either all or limited AI features of the software. These no-cost trial plans are ideal for users who wish to try out a tool before purchasing it.
Free versions: Offer perpetual access to basic AI cybersecurity features, including threat and anomaly detection. These free plans are ideal for small businesses or security teams on a budget.
Entry-level plans: Start at $7.99 per month and provide access to standard features. These are suitable for businesses with basic AI cybersecurity needs, such as malware detection, phishing prevention, and firewall protection.
Mid-tier plans: Range from $25 to $180 per month and offer advanced AI-enabled security features, such as real-time threat intelligence, automated incident response, and adaptive security measures. These are suitable for businesses that have outgrown entry-level cybersecurity tools but don’t require the full range of functionality provided by enterprise-level systems.
High-end plans: Cost more than $389 per month and offer a range of advanced AI capabilities, including unlimited access to entry-level and mid-tier features, predictive analytics, and contextual threat prioritization. These plans are suitable for larger enterprises with extensive cybersecurity requirements.
Hidden costs associated with AI cybersecurity software
Besides the software license, additional costs can include:
Implementation and integration: Integrating AI cybersecurity software with your existing IT infrastructure may require additional resources, such as consulting services, customization, and integration with other security tools or platforms. These costs can vary depending on the implementation complexity and the customization level required.
Maintenance and updates: Ongoing updates are essential to keep AI cybersecurity software up to date and effective against evolving threats. This may involve subscription fees for access to the updates, patches, and technical support services the software vendor provides.
Data storage and processing: AI cybersecurity software often requires computational resources for data storage and processing, especially when dealing with large volumes of data. Depending on your business requirements, you may need to invest in additional storage capacity or cloud computing resources, which can contribute to the overall cost.
Frequently asked questions when selecting AI cybersecurity software
Here are some common questions to ask software vendors:
What data sources does the software utilize for threat detection?
AI cybersecurity tools use various data sources to identify and mitigate security risks. These sources can include network traffic data, endpoint logs, and user behavior data. Network traffic data provides insights into communication patterns, anomalies, and potential intrusions within your network infrastructure. Endpoint logs provide information about activities and events occurring on individual devices, helping identify malicious behavior or unauthorized access attempts. Similarly, user behavior data monitors and analyzes actions and patterns of user activity, detecting insider threats or abnormal behavior. Having access to all of these data sources will better equip your security team to leverage the AI tool for determining threat mitigation strategies.
What level of human oversight or intervention is required?
While AI can automate routine malware and anomaly detection, human intervention is often necessary for complex threat analysis, incident response coordination, and strategic decision-making. Additionally, human analysts contribute their domain knowledge and experience to refine AI algorithms, validate machine learning models, and improve the effectiveness of the cybersecurity program. When evaluating AI cybersecurity solutions, understand the extent to which human analysts are involved in the decision-making process and how the AI software complements human expertise in cybersecurity operations.
How does the software handle privacy and compliance concerns?
Ask the software vendor about the encryption mechanism used to protect sensitive data and the access controls implemented to restrict data manipulation to authorized personnel. Inquire about the use of anonymization or pseudonymization techniques to minimize privacy risks associated with personally identifiable information (PII) and sensitive data. Additionally, determine whether the software complies with relevant privacy regulations and industry standards, such as the General Data Protection Regulation (GDPR) or Health Insurance Portability and Accountability Act (HIPAA), by implementing appropriate data protection measures and ensuring transparency in data handling practices.
Methodology
To be considered for this list, products had to:
Have at least 20 unique product reviews published on Software Advice within the past two years, with an average rating of 3.0 or higher (as of Feb. 26, 2024).
Meet our market definition for cybersecurity software: “Cybersecurity software aims to prevent unauthorized access to data that is stored electronically. This type of software protects businesses from data theft, malicious data, and system usage by third parties.”
Show evidence of offering AI capabilities as demonstrated by publicly available sources, such as the vendor’s website.
*Our research team identified these features from vendor websites, as of Feb. 26, 2024, based on their analysis of what users find valuable in or expect from AI-enabled cybersecurity software. This list is not exhaustive. For additional capabilities, refer to the vendor's website.
Research for this article was provided by Akriti Sharma.
For the section titled “How much does AI cybersecurity software cost?,” only products with publicly available pricing information and AI features, as of Feb. 26, 2024, were considered for pricing calculations.
Editorial independence: We select and rank products based on an objective methodology developed by our research team. While some vendors may pay us when they receive web traffic or leads, this does not influence our methodology.
Definitions
Machine learning is a computer science that uses data to learn in the way humans do. It is a category that falls under artificial intelligence (AI). ML uses data and algorithms for different technologies, including deep learning, neural networks, and natural language processing (NLP). By analyzing data, machine learning can learn patterns and make decisions without the need for human intervention.
Natural language processing (NLP) is an artificial intelligence technology that enables computers to understand human language. Computers do so by analyzing text and extracting meaning from it to perform tasks such as translating languages and understanding questions posed in natural language.