Cato SASE Cloud Features

Take away need to manage separate overlay and underlay networks.

Enable network connectivity to private and public data sources.

Provide high availability and load balancing.

Allow for seamless integration of apps.

Improve application performance.

Monitor the health of your applications.

Self-heal application issues.

Simplify application deployment.

Reduce operating expenses.

Allows administrative control over network components, mapping, and segmentation.

Allows visual display of networks segmented components and their connected resources.

Utilizes behavioral analysis to improve security procedures and documentation.

Application Programming Interface - Specification for how the application communicates with other software. API's typically enable integration of data, logic, objects, etc. with other software applications.

Protects application access and data. Prompts additional authentication for suspicious users.

Protects computing resources across a network. Prompts additional authentication for suspicious users.

Protects informatin stored on premises and in the cloud. Prompts additional authentication for suspicious users.

Allows users to create, edit, and relinquish user access privileges.

Stores data securely either on premise or in an adjacent cloud database to prevent loss of data at rest.

Manages policies for user data access and data encryption.

Supports LDAP Protocol to enable access control and governance.

Encrypt data to and from the cloud and on cloud storage devices

Prevent and monitor unauthorized access, misuse, modification, or denial of a computer network and network-accessible resources

Identify and respond to security threats to cloud applications

Detect and prevent data breaches, exfiltration, or unwanted destruction of sensitive data.

Collection of processes, policies, and standards to manage the storage & usability of enterprise data

Provides a risk-based approcach to determining trust within the network.

Calculates risk based on user behavior, permissions, and requests.

Monitors users attempting unauthorized access to databases, applicaitons, and othe network components.

Allows for reporting and documentation of individual user behavior and privileges.

Analyzes data associated with denied entries and policy enforcement, giving information of better authentication and security protocols.

Monitors acivity related to user behavior and compares activity to benchmarked patterns.

View and track pertinent metrics to find patterns and gain insights from data

Track and interpret metrics on the usage of company resources

Provides a single access point for users to access multiple cloud products without multiple logins.

Details SaaS products the cloud security product can integrate with and provide security for.

Offers the ability to set standards for types of mobile devices and networks capable of accessing data.

Offers data loss prevention tools to protect data from leaving the environments it is allowed to.

Scale resources automatically, adjusting for usage demands.

Enables administrators to create access policies and applies policy controls throughout request and provisioning processes

Provides advanced data center network services to deliver multiple high-speed IP.

Allows users to track and control activity across cloud services and providers.

Constantly monitors system to detect anomalies in real time.

Managed, cloud-delivered firewall that protects devices, assets, networks, and other cloud services from web-based threats.

Provides a single access point for users to access multiple cloud applications, services, and products through a central gateway

Provides a private web gateway for secure internet browsing.

Provides a risk-based approach to determining trust within the network.

Condenses long documents or text into a brief summary.

Allows users to generate text based on a text prompt.

Provides centralized control and monitoring via API or dashboard

Ensures compatibility with various cloud infrastructures

Dynamically adjusts network resources based on business needs

Includes encryption, firewalls, Zero Trust, and compliance policies

Adheres to industry regulations like HIPAA, GDPR, and SOC 2

Provides real-time attack detection and mitigation

Monitors performance in real-time and prioritizes critical applications

Enhances traffic routing, load balancing, and overall efficiency

Automates network setup and reduces manual intervention

Adapts security and network policies dynamically based on user behavior

Uses AI to continuously assess and respond to emerging threats

Uses AI and ML to predict congestion and optimize traffic

Provides VPN-like encrypted connectivity without physical hardware

Enables high-speed, low-latency connections for enterprise networks

Extends network services to the edge for lower latency

Adapts security and network policies dynamically based on user behavior

Uses AI to continuously assess and respond to emerging threats

Uses AI and ML to predict congestion and optimize traffic

Enforces zero trust access rules.

Integrates wide area network (WAN) capabilities, such as SD-WAN.

Enforces security requirements and secures connections with cloud resources.

Prevents unauthorized web domains from entering a network and protects against web-based threats.

Provides cloud-based firewall protection.

Uses predictive analytics to anticipate emerging threats.

Utilizes AI algorithms to identify anomolies and block access to malicious sites.

Automates common workflows and remediation tasks.

Capability to perform complex tasks without constant human input

Works across multiple software systems or databases

Anticipates needs and offers suggestions without prompting

Makes informed choices based on available data and objectives

Prevents unauthorized web domains from entering a network and protects against web-based threats.

Provides cloud-based firewall protection.

Enforces zero trust access rules.

Enforces security requirements and secures connections with cloud resources.

Automates common workflows and remediation tasks.

Uses predictive analytics to anticipate emerging threats.

Utilizes AI algorithms to identify anomolies and block access to malicious sites.

Makes informed choices based on available data and objectives.

Capability to perform complex tasks without constant human input.

Works across multiple software systems or databases.

Anticipates needs and offers suggestions without prompting.

Provides specific capability to defend AI assets from adversarial attacks (including prompt injection, data poisoning, model inversion or extraction) without requiring retraining of the underlying model.

Enables automatic inspection of model inputs (prompts) and/or outputs (responses) to prevent unsafe, sensitive or manipulated content.

Monitors the integrity of model weights, dependencies or metadata (for example via SBOM/AIBOM) to detect tampering, drift or unauthorised modification.

Verifies the ability to enforce who or what (users, agents, systems) may access a model or LLM asset.

Detects unusual or harmful runtime behaviour of AI models, agents or workflows (such as unexpected output patterns, excessive permissions use, or unknown agents).

Provides a persistent, searchable audit log of AI‑asset inputs, outputs and interactions (including who/what invoked the model, when, and with what data) for forensics and compliance.

Ensures that the AI‑security platform supports scaling of AI‑asset protection (models, agents, multi‑cloud deployments) and applies governance/compliance frameworks as AI usage grows.

Enables integration of the AI‑security solution with traditional security stacks (SIEM, SOAR, cloud security, application security, identity/access management) to unify visibility and response.

Offers visibility into unmanaged or unauthorized AI/agent use (“shadow AI”) across the organisation and enforces control over such usage (e.g., agent creation, LLM‑based services).

Supports codified, machine‑enforceable security policies targeting AI models/agents (for example, blocking certain categories of prompts, enforcing least‑privilege for model use, enforcing “no external data” rules).

Allows businesses to monitor and secure applications and workloads across multiple public clouds

Assess and score risks using risk matrices

Automatically scan the network for devices and take pre-defined actions upon discovery

Application programming interface that allows for integration with other systems/databases

Receive notification of issues as soon as they occur

Identify component attributes like servers, hardware, software, and manage relationships across all services

Set up connections to third-party platforms to improve business processes

Manage user accounts, profiles, roles, permissions, and other details across applications, devices or networks

Track and report regulatory data to either internal management or external stakeholders

Analyze potential risks across the organization

Protect incoming and outgoing communications against malware, spam, display spoofing, and other threats

A set of guidelines regarding cloud security management

Use AI to generate content in the form of text, images, videos, etc.

Maintenance and upkeep of physical and/or virtual devices

Plan, schedule, and execute organization's accounts and assets to ensure compliance with policies and laws

Dashboard to view the status of ongoing processes, identify current incidents and track past activities

Alerts or notifications of various types such as pop-up messages, sounds, banners, or badges

Monitor and analyze the performance and status of a server or system/application

A virtual assistant that uses AI to pursue goals and complete tasks on behalf of users

Track and manage adherence to policies for any service, product, process, or supplier