Protect AI: Key Features and Tool

Protect AI offers AI security solutions that focus on securing AI applications. It offers comprehensive tools which specially designed to efficiently identify, test and protect AI. Protect AI delivers automated security testing capabilities that allows security teams to detect vulnerabilities.

This blog explores what is protect AI, its features and side by side comparison with Akto to help businesses make a wise decision on choosing the right AI security.

What is Protect AI?

Protect is an end-to-end AI security platform that secures machine learning driven systems across the entire lifecycle. It is the broadest and comprehensive AI security solution and has multiple tools like Guardian, Recon and Layer that operates on a single, unified platform and secure AI applications from model selection and testing runtime and beyond. Together, these tools help organizations identify threats such as prompt injection, data poisoning, model extraction and other attacks before they could compromise AI applications to ensure compliant and secure AI deployment at scale.

Besides this, to its core security tooling, Protect AI focuses on proactive threat research and secure-by-design principles that integrate security throughout AI workflows and development.

Key Components of Protect AI Approach to AI Security

The key components of Protect AI’s AI security platform are as below.

Guardian - AI Model Security

Guardian is Protect AIs core model security component that can identify and scan AI and ML models against hidden threats before they are used. It provides advanced scanners that identify vulnerabilities like deserialization risks, backdoors and other model specific threats, which helps businesses safely adopt any model from diverse sources without compromising security. Guardian embeds into current development workflows which enables policy-based enforcement of security standards across model selection and deployment.

Image Source: Protect AI Guardian

Recon - Scalable Red Teaming

Recon offers automatic red-teaming and strong adversarial testing for AI applications. It lets teams to simulate and analyze multiple attack vectors and threats against AI systems before production to provide actionable insights to mitigate security risks and help teams to confidently implement AI.

Image Source: Protect AI Recon

Layer - Runtime Security for AI

Layer focuses on runtime security by monitoring AI applications in real-time. It detects and mitigates threats as they happen during operation, which offers visibility and control over deployed AI behavior to stop attacks at runtime.

Image Source: Protect AI Layer

Open Source Tools

Protect AI also includes open source components like ModelScan and LLM guard to secure LLM powered applications through input and output sanitization which extends security features and supporting integration into diverse AI workflows.

Features and Capabilities of Protect AI

Here are some of the features and capabilities of Protect AI

Secure Gateway Functionality

It serves as a controlled gateway that validates model requests, enforce security policies and block unsafe harmful models while integrating seamlessly with current MLOps workflows.

Comprehensive Model Scanning

Advanced pre-deployment scanning identifies harmful code and vulnerabilities in internal and third-party models that ensure secure, compliant ML models enter production environments.

Integration with Current Security Frameworks

Effortlessly integrate with present security tools, improve protection without disruption and also provide end-to-end visibility across ML and AI threat surfaces.

Policy Enforcement Engine

Automatic policies may approve or reject models based on source, security risks and license compliance which helps organizations consistently implement AI governance and security standards.

Consolidated Insights and Dashboards

Executive dashboards consolidate model security status, licensing data, ownership, deliver clear visibility into enterprise AI usage for risks and compliance decisions.

Akto’s Approach to MCPs and AI Agents Security

Akto offers multiple approaches to MCP and Agentic AI security, so let's have a look over some of the features and capabilities.

AI Agent and LLM Discovery

Automatically identifies all MCP, AI agents, endpoints of LLM that are associated across your infrastructure which includes shadow resources. This offers complete visibility into your AI attack surface.

AI Guardrails

It enforces actionable security guardrails and automated policy actions to prevent harmful actions by agents, implement least-privileged access, mask sensitive data and maintain compliance across all the autonomous workflows.

Agentic Red Teaming

It performs simulation of adversarial attacks designed for agent specific risks, prompt injections, tool poisoning, context leak and other emerging agent AI threats, that help security identify teams weaknesses effectively.

Risk Visibility and Reporting

Complete visibility into agentic ecosystems, dashboards, risk scoring and security analytics that support decision making, compliance and governance workflows.

Protect AI Vs Akto: A Detailed Comparison

Protect AI Security and Akto are well-known platforms in AI Agents and MCP Security. Here is a detailed comparison between Protect AI and Akto.

Final Thoughts on Protect AI

Protect AI and Akto both offer robust AI security solutions, but with distinct feature sets. Organizations seeking comprehensive vulnerability testing, continuous monitoring, and automated risk prioritization may choose the platform that best fits their AI infrastructure and workflow needs. While Protect AI focuses on, Akto provides agentic AI security, MCP-aligned workflow protection, and real-time anomaly detection to secure autonomous AI agents, APIs, and integrated systems.

By Integrating a strong Agentic AI Security, security teams can strengthen their defense mechanism through threat detection, lower response times and stay ahead of emerging Agentic AI security risks and threats. Akto has integrated next generation Agentic AI security and MCP Security to cover modern AI-powered businesses. It can easily integrate into DevSecOps pipeline to enable security teams to maintain continuous inventory of APIs, monitor runtime issues and test vulnerabilities. It runs 1000+ probes and simulates across discovered AI and MCPs, implements AI Guardrails and automates policy actions, flags sensitive data exposure, misconfigurations and levels of risk.

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