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What is GuardionAI?

GuardionAI functions as both an Agent and a MCP Security Gateway, providing all-encompassing security for AI agents and Model Context Protocol tools that engage with enterprise data. Strategically integrated within the execution path, it proficiently detects and redacts sensitive information, enforces protective measures, and grants improved visibility into activities often overlooked by traditional SIEM, DLP, and identity frameworks. Every action taken by agents is thoroughly monitored, enforced, and recorded at the protocol level, covering a wide array of components including AI agents, LLM applications, RAG systems, chatbots, coding assistants, MCP servers, internal applications, databases, operating systems, and cloud infrastructures. GuardionAI is specifically engineered to mitigate critical vulnerabilities in AI, such as prompt injection, system overrides, web-based attacks, MCP tool tampering, harmful code execution, inappropriate content exposure, leakage of personally identifiable information and credentials, unauthorized access to sensitive data, off-topic drift, and violations of access control, all in accordance with the OWASP LLM Top 10 and agentic AI threat frameworks. Furthermore, the gateway features a formidable four-layer protection system, ensuring that organizations can effectively secure their AI assets like never before. This comprehensive strategy not only bolsters security but also equips teams with the necessary insights to adeptly navigate the intricacies of modern AI landscapes, ultimately fostering a more robust defense against emerging threats. In an age where data integrity is paramount, GuardionAI stands as a critical partner in safeguarding enterprise resources.

What is Codename MDASH?

Codename MDASH refers to a sophisticated code scanning tool that is incorporated into Microsoft Defender, utilizing a multi-modal AI framework to identify, confirm, and resolve vulnerabilities with far greater depth than traditional static analysis techniques. It enhances the Defender CLI through a multistage method where dedicated agents collaborate across four distinct phases. First, the preparation phase sorts files by risk level, applying call-graph analysis and assessing code complexity to pinpoint functions most likely to harbor vulnerabilities. Next, the scanning phase delivers this prioritized code to over 100 specialized agents, each concentrating on specific types of vulnerabilities such as injection flaws, memory safety concerns, and authentication bypasses, ensuring targeted assessments. The subsequent validation phase incorporates taint analysis and type resolution via Language Server Protocol servers, in addition to a deliberation among multi-model agents, to bolster confidence levels and reduce false positives effectively. Ultimately, the deduplication step consolidates overlapping findings into a coherent set of unique, actionable results, thereby improving the overall efficacy of vulnerability management strategies. This groundbreaking methodology marks a transformative shift in how threats are detected and remediated during the software development lifecycle. As a result, organizations can better safeguard their applications against emerging security risks.

Media

Media

Integrations Supported

Anthropic
Claude Code
CrewAI
Cursor
GitHub Copilot
Helicone
LangChain
LiteLLM
LlamaIndex
Meta AI
Model Context Protocol (MCP)
OpenAI
OpenClaw
Pinecone
Portkey
PostgreSQL
Redis
Swarm
WhatsApp

Integrations Supported

MAI-Cyber-1-Flash

API Availability

Has API

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

Mac
On-Prem
Linux

Supported Platforms

SaaS

Customer Service / Support

24 Hour Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub

Company Facts

Organization Name

GuardionAI

Date Founded

2025

Company Location

United States

Company Website

guardion.ai/

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

learn.microsoft.com/en-us/security-exposure-management/ai-code-security-overview

Categories and Features

AI Security

Not specified

Categories and Features

AI Security

Not specified

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