Ratings and Reviews 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • cside Reviews & Ratings
    4.9 out of 5 stars 37 Ratings
    Company Website for cside
  • Kitecyber Reviews & Ratings
    4.9 out of 5 stars 89 Ratings
    Company Website for Kitecyber
  • Criminal IP Reviews & Ratings
    4.6 out of 5 stars 459 Ratings
    Company Website for Criminal IP
  • Daylight Reviews & Ratings
    4.8 out of 5 stars 15 Ratings
    Company Website for Daylight
  • Rocket z/Assure VAP Reviews & Ratings
    5.0 out of 5 stars 1 Rating
    Company Website for Rocket z/Assure VAP
  • Adaptive Security Reviews & Ratings
    4.9 out of 5 stars 152 Ratings
    Company Website for Adaptive Security
  • Anaconda Reviews & Ratings
    4.4 out of 5 stars 626 Ratings
    Company Website for Anaconda
  • Astra Pentest Reviews & Ratings
    4.6 out of 5 stars 296 Ratings
    Company Website for Astra Pentest
  • Athena Security Reviews & Ratings
    4.8 out of 5 stars 5 Ratings
    Company Website for Athena Security
  • Gemini Enterprise Agent Platform Reviews & Ratings
    4.3 out of 5 stars 1,178 Ratings
    Company Website for Gemini Enterprise Agent Platform

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.

What is AppSOC?

Achieve thorough coverage across various security scanners, which should include infrastructure, platforms, and applications. Formulate a cohesive policy that can be uniformly implemented across all scanners present in the pipeline, incorporating any microservice or application. Improve your software bill of materials by assimilating insights garnered from your SCA platform along with a diverse array of scanners. By generating consolidated reports that link applications to vulnerabilities, business leaders and product owners are better equipped to accelerate their time to market. The implementation of automated triaging, deduplication, and an impressive 95% reduction in noise enables a concentrated focus on high-priority vulnerabilities. With the advent of workflow automation designed for risk-based triaging and prioritization, organizations can effectively scale their operations instead of manually managing each individual issue. In addition, applying machine learning for correlation and risk assessment at the application level grants a precise understanding of how each vulnerability affects compliance, allowing for more strategic decision-making regarding security policies. This methodology not only refines security practices but also significantly boosts the organization’s agility in managing potential threats while fostering a culture of proactive risk management. By adopting these strategies, companies can ensure they are better prepared to handle the evolving landscape of cybersecurity challenges.

Media

Media

Integrations Supported

MAI-Cyber-1-Flash

Integrations Supported

Amazon Web Services (AWS)
Azure Boards
Checkmarx
GitLab
Jenkins
Jira
Microsoft Teams
Slack
Tenable One
Veracode

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Online Training

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

Company Facts

Organization Name

AppSOC

Date Founded

2021

Company Location

United States

Company Website

www.appsoc.com

Categories and Features

AI Security

Not specified

Categories and Features

Popular Alternatives

Popular Alternatives

Claude Security Reviews & Ratings

Claude Security

Anthropic
CodeMender Reviews & Ratings

CodeMender

Google DeepMind