Codename MDASH

Codename MDASH

Microsoft
RankLLM

RankLLM

Castorini
+
+

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About

Codename MDASH is an agentic code scanner in Microsoft Defender that uses a multi-model AI system to detect, validate, and remediate vulnerabilities with greater depth than traditional static analysis. It extends Defender CLI with a multistage pipeline in which specialized agents collaborate across four stages. Prepare ranks files by risk using call-graph analysis and code-complexity metrics, prioritizing functions most likely to contain vulnerabilities. Scan sends ranked code to more than 100 expert agents, including injection, memory-safety, and auth-bypass auditors, with each agent focused on a specific vulnerability class. Validate combines taint analysis, type resolution through Language Server Protocol servers, and multi-model agentic debate to refine confidence and reduce false positives. Dedup consolidates overlapping results into a final set of unique actionable findings.

About

RankLLM is a Python toolkit for reproducible information retrieval research using rerankers, with a focus on listwise reranking. It offers a suite of rerankers, pointwise models like MonoT5, pairwise models like DuoT5, and listwise models compatible with vLLM, SGLang, or TensorRT-LLM. Additionally, it supports RankGPT and RankGemini variants, which are proprietary listwise rerankers. It includes modules for retrieval, reranking, evaluation, and response analysis, facilitating end-to-end workflows. RankLLM integrates with Pyserini for retrieval and provides integrated evaluation for multi-stage pipelines. It also includes a module for detailed analysis of input prompts and LLM responses, addressing reliability concerns with LLM APIs and non-deterministic behavior in Mixture-of-Experts (MoE) models. The toolkit supports various backends, including SGLang and TensorRT-LLM, and is compatible with a wide range of LLMs.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

DevSecOps teams managing large polyglot repositories that need deeper vulnerability detection and AI-assisted remediation inside existing delivery pipelines

Audience

Academic researchers and developers seeking a solution offering tools for implementing and evaluating listwise reranking with large language models

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Microsoft
Founded: 1975
United States
learn.microsoft.com/en-us/security-exposure-management/ai-code-security-overview

Company Information

Castorini
Canada
github.com/castorini/rank_llm/

Alternatives

Alternatives

RankGPT

RankGPT

Weiwei Sun
Claude Security

Claude Security

Anthropic
ColBERT

ColBERT

Future Data Systems
CodeMender

CodeMender

Google DeepMind

Categories

Categories

Integrations

Gemini
Gemini Enterprise
Llama
MAI-Cyber-1-Flash
Mistral AI
NVIDIA TensorRT
OpenAI
Python
Qwen
RankGPT

Integrations

Gemini
Gemini Enterprise
Llama
MAI-Cyber-1-Flash
Mistral AI
NVIDIA TensorRT
OpenAI
Python
Qwen
RankGPT
Claim Codename MDASH and update features and information
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