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Description

Antares represents a suite of open-weight security small language models specifically designed to identify existing vulnerabilities within extensive codebases. With models like Antares-350M and Antares-1B, organizations can operate them locally or on-site, allowing for the protection of proprietary source code while also minimizing both inference costs and runtime. The process begins with a description of the vulnerability, an advisory, or a CWE category, where the model engages in a step-by-step investigation akin to that of a human analyst, systematically searching for pertinent code patterns, examining potential files, assimilating new information, and altering its approach when certain avenues prove unfruitful. This strategy enables the model to focus its efforts on the files that are most likely to harbor the identified weaknesses. Ultimately, Antares generates a prioritized list of potentially vulnerable source files along with the detailed exploration trail that led to these findings, facilitating easier review and prioritization for teams. Moreover, this capability not only streamlines the vulnerability assessment process but also enhances the overall security posture of the development environment.

Description

Consistently monitor and remediate vulnerabilities within AI data, models, and application usage using IBM Guardium AI Security, which provides automated and ongoing surveillance for AI implementations. The system identifies security flaws and misconfigurations while managing the security dynamics between users, models, data, and applications. This functionality is integrated within the IBM Guardium Data Security Center, designed to enhance collaboration between security and AI teams through streamlined workflows, a unified overview of data assets, and centralized compliance regulations. Guardium AI Security identifies the specific AI model linked to each deployment, revealing the data, model, and application interactions involved. Additionally, it displays all applications that access the model, allowing users to assess vulnerabilities in the model, its foundational data, and the interacting applications. Each identified vulnerability is given a criticality score, enabling effective prioritization of remediation efforts. Furthermore, users can easily export the vulnerability list for comprehensive reporting, ensuring that all necessary stakeholders are informed and aligned on security efforts. This proactive approach not only strengthens security but also fosters a culture of awareness and responsiveness within the organization.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Azure Marketplace
IBM Guardium

Integrations

Azure Marketplace
IBM Guardium

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Cisco

Founded

1984

Country

United States

Website

blogs.cisco.com/ai/introducing-antares-the-most-efficient-open-weight-ai-models-for-vulnerability-localization

Vendor Details

Company Name

IBM

Founded

1911

Country

United States

Website

www.ibm.com/products/guardium-ai-security

Product Features

Product Features

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