Antares

Antares

Cisco
+
+

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About

Antares is a family of open-weight security small language models purpose-built to localize known vulnerabilities inside large codebases. Antares-350M and Antares-1B are compact enough to run locally or on premises, helping teams keep proprietary source code inside their environment while reducing inference cost and runtime. Starting from a vulnerability description, advisory, or CWE category, the model follows an iterative investigation process similar to a human analyst, it searches for relevant code patterns, reads candidate files, incorporates new evidence, changes direction when a path is unproductive, and narrows the search to the files most likely to contain the weakness. Antares returns a ranked list of potentially vulnerable source files together with the terminal exploration trace that produced the result, making findings easier to review and prioritize.

About

From thwarting model poisoning to preserving data integrity, Aegis ensures that your AI models are shielded by default, empowering you to deploy your AI/ML projects in the cloud or on-premise, confident that your security posture is protecting you against an evolving threat landscape. Unsecured AI/ML tools broaden attack surfaces, amplifying enterprise vulnerability to security breaches without vigilant oversight by security teams. Suboptimal AI/ML security posture risks data breaches, downtime, profit losses, reputational damage, and credential theft. Vulnerable AI/ML frameworks jeopardize data science initiatives, risking breaches, intellectual property theft, supply chain attacks, and data manipulation. Aegis uses an ensemble of specialized tools and AI models to analyse data from your AI/ML landscape, as well as external data sources.

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

University cybersecurity labs that need efficient, locally deployable models for locating vulnerabilities in sensitive codebases

Audience

Companies wanting a platform to safeguard their AI/ML landscapes against emerging threats

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

No information available.
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

Cisco
Founded: 1984
United States
blogs.cisco.com/ai/introducing-antares-the-most-efficient-open-weight-ai-models-for-vulnerability-localization

Company Information

Neysa
www.neysa.ai/aegis

Alternatives

Alternatives

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Devstral Small 2

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Categories

Categories

Integrations

No info available.

Integrations

No info available.
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