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

Straiker is an AI-native security platform built specifically to protect enterprise AI applications and autonomous agents, focusing on the emerging risks of “agentic AI” systems that interact with tools, APIs, and sensitive data. It provides full visibility and control across the entire AI stack by analyzing behavioral signals from models, prompts, tools, identities, and infrastructure, enabling real-time detection and prevention of AI-specific threats such as prompt injection, privilege escalation, data exfiltration, and malicious tool usage. It combines continuous discovery, adversarial testing, and runtime protection through core components like Discover AI, Ascend AI, and Defend AI, which together identify all active agents, simulate attacks to uncover vulnerabilities, and enforce real-time safeguards during execution. Its multi-layered architecture captures deep contextual signals across user interactions, networks, and agent workflows.

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

AI-native engineering and security teams building autonomous agents that need real-time protection, testing, and control over complex multi-agent systems

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

Straiker
Founded: 2024
United States
www.straiker.ai/

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Categories

Categories

Integrations

Claude
Claude Code
GitHub
LangChain
Microsoft Copilot
Model Context Protocol (MCP)
OpenAI
Slack

Integrations

Claude
Claude Code
GitHub
LangChain
Microsoft Copilot
Model Context Protocol (MCP)
OpenAI
Slack
Claim Antares and update features and information
Claim Antares and update features and information
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