AntaresCisco
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Related Products
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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.
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About
PRFlow is an AI code reviewer built to find the bugs that ship. It indexes your codebase, traces cross-file dependencies, and produces a structured security review in under 3 minutes, automatically on every pull request. Built for the complexity of real codebases, PRFlow uses semantic codebase memory to understand cross-repo dependencies and internal patterns before reading the PR. It extracts the right context for the LLM, including the changed function and its cross-file dependencies, instead of sending only the diff or the whole file. Its security-first review focuses on issues like XSS, SSRF, SQL injection, auth bypass, and race conditions by tracing how code flows across files. PRFlow reads the whole PR once and produces a complete structured review with a score, walkthrough, issues by file, severity, strengths, and code fix suggestions directly as inline GitHub PR comments. It supports conversational follow-up inside the PR thread.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
University cybersecurity labs that need efficient, locally deployable models for locating vulnerabilities in sensitive codebases
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Audience
Senior engineering teams that need fast, security-focused AI pull request reviews with cross-file context and learning from team feedback
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
No information available.
Free Version
Free Trial
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Pricing
Free
Free Version
Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationCisco
Founded: 1984
United States
blogs.cisco.com/ai/introducing-antares-the-most-efficient-open-weight-ai-models-for-vulnerability-localization
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Company InformationPRFlow
United States
prflow.graphbit.ai/
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Categories |
Categories |
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Integrations
C#
GitHub
Go
JavaScript
Python
Ruby
Rust
SQL
TypeScript
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