Head-to-Head Comparison

Cynative Security Research Agent vs AI Eyes

Comprehensive feature analysis, ratings breakdown, platform compatibility, and community review comparison.

Cynative Security Research Agent

Cynative Security Research Agent

Open Source

Ask your cloud anything without breaking prod. Read-only.

No ratings (0 reviews)99 Upvotes
AI Eyes

AI Eyes

Open Source

Permission-first co-presence controls for AI companions

No ratings (0 reviews)63 Upvotes

Detailed Feature Comparison Matrix

Compare Other Tools
Dimension
Cynative Security Research AgentCynative Security Research Agent
AI EyesAI Eyes
Primary CategoryOpen SourceOpen Source
Community Rating
No ratings(0 reviews)
No ratings(0 reviews)
Community Upvotes99 votes63 votes
Supported Platforms
Web
Web
Tags & Focus
#Developer Tools#Open Source#Security
#Developer Tools#Open Source#Privacy#OpenAI Day
Maker / CompanyIndependent DeveloperIndependent Developer
Platform VerificationCommunity ListingCommunity Listing

About Cynative Security Research Agent

Cynative Security Research Agent is an open-source AI command-line interface (CLI) designed to give security engineers, developers, and DevOps teams quick, natural-language visibility into their cloud, code, and runtime security environments. Created by co-founders Shaked Zin and Yuri Shapira, the tool allows users to ask deep infrastructure questions—such as "what's publicly exposed that shouldn't be?" or "can my CI escalate to cloud admin?"—without any risk of breaking production.

Built strictly read-only by construction, Cynative resolves every request into explicit IAM actions. It checks and authorizes these actions against a strict read-only policy before attaching any API credentials. As a result, the tool is structurally incapable of altering or modifying your infrastructure, even if specifically instructed to do so.

Unlike typical Model Context Protocol (MCP) integrations that rely on single tool calls, Cynative generates and executes JavaScript scripts inside a secure, sandboxed runtime environment for every turn. This enables complex, multi-step research and cross-platform correlation across broad environments including AWS, GCP, Azure, Kubernetes (K8s), GitHub, and GitLab.

Pros of Cynative Security Research Agent

  • Strictly read-only architecture guarantees no accidental modifications to production infrastructure
  • Supports plain language queries across cloud, code, and runtime environments
  • Broad ecosystem support covering AWS, GCP, Azure, K8s, GitHub, and GitLab
  • Uses a sandboxed JavaScript execution runtime for flexible, scriptable multi-step research
  • Fully open-source CLI tool built for developer security transparency

Cons of Cynative Security Research Agent

  • Interface is command-line based, which may not appeal to non-technical users
  • By design, cannot perform automated remediation or apply infrastructure changes

Frequently Asked Questions

What is Cynative Security Research Agent?

Cynative Security Research Agent is an open-source AI CLI tool that allows security and engineering teams to ask natural language questions about their cloud infrastructure, source code, and runtime environments.

Is Cynative safe to use in production environments?

Yes. Cynative is built to be read-only by construction. Every call is mapped to specific IAM actions and verified against a read-only policy before credentials attach, preventing any write or modification operations.

Which platforms and environments are supported?

Cynative supports security querying across AWS, GCP, Azure, Kubernetes (K8s), GitHub, and GitLab.

How does Cynative differ from standard MCP tools?

Rather than relying on single API calls per turn like traditional MCP setups, Cynative writes and executes JavaScript scripts within a sandboxed runtime per turn to perform deeper analysis.

About AI Eyes

AI Eyes is a permission-first co-presence prototype designed for AI companions. Created by developer Deen Storkey, this open-source tool establishes a privacy-focused, local-first foundation for managing what your digital companions can see and hear.

With its initial v0.1 release, AI Eyes allows users to choose a specific screen or window to capture and gives granular, separate controls for screen, system audio, and microphone inputs. The interface makes it easy to invite named companions and ensures transparency by always displaying when sensing is active. Users can pause or end sessions at any time; ending a session immediately stops all media tracks and resets the session completely.

Built using Codex and GPT-5.6, this prototype is focused entirely on local-first permission, presence, and session-control. Please note that in this foundational stage, no external AI provider or semantic understanding has been connected yet.

Pros of AI Eyes

  • Privacy-focused, local-first permission architecture
  • Separate, granular control over screen, system audio, and microphone capture
  • Clear visual indicators showing when active sensing is occurring
  • Open-source code base allowing developers to review and build upon the prototype

Cons of AI Eyes

  • It is a prototype (v0.1) and does not yet have an active AI provider or semantic understanding connected
  • Limited to foundational capture and session-control features at this stage

Frequently Asked Questions

What is AI Eyes?

AI Eyes is an open-source, permission-first co-presence prototype built to manage what AI companions can access. It provides local-first controls over screen sharing, audio, and session state.

Does AI Eyes currently analyze my screen or voice?

No. In the v0.1 release, no AI provider or semantic understanding is connected. The prototype is currently a local-first foundation focused on permission, capture, presence, and session-control.

How do I control my privacy while using AI Eyes?

AI Eyes lets you choose exactly which screen or window to capture and gives you separate toggle controls for your screen, system audio, and microphone. There is also a clear indicator to show when sensing is active, and you can pause or end the session to stop all media tracks instantly.

What technologies were used to build AI Eyes?

The AI Eyes prototype was built using Codex and GPT-5.6.

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