Cross-system research
Runs frontier models across code, cloud, and runtime so a single question can fan out across GitHub, GitLab, AWS, GCP, Azure, and Kubernetes.
Cynative is a command-line tool for infrastructure research that reasons across code, cloud, and runtime and returns verified answers. It is designed for read-only investigations such as exposure checks, permission tracing, and drift analysis.
Cynative is a command-line research tool for infrastructure and runtime questions. Its README describes it as a way to ask your infrastructure anything and have frontier models reason across code, cloud, and runtime as one system, then return verified answers.
The repository shows examples focused on security, drift, permissions, and exposure analysis. Cynative can run research code in an ephemeral sandbox, query APIs in parallel, and cross-check findings against live evidence before presenting results.
The product is positioned as read-only by construction: calls are gated and authorized before credentials are attached, and the README says the research sandbox has no host access with network access pinned to mapped services. The documentation also shows support for multiple LLM providers through environment variables and simple CLI prompts.
Runs frontier models across code, cloud, and runtime so a single question can fan out across GitHub, GitLab, AWS, GCP, Azure, and Kubernetes.
Writes and runs code in an ephemeral sandbox to query APIs in parallel, which the README says helps it research at scale.
Cross-checks findings and traces them back to source evidence so the output is verified rather than a single model answer.
Uses an action-gate and read-only policy so every call is authorized before a credential is attached, and the tool fails closed when required IAM actions are not allowed.
Redacts secrets from tool output before they are sent to the model, according to the README’s comparison table.
Provides a single binary with built-in connectors and supports many model providers through the embedded Bifrost SDK.
Use Cynative to ask where a cloud environment is exposed, which permissions are high risk, or whether a credential leak has changed the blast radius of a system.
Trace privilege paths, IAM escalation routes, and policy changes back to the pull request or source of origin when you need an audit trail.
Compare live cloud resources with infrastructure-as-code to find drift between what is deployed and what should be deployed.
Investigate issues that span application code and runtime data by querying GitHub or GitLab alongside cloud and Kubernetes systems in one pass.
Run research in an interactive session or with one-off prompts when you need a repeatable CLI workflow for ad hoc infrastructure questions.
Cynative is presented as a research tool for infrastructure questions across code, cloud, and runtime. The README shows example prompts such as identifying exposed cloud resources, tracing IAM role escalation paths, and finding drift between live resources and infrastructure-as-code.
The quick start shows a command-line workflow: install Cynative, set an LLM provider and model in environment variables, then run a prompt with `cynative -p` or start an interactive session.
The README says Cynative can reason across GitHub, GitLab, AWS, GCP, Azure, and Kubernetes, and the provider docs show support for many LLM providers including OpenAI, Anthropic, Azure OpenAI, Bedrock, Vertex, Gemini, Cohere, Mistral, Groq, Ollama, and vLLM.
Cynative states that it is read-only by construction, with every call gated and authorized before a credential is attached. It also says research code runs in a sandbox and that findings are cross-checked against live evidence.
The pricing page on GitHub shows a free plan, a Team plan, and an Enterprise plan with a free trial path, but the Cynative repository itself does not document product-specific pricing.
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