GENE-IPINFO

Feluda.ai Gene: GENE-IPINFO

GENE-IPINFO is an IP metadata retrieval gene built specifically for AI models and autonomous workflows, using the IPinfo.io LITE API as a trusted upstream source. It enables models to reliably obtain, store, and re-use basic IP context as part of reasoning, enrichment, and decision-making pipelines inside the Feluda.ai ecosystem.

Purpose and scope

This gene allows AI systems to perform deterministic IP address lookups (IPv4 and IPv6), persist the raw IPinfo LITE response as structured JSON, and reference that data later without repeated external calls.

The scope is intentionally limited to the IPinfo LITE dataset. No additional enrichment, inference, or modification of the upstream data is performed, ensuring transparency and predictable behavior for models.

Who this gene is for

GENE-IPINFO is designed primarily for AI agents, LLM-based workflows, and automated reasoning systems that need access to factual IP metadata from a known, trusted source.

By making IP context directly accessible to models, human operators such as security engineers, platform teams, and investigators benefit indirectly: their AI systems can reason faster, more consistently, and with fewer assumptions when handling IP-related data.

Typical use cases

• Allowing AI models to enrich alerts, logs, or events with basic IP metadata during automated analysis.

• Supporting AI-driven investigations where models need geographic or ASN context to guide reasoning steps.

• Enabling repeatable, auditable AI workflows by storing lookup results instead of relying on live API calls.

• Powering internal tooling and orchestration where LITE-level IP data is sufficient and predictable.

Supported operations

help returns usage instructions and supported parameters for AI or workflow invocation.

get fetches IP metadata from the IPinfo LITE API, stores the result under a specified folder name, and returns the storage path and HTTP status to the calling model.

listfolders returns the raw platform JSON describing all top-level folders in the gene dataspace.

listfoldercontent returns the raw JSON listing files within a specific folder.

readfile reads a stored JSON file using foldername and filename and returns its raw contents for direct model consumption.

Inputs and outputs

Inputs are provided as simple key/value parameters such as case, ip, foldername, description, and filename, making the gene easy to invoke from structured AI calls.

For the get operation, the primary output is a JSON file saved at //.json, along with a response object indicating request status and storage location.

The readfile operation returns the raw JSON string, allowing models to parse, reason over, or pass the data into downstream tools without transformation.

Storage, security, and constraints

Stored files follow a consistent structure: { "ip": "<ip>", "description": "<optional>", "data": { ... } }, where data is the unmodified response from IPinfo LITE.

The IPinfo API token is securely retrieved from Vault via IPINFO_TOKEN. API credentials are never exposed to models or passed as input parameters.

Folder names are restricted to short, safe identifiers, filenames cannot contain path separators, and IP addresses are validated before any external request is made, ensuring safe execution within autonomous AI workflows.

Example usage

Fetch and store IP data: { "case":"get", "ip":"1.1.1.1", "foldername":"generaltesting", "description":"investigation" }

List folders: { "case":"listfolders" }

List folder contents: { "case":"listfoldercontent", "foldername":"generaltesting" }

Read a stored file: { "case":"readfile", "foldername":"generaltesting", "filename":"1.1.1.1.json" }