> For the complete documentation index, see [llms.txt](https://docs.elastiflow.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.elastiflow.com/data_platforms/elastic/ml/netsec/netsec_activity/rare_asn.md).

# Rare Autonomous System

Identifying network traffic to or from a rare Autonomous System (AS) is crucial in network security and management. An Autonomous System is a distinct network or group of networks under a common administration that shares a common routing policy. Traffic involving a rare AS, which is not typically observed in normal network operations, can be indicative of several potential issues. These can range from inadvertent misconfigurations in routing settings to more serious concerns like attempts at data exfiltration, unauthorized access, or a precursor to cyber-attacks. Early detection of such anomalies allows network administrators to investigate and address these irregularities promptly, thereby preventing potential security breaches and ensuring the integrity of the network.

ElastiFlow provides a collection of anomaly detection jobs designed to identify network traffic to/from a rare Autonomous System comprises various tools and methods focusing on analyzing network traffic patterns.

## Attributes

| Attribute    | Information |
| ------------ | ----------- |
| **Analysis** | temporal    |

## Downloads

| Schema    | Endpoint   | Link                                                                                                                                                                       |
| --------- | ---------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **CODEX** | **client** | [elastiflow\_codex\_netsec\_rare\_asn\_client](https://github.com/elastiflow/elastiflow_for_elasticsearch/raw/master/ml/codex/netsec_activity/netsec_rare_asn_client.json) |
| **CODEX** | **server** | [elastiflow\_codex\_netsec\_rare\_asn\_server](https://github.com/elastiflow/elastiflow_for_elasticsearch/raw/master/ml/codex/netsec_activity/netsec_rare_asn_server.json) |
| **ECS**   | **client** | [elastiflow\_ecs\_netsec\_rare\_asn\_client](https://github.com/elastiflow/elastiflow_for_elasticsearch/raw/master/ml/ecs/netsec_activity/netsec_rare_asn_client.json)     |
| **ECS**   | **server** | [elastiflow\_ecs\_netsec\_rare\_asn\_server](https://github.com/elastiflow/elastiflow_for_elasticsearch/raw/master/ml/ecs/netsec_activity/netsec_rare_asn_server.json)     |

By implementing this collection of anomaly detection jobs, network administrators can quickly identify and respond to unusual network traffic involving rare Autonomous Systems. This proactive approach is critical in mitigating potential threats and maintaining the overall security and efficiency of the network. Timely identification and investigation of such anomalies help ensure that the network remains robust against both inadvertent misconfigurations and deliberate malicious activities.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.elastiflow.com/data_platforms/elastic/ml/netsec/netsec_activity/rare_asn.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
