BuffaLogs is an Open Source Django Project whose main purpose is to detect impossible travel logins.

In detail, it sends several types of alerts:

1. Impossible Travel

   It occurs when a user logs into the system from a significant distance within a range of time that cannot be covered by conventional means of transport.

2. Login from new device

   This alert is sent if the user utilizes a new appliance.

3. Login from a new country

   This alert is dispatched if the system is logged by a user from a country where they have never authenticated before.

For further details: Wiki - About

Honeynet	IntelOwl

Since its birth, this project has been participating in the GSoC under the Honeynet Project!

• 2023: Project available

Stay tuned for the upcoming GSoC! Join the Honeynet Slack chat for more info.

First of all, and if you have not done that yet, read the contributor guide which will allow you to understand all this process and how the program works overall. Refer to its left side menu to quick access sections that may interest you the most, although we recommend you to read everything.

This is a required step and you can use the current issues as a start to propose your idea.

We are not limited to what is listed right now, if you want to propose a new idea, please discuss it with the mentors in Honeynet slack channel #2023-buffalogs. We're always open to new ideas and won't hesitate on choosing them if you demonstrate to be a good candidate!

• You're committing to a project and we ask you to publicly publish your weekly progress on it in Github.
• We will ask you to give feedback on our mentorship and management continuously. Communication is key to the success of the project.
• You wholeheartedly agree with the code of conduct.
• You must tell us if there's any proposed idea that you don't think would fit the timeline or could be boring (yes, we're asking for feedback).

We recommend you to follow Google's guide to Writing a Proposal.

Once you have a draft proposal please share it with us via gsoc slack channel #2023-buffalogs.

You can also ask for a review anytime to the community or mentor candidates before the contributor application deadline. It's much easier if you get feedback early than to wait for the last moment.

• Slack chat

BuffaLogs employs the following tools which have to be installed on the machine:

• Docker
• Docker-compose
• Python

Then, you can clone this repository on your local computer with:

git clone git@github.com:certego/BuffaLogs.git

Or download the application directly from the Docker Hub, with the sudo docker pull certego/buffalogs:<release_tag>.

After that, there are two ways of running BuffaLogs, depending on your system configurations:

• if you already have an elastic cluster:
  • set the address of the host into the CERTEGO_ELASTICSEARCH variable in the buffalogs.env file
  • launch docker-compose up -d to run the containers
• if you have no hosts with Elasticsearch installed on it, you can run it directly with Buffalogs:
  • run docker-compose -f docker-compose.yaml -f docker-compose.elastic.yaml up -d in order to execute all the containers, included Elasticsearch and Kibana
  • Now elasticsearch and kibana are running on the same host with Buffalogs.

For further examples: Wiki - Example

BuffaLogs is able to analyse logs coming from any source, provided that it complies with the Elastic Common Schema and with the given structure:

```
{
    "_index": "<elastic_index>",
    "_id": "<log_id>",
    "@timestamp": "<log_timestamp>",
    "user": {
        "name": "<user_name>"
    },
    "source": {
        "geo": {
            "country_name": "<country_origin_log>",
            "location": {
                "lat": "<log_latitude>",
                "lon": "<log_longitude>"
            }
        },
        "ip": "<log_source_ip>"
    },
    "user_agent": {
        "original": "<log_device_user_agent>"
    },
    "event": {
        "type": "start",
        "category": "authentication",
        "outcome": "success"
    }
}

```

For a basic analysis to detect only impossible travel logins, the user_agent field is useless.

Five views were implemented using DRF - Django-Rest Framework, in order to provide the possible to query and produce the charts data. In particular, the supplied APIs are:

For further details: Wiki - REST APIs

To uninstall and remove all files, delete all containers with:

sudo docker-compose down -v

Then you can safely delete this repository.

BuffaLogs is an Open Source project and was developed in order to allow enrichments from people with any level of experience, but please read carefully the Contribution guidelines before making any changes to the project.

1. If needed, update the requirements in the requirements.txt and also into the setup.cfg file
2. Add a new entry in CHANGELOG.md containing all the features, changes and bugfix developed
3. Modify the version in the setup.cfg
4. Remove the previous version of the reusable app into django-buffalogs/dist and create the new version running python3 setup.py sdist from django-buffalogs/
5. Commit a PR from the develop to the main branch with the version as a Title and the changes as a comment
6. Now you can export BuffaLogs copying the buffalogs-x.y.z.tar.gz package into your project

This project is protected by the Apache Licence 2.0.