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https://github.com/SpamScope/spamscope
Fast Advanced Spam Analysis Tool
https://github.com/SpamScope/spamscope
ansible ansible-playbook apache-storm application-security dialect docker docker-image mail-analyzer outlook python security smtp spam-analyzer spamscope streamparse
Last synced: 3 months ago
JSON representation
Fast Advanced Spam Analysis Tool
- Host: GitHub
- URL: https://github.com/SpamScope/spamscope
- Owner: SpamScope
- License: apache-2.0
- Created: 2016-08-24T21:55:46.000Z (almost 8 years ago)
- Default Branch: develop
- Last Pushed: 2024-03-18T20:27:33.000Z (3 months ago)
- Last Synced: 2024-03-20T10:07:48.859Z (3 months ago)
- Topics: ansible, ansible-playbook, apache-storm, application-security, dialect, docker, docker-image, mail-analyzer, outlook, python, security, smtp, spam-analyzer, spamscope, streamparse
- Language: Python
- Homepage: https://pypi.python.org/pypi/SpamScope
- Size: 6.24 MB
- Stars: 276
- Watchers: 20
- Forks: 59
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml
- License: LICENSE.txt
Lists
- awesome-list-ansible - spamscope
- awesome-opensource-email - Spamscope - Fast Advanced Spam Analysis Tool. (Sending / SPAM Filtering)
README
[](https://badge.fury.io/py/SpamScope)
[](https://travis-ci.org/SpamScope/spamscope)
[](https://coveralls.io/github/SpamScope/spamscope?branch=develop)
[](https://bettercodehub.com/)
# Overview
SpamScope is an advanced spam analysis tool that use [Apache Storm](http://storm.apache.org/) with [streamparse](https://github.com/Parsely/streamparse) to process a stream of mails.
To understand how SpamScope works, I suggest to read these overviews:
- [Apache Storm Concepts](http://storm.apache.org/releases/1.2.3/Concepts.html)
- [Streamparse Quickstart](http://streamparse.readthedocs.io/en/stable/quickstart.html)
In general the first step is run Apache Storm, then you can run the topologies on it.
SpamScope has some topologies in [topologies folder](./topologies/), but you can make others topologies.
# Apache 2 Open Source License
SpamScope can be downloaded, used, and modified free of charge. It is available under the Apache 2 license.
## Support the project
**Dogecoin**: `DAUbDUttkf8WN1kwP9YYQQKyEJYY2WWtEG`
[](https://en.cryptobadges.io/donate/1BCJ8wok4DNW8KbdL8H3VwZviXAWibhEPe)
[](https://www.paypal.com/cgi-bin/webscr?cmd=_s-xclick&hosted_button_id=VEPXYP745KJF2)
# What Does SpamScope do?
SpamScope gets the raw emails (both RFC822 and Outlook formats) in input and returns an JSON object. Then it extracts urls and attachments (if they are zipped extracts the content files). All informations are saved in JSON objects. This is the first analysis. After that SpamScope runs a _phishing_ module, that gives a _phishing score_ to the emails.
Then you can enable/disable post processing modules, that connect SpamScope with third party tools. There are three main categories:
- raw emails analysis
- attachments analysis
- sender emails analysis
It's possible to add new modules in these three categories, if you want connect SpamScope with others tools.
## Raw emails analysis
These modules (see [here](./src/modules/mails)) analyze the raw emails:
- SMTP dialect
- SpamAssassin
## Attachments analysis
These modules (see [here](./src/modules/attachments)) analyze the attachments of emails:
- Apache Tika
- Store sample on disk (as default SpamScope saves samples in JSON objects)
- Thug
- VirusTotal
- Zemana
## Sender emails analysis
SpamScope can detects the exact sender IP and then it can analyze it (see [here](./src/modules/networks)):
- Shodan
- VirusTotal
# Why should I use SpamScope
- It's very fast: the job is splitted in functionalities that work in parallel.
- It's flexible: you can choose what SpamScope has to do.
- It's distributed: SpamScope uses Apache Storm, free and open source distributed realtime computation system.
- It makes JSON output that you can save where you want.
- It's easy to setup: there are docker images and docker-compose ready for use.
- It's integrated with Apache Tika, VirusTotal, Thug, Shodan and SpamAssassin (for now).
- It's free and open source (for special functions you can contact me).
- It can analyze Outlook msg.
## Distributed
SpamScope uses Apache Storm that allows you to start small and scale horizontally as you grow. Simply add more workers.
## Flexibility
You can choose your mails input sources (with **spouts**) and your functionalities (with **bolts**).
SpamScope comes with the following bolts:
- **tokenizer** splits mail in token like headers, body, attachments and it can filter emails, attachments and ip addresses already seen
- **phishing** looks for your keywords in email and connects email to targets (bank, your customers, etc.)
- **raw_mail** is for all third party tools that analyze raw mails like SpamAssassin
- **attachments** analyzes all mail attachments and uses third party tools like VirusTotal
- **network** analyzes all sender ip addresses with third party tools like Shodan
- **urls** extracts all urls in email and attachments
- **json_maker** and **outputs** make the json report and save it
## Store where you want
You can build your custom output bolts and store your data in Elasticsearch, MongoDB, filesystem, etc.
## Build your topology
With streamparse tecnology you can build your topology in Python, add and/or remove spouts and bolts.
## API
For now SpamScope doesn't have its own API, because it isn't tied to any tecnology.
If you use `Redis` as spout (input), you'll use Redis API to put mails in topology.
If you use `Elasticsearch` as output, you'll use Elasticsearch API to get results.
It's possible to develop a middleware API that it talks with input, output and changes the configuration, but now there isn't.
# SpamScope on Web
- [Shodan Applications & Integrations](https://developer.shodan.io/apps)
- [The Honeynet Project](http://honeynet.org/node/1329)
- [securityonline.info](http://securityonline.info/pcileech-direct-memory-access-dma-attack-software/)
- [jekil/awesome-hacking](https://github.com/jekil/awesome-hacking)
- [Linux Security Expert](https://linuxsecurity.expert/tools/spamscope/)
# Authors
## Main Author
Fedele Mantuano (**LinkedIn**: [Fedele Mantuano](https://www.linkedin.com/in/fmantuano/))
# Requirements
For operating system requirements you can read [Ansible playbooks](./ansible), that go into details.
For Python requirements you can read:
* [mandatory requirements](./requirements.txt)
* [optional requirements](./requirements_optional.txt)
_Thug_ is another optional requirement, that it's not in requirements. See [Thug section](#thug-optional) for more details.
## Apache Storm
[Apache Storm](http://storm.apache.org/) is a free and open source distributed realtime computation system.
## streamparse
[streamparse](https://github.com/Parsely/streamparse) lets you run Python code against real-time streams of data via Apache Storm.
## mail-parser
[mail-parser](https://github.com/SpamScope/mail-parser) is the parsing for raw email of SpamScope.
## Faup
[Faup](https://github.com/stricaud/faup) stands for Finally An Url Parser and is a library and command line tool to parse URLs and normalize fields.
## rarlinux (optional)
[rarlinux](https://www.rarlab.com/) unarchives rar file.
## SpamAssassin (optional)
SpamScope can use [SpamAssassin](http://spamassassin.apache.org/) an open source anti-spam to analyze every mails.
## Apache Tika (optional)
SpamScope can use [Apache Tika](https://tika.apache.org/) to parse every attachments.
The Apache Tika toolkit detects and extracts metadata and text from over a thousand different file types (such as PPT, XLS, and PDF).
To use Apache Tika in SpamScope you must install [tika-app-python](https://github.com/fedelemantuano/tika-app-python) with `pip` and [Apache Tika](https://tika.apache.org/download.html).
## Thug (optional)
From release v1.3 SpamScope can analyze Javascript and HTML attachments with [Thug](https://github.com/buffer/thug).
If you want to analyze the attachments with Thug, follow [these instructions](http://buffer.github.io/thug/doc/build.html) to install it. Enable it in `attachments` section of [main configuration file](./conf/spamscope.example.yml).
What is Thug? From README project:
> Thug is a Python low-interaction honeyclient aimed at mimicing the behavior of a web browser in order to detect and emulate malicious contents.
You can see a complete SpamScope report with Thug analysis [here](https://goo.gl/Y4kWCv).
Thug analysis can be very slow and you can have `heartbeat timeout` errors in Apache Storm.
To avoid any issue set `supervisor.worker.timeout.secs`:
```
nr. user agents * timeout_thug < supervisor.worker.timeout.secs
```
The best value for `threshold` is 1.
## VirusTotal (optional)
It's possible add to results (for mail attachments and sender ip address) the VirusTotal report. You need a private API key.
## Shodan (optional)
It's possible add to results the Shodan report for sender ip address. You need a private API key.
## Elasticsearch (optional)
It's possible to store the results in Elasticsearch. In this case you should install `elasticsearch` package.
## Redis (optional)
It's possible to store the results in Redis. In this case you should install `redis` package.
# Configuration
Read the [example of main configuration file](./conf/spamscope.example.yml).
The default value where SpamScope will search the configuration file is `/etc/spamscope/spamscope.yml`, but it's possible to set the environment variable `SPAMSCOPE_CONF_FILE`:
```
$ export SPAMSCOPE_CONF_FILE=/etc/spamscope/spamscope.yml
```
When you change the configuration file, SpamScope automatically reloads the new changes.
# Installation
You can use:
* [Docker images](./docker/README.md) to run SpamScope with docker engine
* [Ansible](./ansible/README.md): to install and run SpamScope on server
# Topologies
SpamScope comes with six topologies:
- [spamscope_debug](./topologies/spamscope_debug.py): the output are JSON files on file system.
- [spamscope_elasticsearch](./topologies/spamscope_elasticsearch.py): the output are stored in Elasticsearch indexes.
- [spamscope_redis](./topologies/spamscope_redis.py): the output are stored in Redis.
- [spamscope_debug_iter](./topologies/spamscope_debug_iter.py): It uses generator to send mails in topology. The output are JSON files on file system.
- [spamscope_elasticsearch_iter](./topologies/spamscope_elasticsearch_iter.py): It uses generator to send mails in topology. The output are stored in Elasticsearch indexes.
- [spamscope_redis_iter](./topologies/spamscope_redis_iter.py): It uses generator to send mails in topology. The output are stored in Redis.
If you want submit SpamScope topology use `spamscope-topology submit` tool. For more details [see SpamScope cli tools](src/cli/README.md):
```
$ spamscope-topology submit --topology {spamscope_debug,spamscope_elasticsearch,spamscope_redis}
```
It's possible to change the default settings for all Apache Storm options. I suggest to change these options:
- **topology.tick.tuple.freq.secs**: reload configuration of all bolts
- **topology.max.spout.pending**: Apache Storm framework will then throttle your spout as needed to meet the `topology.max.spout.pending` requirement
- **topology.sleep.spout.wait.strategy.time.ms**: max sleep for emit new tuple (mail)
You can use `spamscope-topology submit` to do these changes.
# Important
If you are using Elasticsearch output, I suggest you to use [Elasticsearch templates](./conf/templates) that comes with SpamScope.
# Unittest
SpamScope comes with unittests for each modules. In bolts and spouts there are no special features, all intelligence is in external modules.
All unittests are in [tests folder](tests/).
To have complete tests you should set the followings enviroment variables:
```
$ export THUG_ENABLED=True
$ export VIRUSTOTAL_ENABLED=True
$ export VIRUSTOTAL_APIKEY="your key"
$ export ZEMANA_ENABLED=True
$ export ZEMANA_APIKEY="your key"
$ export ZEMANA_PARTNERID="your partner id"
$ export ZEMANA_USERID="your userid"
$ export SHODAN_ENABLED=True
$ export SHODAN_APIKEY="your key"
$ export SPAMASSASSIN_ENABLED=True
```
# Output example
This is a [raw email](https://goo.gl/wMBfbF) that I analyzed with SpamScope:
- [SpamScope output](https://goo.gl/fr4i7C).
This is another example with [Thug analysis](https://goo.gl/Y4kWCv).
# Screenshots
