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135 lines
10 KiB
Markdown
135 lines
10 KiB
Markdown
[![Build Status](https://travis-ci.org/vstakhov/rspamd.png)](https://travis-ci.org/vstakhov/rspamd)
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## Introduction
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[Rspamd](https://rspamd.com) is an advanced spam filtering system that allows evaluation of messages by a number of
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rules including regular expressions, statistical analysis and custom services
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such as URL black lists. Each message is analysed by rspamd and given a `spam score`.
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According to this spam score and the user's settings rspamd recommends an action for
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the MTA to apply to the message- for example to pass, reject or add a header.
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Rspamd is designed to process hundreds of messages per second simultaneously and has a number of
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features available.
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## Spam filtering features
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Rspamd distribution contains a number of mail processing features, including such techniques as:
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* **Regular expressions filtering** - allows basic processing of messages, their textual parts, MIME headers and
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SMTP data received by MTA against a set of expressions that includes both normal regular expressions and
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message processing functions. Rspamd expressions are the powerful tool that allows to filter messages based on
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some pre-defined rules. This feature is similar to regular expressions in spamassassin spam filter.
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* **SPF module** that allows to validate a message's sender against the policy defined in the DNS record of sender's domain. You can read
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about SPF policies [here](http://www.openspf.org/). A number of mail systems includes SPF support, such as `gmail` or `yahoo mail`.
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* **DKIM module** validates a message cryptographic signature against a public key placed in the DNS record of sender's domain. Like SPF,
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this technique is widely spread and allows to validate that a message is sent from that specific domain.
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* **DNS black lists** allows to estimate reputation of sender's IP address or network. Rspamd uses a number of DNS lists including such lists as
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`SORBS` or `spamhaus`. However, rspamd doesn't trust any specific DNS list and use a conjunction of estimations instead that allows to
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avoid mistakes and false positives. Rspamd also uses positive and grey DNS lists for checking for trusted senders.
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* **URL black lists** are rather similar to DNS black lists but uses URLs in a message to make an estimation of sender's reputation.
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This technique is very useful for finding malicious or phished domains and filter such mail.
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* **Statistics** - rspamd uses bayesian classifier based on five-gramms of input. This means that the input is estimated not based on individual
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words, but all input is organized in chains that are further estimated by bayesian classifier. This approach allows to achieve better results than
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traditionally used monogramms (or words literally speaking), that is described in details in the following [paper](http://osbf-lua.luaforge.net/papers/osbf-eddc.pdf).
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* **Fuzzy hashes** - for checking of malicious mail patterns rspamd uses so called `fuzzy hashes`. Unlike normal hashes, these structures are targeted to hide
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small differences between text patterns allowing to find similar messages quickly. Rspamd has internal storage of such hashes and allows to block mass spam sendings
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quickly based on user's feedback that specifies messages reputation. Moreover, this allows to feed rspamd with data from [`honeypots`](http://en.wikipedia.org/wiki/Honeypot_(computing)#Spam_versions)
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without polluting the statistical module.
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Rspamd uses the conjunction of different techniques to make the finall decision about a message. This allows to improve the overall quality of filtering and reduce the number of
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false positives (e.g. when a innocent message is badly classified as a spam one). I have tried to simplify rspamd usage by adding the following elements:
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* **Web interface** - rspamd is shipped with the fully functional ajax-based web interface that allows to observe rspamd statistic, to configure rules, weights and lists, to scan
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and learn messages and to view the history of scans. The interface is self-hosted, requires zero configuration and follows the recent web applications standards. You don't need a
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web server or applications server to run web UI - you just need to run rspamd itself and a web browser.
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* **Integration with MTA** - rspamd can work with the most popular mail transfer systems, such as postfix, exim or sendmail. For postfix and sendmail, there is an [`rmilter` project](https://github.com/vstakhov/rmilter),
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whilst for exim there are several solutions to work with rspamd. Should you require MTA integration then please consult with the [integration guide](https://rspamd.com/doc/integration.html).
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* **Easy configuration** - rspamd uses [`UCL` language](https://github.com/vstakhov/libucl) for configuration. UCL is a simple and intuitive language that is focused on easy to read configuration files.
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You have many choices to write your definitions, so use whatever you like (even a strict `JSON` would be OK).
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* **Dynamic tables** - rspamd allows to specify some data as `dynamic maps` that are checked in runtime with updating data when they are changed. Rspamd supports file and HTTP maps.
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## Performance
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Rspamd is designed to be fast. The core of rspamd is written in `C` and uses an event-driven model that allows to process multiple messages simultaneously and without blocking.
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Moreover, a set of techniques is used in rspamd to process messages faster:
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* **Finite state machines processing** - rspamd uses specialized finite state machines for the performance critical tasks to process input faster than a set of regular expressions.
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Of course, it is possible to implement these machines by ordinary `perl regular expressions` but then they won't be compact or human-readable. On the contrary, rspamd optimizes
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such actions as headers processing, received elements extraction, protocol operations by building the concrete automata for an assigned task.
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* **Expressions optimizer** - allows to optimize expressions by execution of `likely false` or `likely true` expressions in order in the branches. That allows to reduce number of
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expensive expressions calls when scanning a message.
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* **Symbols optimizer** - rspamd tries to check first the rules that are frequent or inexpensive in terms of time or CPU resources which allows to block spam before processing of
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expensive rules (rules with negative weights are always checked before other ones).
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* **Event driven model** - rspamd is designed not to block anywhere in the code and knowing that a spam check requires a lot of network operations, rspamd can process many messages
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simultaneously increasing the efficiency of shared DNS caches and other system resources. Moreover, event-driven system normally scales automatically and you won't need to do any
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tuning in the most of cases.
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* **Threaded expressions and statistics** - rspamd allows to perform computation for resources intensive tasks -- such as regular expressions or statistics -- in separate threads pools which
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allows to scale even more on modern multi-core systems.
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* **Clever choice of data structures** - rspamd tries to use the optimal data structure for each task. For example it uses very efficient suffix tries for fast matching of a text
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against a set of multiple patterns. Or it uses radix bit trie for storing IP addresses information that provides O(1) access time complexity.
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## Extensions
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Besides its `C` core, rspamd provides an extensive [Lua](http://lua.org) API to access almost all the features available directly from `C`. Lua is an extremely easy
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to learn programming language though it is powerful enough to implement complex mail filters. In fact rspamd has a significant amount of code written completely in Lua such as
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DNS blacklists checks, user's settings or different maps implementation. You can also write your own filters and rules in Lua adopting rspamd functionality to your needs.
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Furthermore, Lua programs are very fast and their performance is rather [close](http://attractivechaos.github.io/plb/) to pure `C`. However, you should mention that for the most
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of performance critical tasks you usually use the rspamd core functionality than Lua code. Anyway, you can also use `LuaJIT` with rspamd if your goal is maximum performance.
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From the Lua API you can do the following tasks:
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* **Reading the configuration parameters** - Lua code has the full access to the parsed configuration knobs and you can easily modify your plugins behaviour by means of the main
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rspamd configuration
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* **Registering custom filters** - it is more than simple to add your own filters to rspamd: just add new index to the global variable `rspamd_config`:
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~~~lua
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rspamd_config.MYFILTER = function(task)
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-- Do something
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end
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~~~
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* **Full access to the content of messages** - you can access text parts, headers, SMTP data and so on and so forth by using of `task` object. The full list of methods could be found
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[here](https://rspamd.com/doc/lua/task.html).
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* **Pre- and post- filters** - you can register callbacks that are called before or after messages processing to make results more precise or to make some early decision,
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for example to implement a rate limit.
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* **Registering functions for rspamd** - you can write your own functions in Lua to extend rspamd internal expression functions.
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* **Managing statistics** - Lua scripts can define a set of statistical files to be scanned or learned for a specific message allowing to create more complex
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statistical systems, e.g. based on an input language. Moreover, you can even learn rspamd statistic from Lua scripts.
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* **Standalone Lua applications** - you can even write your own worker based on rspamd core and performing some asynchronous logic in Lua. Of course, you can use the
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all features from rspamd core, including such features as non-blocking IO, HTTP client and server, non-blocking redis client, asynchronous DNS, UCL configuration and so on
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and so forth.
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* **API documentation** - rspamd Lua API has an [extensive documentation](https://rspamd.com/doc/lua) where you can find examples, references and the guide about how to extend
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rspamd with Lua.
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## References
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* Home site: <https://rspamd.com>
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* Development: <https://github.com/vstakhov/rspamd>
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