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Published on May 2nd, 2016 📆 | 8534 Views ⚑

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AIEngine — Artificial Inteligent Packet Inspection Engine


https://www.ispeech.org/text.to.speech
AIEngine is a next generation interactive/programmable Python/Ruby/Java packet inspection engine with capabilities of learning without any human intervention, NIDS (Network Intrusion Detection System) functionality, DNS domain classification, network collector, network forensics and many others. AIEngine also helps network/security professionals to identify traffic and develop signatures for use them on NIDS, Firewalls, Traffic classifiers and so on.

The main functionalities of AIEngine are:

  • Support for interacting/programing with the user while the engine is running.
  • Support for PCRE JIT for regex matching.
  • Support for regex graphs (complex detection patterns).
  • Support five types of NetworkStacks (lan,mobile,lan6,virtual and oflow).
  • Support Sets and Bloom filters for IP searches.
  • Support Linux, FreeBSD and MacOS operating systems.
  • Support for HTTP,DNS and SSL Domains matching.
  • Support for banned domains and hosts for HTTP, DNS, SMTP and SSL.
  • Frequency analysis for unknown traffic and auto-regex generation.
  • Generation of Yara signatures.
  • Easy integration with databases (MySQL, Redis, Cassandra, Hadoop, etc…) for data correlation.
  • Easy integration with other packet engines (Netfilter).
  • Support memory clean caches for refresh stored memory information.
  • Support for detect DDoS at network/application layer.
  • Support for rejecting TCP/UDP connections.
  • Support for network forensics on real time.

 

AIEngine 1.4 Released !

Using AIEngine

To use AIEngine(reduce version) just execute the binary aiengine or use the python/ruby/java binding.

cyberpunk@n0where.net:~/c++/aiengine/src$ ./aiengine -h
aiengine 1.4
Mandatory arguments:
  -I [ --input ] arg                Sets the network interface ,pcap file or 
                                    directory with pcap files.

Link Layer optional arguments:
  -q [ --tag ] arg      Selects the tag type of the ethernet layer (vlan,mpls).

TCP optional arguments:
  -t [ --tcp-flows ] arg (=32768) Sets the number of TCP flows on the pool.

UDP optional arguments:
  -u [ --udp-flows ] arg (=16384) Sets the number of UDP flows on the pool.

Regex optional arguments:
  -R [ --enable-signatures ]     Enables the Signature engine.
  -r [ --regex ] arg (=.*)       Sets the regex for evaluate agains the flows.
  -c [ --flow-class ] arg (=all) Uses tcp, udp or all for matches the signature
                 on the flows.
  -m [ --matched-flows ]         Shows the flows that matchs with the regex.
  -j [ --reject-flows ]          Rejects the flows that matchs with the 
                                     regex.
  -w [ --evidence ]              Generates a pcap file with the matching 
                                     regex for forensic analysis.

Frequencies optional arguments:
  -F [ --enable-frequencies ]       Enables the Frequency engine.
  -g [ --group-by ] arg (=dst-port) Groups frequencies by src-ip,dst-ip,src-por
                    t and dst-port.
  -f [ --flow-type ] arg (=tcp)     Uses tcp or udp flows.
  -L [ --enable-learner ]           Enables the Learner engine.
  -k [ --key-learner ] arg (=80)    Sets the key for the Learner engine.
  -b [ --buffer-size ] arg (=64)    Sets the size of the internal buffer for 
                                    generate the regex.
  -y [ --enable-yara ]              Generates a yara signature.

Optional arguments:
  -n [ --stack ] arg (=lan)    Sets the network stack (lan,mobile,lan6,virtual,
                   oflow).
  -d [ --dumpflows ]           Dump the flows to stdout.
  -s [ --statistics ] arg (=0) Show statistics of the network stack (5 levels).
  -T [ --timeout ] arg (=180)  Sets the flows timeout.
  -P [ --protocol ] arg        Show statistics of a specific protocol of the 
                                   network stack.
  -e [ --release ]             Release the caches.
  -l [ --release-cache ] arg   Release a specific cache.
  -p [ --pstatistics ]         Show statistics of the process.
  -h [ --help ]                Show help.
  -v [ --version ]             Show version string.

 

NetworkStack types

AIEngine supports five types of Network stacks depending on the network topology.

  • StackLan (lan) Local Area Network based on IPv4.
  • StackLanIPv6 (lan6) Local Area Network with IPv6 support.
  • StackMobile (mobile) Network Mobile (Gn interface) for IPv4.
  • StackVirtual (virtual) Stack for virtual/cloud environments with VxLan and GRE Transparent.
  • StackOpenFlow (oflow) Stack for openflow environments.

 

Integrating/Program AIEngine with other systems

AIEngine is a python/ruby/java module also that allows to be more flexible in terms of integration with other systems and functionalities. The main objects that the python module provide export are the following ones.

    DNSInfo
    BitcoinInfo
    DatabaseAdaptor (Abstract class)
    DomainName
    DomainNameManager
    Flow
    FlowManager
    Frequencies
    FrequencyGroup
    HTTPInfo
    HTTPUriSet
    IMAPInfo
    IPAbstractSet (Abstract class)
        IPSet
    IPSetManager
    LearnerEngine
    NetworkStack (Abstract class)
        StackLan
        StackLanIPv6
        StackMobile
        StackOpenFlow
        StackVirtual
    POPInfo
    PacketDispatcher
    PacketFrequencies
    Regex
    RegexManager
    SIPInfo
    SMTPInfo
    SSLInfo

For a complete description of the class methods

import pyaiengine
help(pyaiengine)

Check the configuration wiki pages or the examples directory in order to have more interesting examples. [https://bitbucket.org/camp0/aiengine/wiki/Configurations]

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Compile AIEngine binary

$ git clone https://bitbucket.com/camp0/aiengine
$ ./autogen.sh
$ ./configure
$ make

 

Compile AIEngine Python library

The first option for compile the library is using O3 compile optimization, this will generate a small library

$ git clone https://bitbucket.com/camp0/aiengine
$ ./autogen.sh
$ ./configure
$ cd src
$ make python

The second option will compile the library by using the standard pythonic way by using setup.py, this will generate a bigger library size if compare with the previous one.

$ git clone https://bitbucket.com/camp0/aiengine
$ ./autogen.sh
$ ./configure
$ cd src
$ python setup.py build_ext -i

 

Compile AIEngine Ruby library

The ruby library is still on develop phase.

$ git clone https://bitbucket.com/camp0/aiengine
$ ./autogen.sh
$ ./configure
$ cd src
$ make ruby

 

Compile AIEngine Java library

The java library is still on develop phase.

$ git clone https://bitbucket.com/camp0/aiengine
$ ./autogen.sh
$ ./configure
$ cd src
$ make java
$ java -cp ".:/usr/share/java/junit.jar:/usr/share/java/hamcrest/core.jar:./buildjava" org.junit.runner.JUnitCore JunitTestSuite

 

 

Artificial Inteligent Packet Inspection Engine: AIEngine Wiki


Source && Download

https://bitbucket.org/camp0/aiengine/downloads



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