Mirror Mirror on the Wall ========================= The following is an overview of **Tor descriptors**. If you're already familiar with what they are and where to get them then you may want to skip to the end. * :ref:`what-is-a-descriptor` * :ref:`where-do-descriptors-come-from` * :ref:`where-can-i-get-the-current-descriptors` * :ref:`where-can-i-get-past-descriptors` * :ref:`can-i-get-descriptors-from-the-tor-process` * :ref:`can-i-create-descriptors` * :ref:`validating-the-descriptors-content` * :ref:`saving-and-loading-descriptors` * :ref:`putting-it-together` * :ref:`are-there-any-other-parsing-libraries` .. _what-is-a-descriptor: What is a descriptor? --------------------- Tor is made up of two parts: the application and a distributed network of a few thousand volunteer relays. Information about these relays is public, and made up of documents called **descriptors**. There are several different kinds of descriptors, the most common ones being... ================================================================================ =========== Descriptor Type Description ================================================================================ =========== `Server Descriptor <../api/descriptor/server_descriptor.html>`_ Information that relays publish about themselves. Tor clients once downloaded this information, but now they use microdescriptors instead. `ExtraInfo Descriptor <../api/descriptor/extrainfo_descriptor.html>`_ Relay information that Tor clients do not need in order to function. This is self-published, like server descriptors, but not downloaded by default. `Microdescriptor <../api/descriptor/microdescriptor.html>`_ Minimalistic document that just includes the information necessary for Tor clients to work. `Network Status Document <../api/descriptor/networkstatus.html>`_ Though Tor relays are decentralized, the directories that track the overall network are not. These central points are called **directory authorities**, and every hour they publish a document called a **consensus** (aka, network status document). The consensus in turn is made up of **router status entries**. `Router Status Entry <../api/descriptor/router_status_entry.html>`_ Relay information provided by the directory authorities including flags, heuristics used for relay selection, etc. `Hidden Service Descriptor <../api/descriptor/hidden_service.html>`_ Information pertaining to a `Hidden Service `_. These can only be `queried through the tor process `_. ================================================================================ =========== .. _where-do-descriptors-come-from: Where do descriptors come from? ------------------------------- Descriptors fall into two camps: * **Server**, **extra-info**, and **hidden service** descriptors are **self-published documents**. Relays and hidden services publish these about themselves, and so naturally can indicate anything they'd like in them (true or not). These are **self contained documents**, bundling within themselves a signiture Stem can `optionally check <./mirror_mirror_on_the_wall.html#validating-the-descriptors-content>`_. * **Network status documents** (aka **votes**, the **consensus**, and **router status entries** they contain) are created by the **directory authorities**. For a great overview on how this works see `Jordan Wright's article on how the consensus is made `_. **Microdescriptors** are merely a distilled copy of a **server descriptor**, and so belong to the first camp. .. _where-can-i-get-the-current-descriptors: Where can I get the current descriptors? ---------------------------------------- To work Tor needs up-to-date relay information. As such getting the current descriptors is easy: *just download it like Tor does*. Every tor relay provides an **ORPort** and many provide a **DirPort** as well which can both be downloaded from using Stem's `stem.descriptor.remote <../api/descriptor/remote.html>`_ module. Listing relays for instance is as easy as... .. literalinclude:: /_static/example/current_descriptors.py :language: python **Please remember that Tor is a shared resource!** If you're going to contribute much load please consider `running a relay `_ to offset your use. **ORPorts** communicate through the `tor protocol `_, and can be downloaded from by specifying it as the endpoint... .. literalinclude:: /_static/example/descriptor_from_orport.py :language: python **DirPorts** by contrast are simpler and specially designed to offer descriptor information, but not all relays offer one. If no endpoint is specified we default to downloading from the DirPorts of tor's directory authorities. If you would like to see what raw descriptors look like try curling a relay's DirPort. Section 6.2 of `tor's directory specification `_ lists the urls you can try. :: % curl 128.31.0.34:9131/tor/server/all router Unnamed 83.227.81.207 9001 0 9030 identity-ed25519 -----BEGIN ED25519 CERT----- AQQABj3aAV7JzKHjSJjocve8jvnMwmy/Pv2HsSKoymeepddNBU5iAQAgBABw1VVB 965QDxs+wicWj4vNXMKIkKCN4gQhvzqG2UxsgmkaQlsKiEMrIxrzwlazP6od9+hi WZKl3tshd0ekgUB6AAKwlvsrxl9wfy0G/Bf8PVsBftvNCWPwLR4pI3nibQU= -----END ED25519 CERT----- master-key-ed25519 cNVVQfeuUA8bPsInFo+LzVzCiJCgjeIEIb86htlMbII ... .. _where-can-i-get-past-descriptors: Where can I get past descriptors? --------------------------------- Descriptor archives are available from `CollecTor `_. If you need Tor's topology at a prior point in time this is the place to go! With CollecTor you can either read descriptors directly... .. literalinclude:: /_static/example/collector_reading.py :language: python ... or download the descriptors to disk and read them later. .. literalinclude:: /_static/example/collector_caching.py :language: python .. _can-i-get-descriptors-from-the-tor-process: Can I get descriptors from the Tor process? ------------------------------------------- If you already have Tor running on your system then it is already downloading descriptors on your behalf. Reusing these is a great way to keep from burdening the rest of the Tor network. Tor only gets the descriptors that it needs by default, so if you're scripting against Tor you may want to set some of the following in your `torrc `_. Keep in mind that these add a small burden to the network, so don't set them in a widely distributed application. And, of course, please consider `running Tor as a relay `_ so you give back to the network! .. code-block:: lighttpd # Descriptors have a range of time during which they're valid. To get the # most recent descriptor information, regardless of if Tor needs it or not, # set the following. FetchDirInfoEarly 1 FetchDirInfoExtraEarly 1 # Tor doesn't need all descriptors to function. In particular... # # * Tor no longer downloads server descriptors by default, opting # for microdescriptors instead. # # * If you aren't actively using Tor as a client then Tor will # eventually stop downloading descriptor information altogether # to relieve load on the network. # # To download descriptors regardless of if they're needed by the # Tor process or not set... FetchUselessDescriptors 1 # Tor doesn't need extrainfo descriptors to work. If you want Tor to download # them anyway then set... DownloadExtraInfo 1 Now that Tor is happy chugging along, up-to-date descriptors are available through Tor's control socket... .. literalinclude:: /_static/example/descriptor_from_tor_control_socket.py :language: python ... or by reading directly from Tor's data directory... .. literalinclude:: /_static/example/descriptor_from_tor_data_directory.py :language: python .. _can-i-create-descriptors: Can I create descriptors? ------------------------- Besides reading descriptors you can create them too. This is most commonly done for test data. To do so simply use the :func:`~stem.descriptor.__init__.Descriptor.create` method of :class:`~stem.descriptor.__init__.Descriptor` subclasses... .. literalinclude:: /_static/example/create_descriptor.py :language: python Unspecified mandatory fields are filled with mock data. You can also use :func:`~stem.descriptor.__init__.Descriptor.content` to get a string descriptor... .. literalinclude:: /_static/example/create_descriptor_content.py :language: python :: router demo 127.0.0.1 80 0 0 published 2012-03-01 17:15:27 bandwidth 153600 256000 104590 reject *:* onion-key -----BEGIN RSA PUBLIC KEY----- MIGJAoGBAJv5IIWQ+WDWYUdyA/0L8qbIkEVH/cwryZWoIaPAzINfrw1WfNZGtBmg skFtXhOHHqTRN4GPPrZsAIUOQGzQtGb66IQgT4tO/pj+P6QmSCCdTfhvGfgTCsC+ WPi4Fl2qryzTb3QO5r5x7T8OsG2IBUET1bLQzmtbC560SYR49IvVAgMBAAE= -----END RSA PUBLIC KEY----- signing-key ... .. _validating-the-descriptors-content: Validating the descriptor's content ----------------------------------- Stem can optionally validate descriptors, checking their integrity and compliance with Tor's specs. This does the following... * Checks that we have mandatory fields, and that their content conforms with what Tor's spec says they should have. This can be useful when data integrity is important to you since it provides an upfront assurance that the descriptor's correct (no need for 'None' checks). * If you have **pycrypto** we'll validate signatures for descriptor types where that has been implemented (such as server and hidden service descriptors). Prior to Stem 1.4.0 descriptors were validated by default, but this has become opt-in since then. General rule of thumb: if *speed* is your chief concern then leave it off, but if *correctness* or *signature validation* is important then turn it on. Validating is as simple as including **validate = True** in any method that provides descriptors... .. literalinclude:: /_static/example/validate_descriptor_content.py :language: python .. _saving-and-loading-descriptors: Saving and loading descriptors ------------------------------ Tor descriptors are just plaintext documents. As such, if you'd rather not use `Pickle `_ you can persist a descriptor by simply writing it to disk, then reading it back later. .. literalinclude:: /_static/example/saving_and_loading_descriptors.py :language: python Our *server_descriptors* here is a list of :class:`~stem.descriptor.server_descriptor.RelayDescriptor` instances. When we write it to a file this looks like... :: router default 68.229.17.182 443 0 9030 platform Tor 0.2.4.23 on Windows XP protocols Link 1 2 Circuit 1 published 2014-11-17 23:42:38 fingerprint EE04 42C3 6DB6 6903 0816 247F 2607 382A 0783 2D5A uptime 63 bandwidth 5242880 10485760 77824 extra-info-digest 1ABA9FC6B912E755483D0F4F6E9BC1B23A2B7206 ... etc... We can then read it back with :func:`~stem.descriptor.__init__.parse_file` by telling it the type of descriptors we're reading... .. literalinclude:: /_static/example/read_with_parse_file.py :language: python For an example of doing this with a consensus document `see here `_. .. _putting-it-together: Putting it together... ---------------------- As discussed above there are four methods for reading descriptors... * Download descriptors directly with `stem.descriptor.remote <../api/descriptor/remote.html>`_. * Read a single file with :func:`~stem.descriptor.__init__.parse_file`. * Read multiple files or an archive with the `DescriptorReader <../api/descriptor/reader.html>`_. * Requesting them from Tor with :class:`~stem.control.Controller` methods like :func:`~stem.control.Controller.get_server_descriptors` and :func:`~stem.control.Controller.get_network_statuses`. Now lets say you want to figure out who the *biggest* exit relays are. You could use any of the methods above, but for this example we'll use `stem.descriptor.remote <../api/descriptor/remote.html>`_... .. literalinclude:: /_static/example/tor_descriptors.py :language: python :: % python example.py 1. herngaard (40.95 MB/s) 2. chaoscomputerclub19 (40.43 MB/s) 3. chaoscomputerclub18 (40.02 MB/s) 4. chaoscomputerclub20 (38.98 MB/s) 5. wannabe (38.63 MB/s) 6. dorrisdeebrown (38.48 MB/s) 7. manning2 (38.20 MB/s) 8. chaoscomputerclub21 (36.90 MB/s) 9. TorLand1 (36.22 MB/s) 10. bolobolo1 (35.93 MB/s) 11. manning1 (35.39 MB/s) 12. gorz (34.10 MB/s) 13. ndnr1 (25.36 MB/s) 14. politkovskaja2 (24.93 MB/s) 15. wau (24.72 MB/s) .. _are-there-any-other-parsing-libraries: Are there any other parsing libraries? -------------------------------------- Yup! Stem isn't the only game in town when it comes to parsing. `Metrics-lib `_ is a highly mature parsing library for Java, and `Zoossh `_ is available for Go. Each library has its own capabilities... .. role:: red .. role:: green =========================== ===================== =================== ============== Capability Stem Metrics-lib Zoossh =========================== ===================== =================== ============== Language :green:`Python` :green:`Java` :green:`Go` Checks signatures :green:`Mostly` :red:`No` :red:`No` Create new descriptors :green:`Yes` :red:`No` :red:`No` Lazy parsing :green:`Yes` :red:`No` :green:`Yes` Type detection by @type :green:`Yes` :green:`Yes` :green:`Yes` Type detection by filename :green:`Yes` :red:`No` :red:`No` Packages :green:`Several` :red:`None` :red:`None` **Can Read/Download From** Files :green:`Yes` :green:`Yes` :green:`Yes` Tarballs :green:`Yes` :green:`Yes` :red:`No` Tor Process :green:`Yes` :red:`No` :red:`No` Directory Authorities :green:`Yes` :green:`Yes` :red:`No` CollecTor :red:`No` :green:`Yes` :red:`No` **Supported Types** Server Descriptors :green:`Yes` :green:`Yes` :green:`Partly` Extrainfo Descriptors :green:`Yes` :green:`Yes` :red:`No` Microdescriptors :green:`Yes` :green:`Yes` :red:`No` Consensus :green:`Yes` :green:`Yes` :green:`Partly` Bridge Descriptors :green:`Yes` :green:`Yes` :red:`No` Hidden Service Descriptors :green:`Yes` :red:`No` :red:`No` Bridge Pool Assignments :red:`No` :green:`Yes` :red:`No` Torperf :red:`No` :green:`Yes` :red:`No` Tordnsel :green:`Yes` :green:`Yes` :red:`No` **Benchmarks** Server Descriptors :green:`0.60 ms` :green:`0.29 ms` :green:`0.46 ms` Extrainfo Descriptors :green:`0.40 ms` :green:`0.22 ms` :red:`unsupported` Microdescriptors :green:`0.33 ms` :green:`0.07 ms` :red:`unsupported` Consensus :green:`865.72 ms` :green:`246.71 ms` :green:`83.00 ms` Benchmarked With Commit :green:`c01a9cd` :green:`8767f3e` :green:`2380e55` Language Interpreter :green:`Python 3.5.1` :green:`Java 1.7.0` :green:`Go 1.5.2` =========================== ===================== =================== ============== Few things to note about these benchmarks... * **Zoossh is the fastest.** Its benchmarks were at a disadvantage due to not reading from tarballs. * Your Python version makes a very large difference for Stem. For instance, with Python 2.7 reading a consensus takes **1,290.84 ms** (almost twice as long). * Metrics-lib and Stem can both read from compressed tarballs at a small performance cost. For instance, Metrics-lib can read an `lzma compressed <../faq.html#how-do-i-read-tar-xz-descriptor-archives>`_ consensus in **255.76 ms** and Stem can do it in **902.75 ms**. So what does code with each of these look like? Stem Example ------------ * `Benchmark Script <../.../../_static/example/benchmark_stem.py>`_ .. literalinclude:: /_static/example/benchmark_server_descriptor_stem.py :language: python Metrics-lib Example ------------------- * `Benchmark Script <../.../../_static/example/benchmark_metrics_lib.java>`_ .. literalinclude:: /_static/example/benchmark_server_descriptor_metrics_lib.java :language: java Zoossh Example -------------- * `Benchmark Script <../.../../_static/example/benchmark_zoossh.go>`_ .. literalinclude:: /_static/example/benchmark_server_descriptor_zoossh.go :language: go