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1 1 .. _parallelsecurity:
2 2
3 3 ===========================
4 4 Security details of IPython
5 5 ===========================
6 6
7 7 .. note::
8 8
9 9 This section is not thorough, and IPython.zmq needs a thorough security
10 10 audit.
11 11
12 12 IPython's :mod:`IPython.zmq` package exposes the full power of the
13 13 Python interpreter over a TCP/IP network for the purposes of parallel
14 14 computing. This feature brings up the important question of IPython's security
15 15 model. This document gives details about this model and how it is implemented
16 16 in IPython's architecture.
17 17
18 18 Process and network topology
19 19 ============================
20 20
21 21 To enable parallel computing, IPython has a number of different processes that
22 22 run. These processes are discussed at length in the IPython documentation and
23 23 are summarized here:
24 24
25 25 * The IPython *engine*. This process is a full blown Python
26 26 interpreter in which user code is executed. Multiple
27 27 engines are started to make parallel computing possible.
28 28 * The IPython *hub*. This process monitors a set of
29 29 engines and schedulers, and keeps track of the state of the processes. It listens
30 30 for registration connections from engines and clients, and monitor connections
31 31 from schedulers.
32 32 * The IPython *schedulers*. This is a set of processes that relay commands and results
33 33 between clients and engines. They are typically on the same machine as the controller,
34 34 and listen for connections from engines and clients, but connect to the Hub.
35 35 * The IPython *client*. This process is typically an
36 36 interactive Python process that is used to coordinate the
37 37 engines to get a parallel computation done.
38 38
39 39 Collectively, these processes are called the IPython *cluster*, and the hub and schedulers
40 40 together are referred to as the *controller*.
41 41
42 42
43 43 These processes communicate over any transport supported by ZeroMQ (tcp,pgm,infiniband,ipc)
44 44 with a well defined topology. The IPython hub and schedulers listen on sockets. Upon
45 45 starting, an engine connects to a hub and registers itself, which then informs the engine
46 46 of the connection information for the schedulers, and the engine then connects to the
47 47 schedulers. These engine/hub and engine/scheduler connections persist for the
48 48 lifetime of each engine.
49 49
50 50 The IPython client also connects to the controller processes using a number of socket
51 51 connections. As of writing, this is one socket per scheduler (4), and 3 connections to the
52 52 hub for a total of 7. These connections persist for the lifetime of the client only.
53 53
54 54 A given IPython controller and set of engines engines typically has a relatively
55 55 short lifetime. Typically this lifetime corresponds to the duration of a single parallel
56 56 simulation performed by a single user. Finally, the hub, schedulers, engines, and client
57 57 processes typically execute with the permissions of that same user. More specifically, the
58 58 controller and engines are *not* executed as root or with any other superuser permissions.
59 59
60 60 Application logic
61 61 =================
62 62
63 63 When running the IPython kernel to perform a parallel computation, a user
64 64 utilizes the IPython client to send Python commands and data through the
65 65 IPython schedulers to the IPython engines, where those commands are executed
66 66 and the data processed. The design of IPython ensures that the client is the
67 67 only access point for the capabilities of the engines. That is, the only way
68 68 of addressing the engines is through a client.
69 69
70 70 A user can utilize the client to instruct the IPython engines to execute
71 71 arbitrary Python commands. These Python commands can include calls to the
72 72 system shell, access the filesystem, etc., as required by the user's
73 73 application code. From this perspective, when a user runs an IPython engine on
74 74 a host, that engine has the same capabilities and permissions as the user
75 75 themselves (as if they were logged onto the engine's host with a terminal).
76 76
77 77 Secure network connections
78 78 ==========================
79 79
80 80 Overview
81 81 --------
82 82
83 83 ZeroMQ provides exactly no security. For this reason, users of IPython must be very
84 84 careful in managing connections, because an open TCP/IP socket presents access to
85 85 arbitrary execution as the user on the engine machines. As a result, the default behavior
86 86 of controller processes is to only listen for clients on the loopback interface, and the
87 87 client must establish SSH tunnels to connect to the controller processes.
88 88
89 89 .. warning::
90 90
91 91 If the controller's loopback interface is untrusted, then IPython should be considered
92 92 vulnerable, and this extends to the loopback of all connected clients, which have
93 93 opened a loopback port that is redirected to the controller's loopback port.
94 94
95 95
96 96 SSH
97 97 ---
98 98
99 99 Since ZeroMQ provides no security, SSH tunnels are the primary source of secure
100 100 connections. A connector file, such as `ipcontroller-client.json`, will contain
101 101 information for connecting to the controller, possibly including the address of an
102 102 ssh-server through with the client is to tunnel. The Client object then creates tunnels
103 103 using either [OpenSSH]_ or [Paramiko]_, depending on the platform. If users do not wish to
104 104 use OpenSSH or Paramiko, or the tunneling utilities are insufficient, then they may
105 105 construct the tunnels themselves, and simply connect clients and engines as if the
106 106 controller were on loopback on the connecting machine.
107 107
108 108 .. note::
109 109
110 110 There is not currently tunneling available for engines.
111 111
112 112 Authentication
113 113 --------------
114 114
115 115 To protect users of shared machines, [HMAC]_ digests are used to sign messages, using a
116 116 shared key.
117 117
118 118 The Session object that handles the message protocol uses a unique key to verify valid
119 119 messages. This can be any value specified by the user, but the default behavior is a
120 120 pseudo-random 128-bit number, as generated by `uuid.uuid4()`. This key is used to
121 121 initialize an HMAC object, which digests all messages, and includes that digest as a
122 122 signature and part of the message. Every message that is unpacked (on Controller, Engine,
123 123 and Client) will also be digested by the receiver, ensuring that the sender's key is the
124 124 same as the receiver's. No messages that do not contain this key are acted upon in any
125 125 way. The key itself is never sent over the network.
126 126
127 127 There is exactly one shared key per cluster - it must be the same everywhere. Typically,
128 128 the controller creates this key, and stores it in the private connection files
129 129 `ipython-{engine|client}.json`. These files are typically stored in the
130 130 `~/.ipython/profile_<name>/security` directory, and are maintained as readable only by the
131 131 owner, just as is common practice with a user's keys in their `.ssh` directory.
132 132
133 133 .. warning::
134 134
135 It is important to note that the key authentication, as emphasized by the use of
136 a uuid rather than generating a key with a cryptographic library, provides a
137 defense against *accidental* messages more than it does against malicious attacks.
138 If loopback is compromised, it would be trivial for an attacker to intercept messages
139 and deduce the key, as there is no encryption.
135 It is important to note that the signatures protect against unauthorized messages,
136 but, as there is no encryption, provide exactly no protection of data privacy. It is
137 possible, however, to use a custom serialization scheme (via Session.packer/unpacker
138 traits) that does incorporate your own encryption scheme.
140 139
141 140
142 141
143 142 Specific security vulnerabilities
144 143 =================================
145 144
146 145 There are a number of potential security vulnerabilities present in IPython's
147 146 architecture. In this section we discuss those vulnerabilities and detail how
148 147 the security architecture described above prevents them from being exploited.
149 148
150 149 Unauthorized clients
151 150 --------------------
152 151
153 152 The IPython client can instruct the IPython engines to execute arbitrary
154 153 Python code with the permissions of the user who started the engines. If an
155 154 attacker were able to connect their own hostile IPython client to the IPython
156 155 controller, they could instruct the engines to execute code.
157 156
158 157
159 158 On the first level, this attack is prevented by requiring access to the controller's
160 159 ports, which are recommended to only be open on loopback if the controller is on an
161 160 untrusted local network. If the attacker does have access to the Controller's ports, then
162 161 the attack is prevented by the capabilities based client authentication of the execution
163 162 key. The relevant authentication information is encoded into the JSON file that clients
164 163 must present to gain access to the IPython controller. By limiting the distribution of
165 164 those keys, a user can grant access to only authorized persons, just as with SSH keys.
166 165
167 166 It is highly unlikely that an execution key could be guessed by an attacker
168 167 in a brute force guessing attack. A given instance of the IPython controller
169 168 only runs for a relatively short amount of time (on the order of hours). Thus
170 169 an attacker would have only a limited amount of time to test a search space of
171 170 size 2**128. For added security, users can have arbitrarily long keys.
172 171
173 172 .. warning::
174 173
175 174 If the attacker has gained enough access to intercept loopback connections on *either* the
176 175 controller or client, then a duplicate message can be sent. To protect against this,
177 176 recipients only allow each signature once, and consider duplicates invalid. However,
178 177 the duplicate message could be sent to *another* recipient using the same key,
179 178 and it would be considered valid.
180 179
181 180
182 181 Unauthorized engines
183 182 --------------------
184 183
185 184 If an attacker were able to connect a hostile engine to a user's controller,
186 185 the user might unknowingly send sensitive code or data to the hostile engine.
187 186 This attacker's engine would then have full access to that code and data.
188 187
189 188 This type of attack is prevented in the same way as the unauthorized client
190 189 attack, through the usage of the capabilities based authentication scheme.
191 190
192 191 Unauthorized controllers
193 192 ------------------------
194 193
195 194 It is also possible that an attacker could try to convince a user's IPython
196 195 client or engine to connect to a hostile IPython controller. That controller
197 196 would then have full access to the code and data sent between the IPython
198 197 client and the IPython engines.
199 198
200 199 Again, this attack is prevented through the capabilities in a connection file, which
201 200 ensure that a client or engine connects to the correct controller. It is also important to
202 201 note that the connection files also encode the IP address and port that the controller is
203 202 listening on, so there is little chance of mistakenly connecting to a controller running
204 203 on a different IP address and port.
205 204
206 205 When starting an engine or client, a user must specify the key to use
207 206 for that connection. Thus, in order to introduce a hostile controller, the
208 207 attacker must convince the user to use the key associated with the
209 208 hostile controller. As long as a user is diligent in only using keys from
210 209 trusted sources, this attack is not possible.
211 210
212 211 .. note::
213 212
214 213 I may be wrong, the unauthorized controller may be easier to fake than this.
215 214
216 215 Other security measures
217 216 =======================
218 217
219 218 A number of other measures are taken to further limit the security risks
220 219 involved in running the IPython kernel.
221 220
222 221 First, by default, the IPython controller listens on random port numbers.
223 222 While this can be overridden by the user, in the default configuration, an
224 223 attacker would have to do a port scan to even find a controller to attack.
225 224 When coupled with the relatively short running time of a typical controller
226 225 (on the order of hours), an attacker would have to work extremely hard and
227 226 extremely *fast* to even find a running controller to attack.
228 227
229 228 Second, much of the time, especially when run on supercomputers or clusters,
230 229 the controller is running behind a firewall. Thus, for engines or client to
231 230 connect to the controller:
232 231
233 232 * The different processes have to all be behind the firewall.
234 233
235 234 or:
236 235
237 236 * The user has to use SSH port forwarding to tunnel the
238 237 connections through the firewall.
239 238
240 239 In either case, an attacker is presented with additional barriers that prevent
241 240 attacking or even probing the system.
242 241
243 242 Summary
244 243 =======
245 244
246 245 IPython's architecture has been carefully designed with security in mind. The
247 246 capabilities based authentication model, in conjunction with SSH tunneled
248 247 TCP/IP channels, address the core potential vulnerabilities in the system,
249 248 while still enabling user's to use the system in open networks.
250 249
251 250 .. [RFC5246] <http://tools.ietf.org/html/rfc5246>
252 251
253 252 .. [OpenSSH] <http://www.openssh.com/>
254 253 .. [Paramiko] <http://www.lag.net/paramiko/>
255 254 .. [HMAC] <http://tools.ietf.org/html/rfc2104.html>
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