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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 .. note::
109
110 There is not currently tunneling available for engines.
111 108
112 109 Authentication
113 110 --------------
114 111
115 112 To protect users of shared machines, [HMAC]_ digests are used to sign messages, using a
116 113 shared key.
117 114
118 115 The Session object that handles the message protocol uses a unique key to verify valid
119 116 messages. This can be any value specified by the user, but the default behavior is a
120 117 pseudo-random 128-bit number, as generated by `uuid.uuid4()`. This key is used to
121 118 initialize an HMAC object, which digests all messages, and includes that digest as a
122 119 signature and part of the message. Every message that is unpacked (on Controller, Engine,
123 120 and Client) will also be digested by the receiver, ensuring that the sender's key is the
124 121 same as the receiver's. No messages that do not contain this key are acted upon in any
125 122 way. The key itself is never sent over the network.
126 123
127 124 There is exactly one shared key per cluster - it must be the same everywhere. Typically,
128 125 the controller creates this key, and stores it in the private connection files
129 126 `ipython-{engine|client}.json`. These files are typically stored in the
130 127 `~/.ipython/profile_<name>/security` directory, and are maintained as readable only by the
131 128 owner, just as is common practice with a user's keys in their `.ssh` directory.
132 129
133 130 .. warning::
134 131
135 132 It is important to note that the signatures protect against unauthorized messages,
136 133 but, as there is no encryption, provide exactly no protection of data privacy. It is
137 134 possible, however, to use a custom serialization scheme (via Session.packer/unpacker
138 135 traits) that does incorporate your own encryption scheme.
139 136
140 137
141 138
142 139 Specific security vulnerabilities
143 140 =================================
144 141
145 142 There are a number of potential security vulnerabilities present in IPython's
146 143 architecture. In this section we discuss those vulnerabilities and detail how
147 144 the security architecture described above prevents them from being exploited.
148 145
149 146 Unauthorized clients
150 147 --------------------
151 148
152 149 The IPython client can instruct the IPython engines to execute arbitrary
153 150 Python code with the permissions of the user who started the engines. If an
154 151 attacker were able to connect their own hostile IPython client to the IPython
155 152 controller, they could instruct the engines to execute code.
156 153
157 154
158 155 On the first level, this attack is prevented by requiring access to the controller's
159 156 ports, which are recommended to only be open on loopback if the controller is on an
160 157 untrusted local network. If the attacker does have access to the Controller's ports, then
161 158 the attack is prevented by the capabilities based client authentication of the execution
162 159 key. The relevant authentication information is encoded into the JSON file that clients
163 160 must present to gain access to the IPython controller. By limiting the distribution of
164 161 those keys, a user can grant access to only authorized persons, just as with SSH keys.
165 162
166 163 It is highly unlikely that an execution key could be guessed by an attacker
167 164 in a brute force guessing attack. A given instance of the IPython controller
168 165 only runs for a relatively short amount of time (on the order of hours). Thus
169 166 an attacker would have only a limited amount of time to test a search space of
170 167 size 2**128. For added security, users can have arbitrarily long keys.
171 168
172 169 .. warning::
173 170
174 171 If the attacker has gained enough access to intercept loopback connections on *either* the
175 172 controller or client, then a duplicate message can be sent. To protect against this,
176 173 recipients only allow each signature once, and consider duplicates invalid. However,
177 174 the duplicate message could be sent to *another* recipient using the same key,
178 175 and it would be considered valid.
179 176
180 177
181 178 Unauthorized engines
182 179 --------------------
183 180
184 181 If an attacker were able to connect a hostile engine to a user's controller,
185 182 the user might unknowingly send sensitive code or data to the hostile engine.
186 183 This attacker's engine would then have full access to that code and data.
187 184
188 185 This type of attack is prevented in the same way as the unauthorized client
189 186 attack, through the usage of the capabilities based authentication scheme.
190 187
191 188 Unauthorized controllers
192 189 ------------------------
193 190
194 191 It is also possible that an attacker could try to convince a user's IPython
195 192 client or engine to connect to a hostile IPython controller. That controller
196 193 would then have full access to the code and data sent between the IPython
197 194 client and the IPython engines.
198 195
199 196 Again, this attack is prevented through the capabilities in a connection file, which
200 197 ensure that a client or engine connects to the correct controller. It is also important to
201 198 note that the connection files also encode the IP address and port that the controller is
202 199 listening on, so there is little chance of mistakenly connecting to a controller running
203 200 on a different IP address and port.
204 201
205 202 When starting an engine or client, a user must specify the key to use
206 203 for that connection. Thus, in order to introduce a hostile controller, the
207 204 attacker must convince the user to use the key associated with the
208 205 hostile controller. As long as a user is diligent in only using keys from
209 206 trusted sources, this attack is not possible.
210 207
211 208 .. note::
212 209
213 210 I may be wrong, the unauthorized controller may be easier to fake than this.
214 211
215 212 Other security measures
216 213 =======================
217 214
218 215 A number of other measures are taken to further limit the security risks
219 216 involved in running the IPython kernel.
220 217
221 218 First, by default, the IPython controller listens on random port numbers.
222 219 While this can be overridden by the user, in the default configuration, an
223 220 attacker would have to do a port scan to even find a controller to attack.
224 221 When coupled with the relatively short running time of a typical controller
225 222 (on the order of hours), an attacker would have to work extremely hard and
226 223 extremely *fast* to even find a running controller to attack.
227 224
228 225 Second, much of the time, especially when run on supercomputers or clusters,
229 226 the controller is running behind a firewall. Thus, for engines or client to
230 227 connect to the controller:
231 228
232 229 * The different processes have to all be behind the firewall.
233 230
234 231 or:
235 232
236 233 * The user has to use SSH port forwarding to tunnel the
237 234 connections through the firewall.
238 235
239 236 In either case, an attacker is presented with additional barriers that prevent
240 237 attacking or even probing the system.
241 238
242 239 Summary
243 240 =======
244 241
245 242 IPython's architecture has been carefully designed with security in mind. The
246 243 capabilities based authentication model, in conjunction with SSH tunneled
247 244 TCP/IP channels, address the core potential vulnerabilities in the system,
248 245 while still enabling user's to use the system in open networks.
249 246
250 247 .. [RFC5246] <http://tools.ietf.org/html/rfc5246>
251 248
252 249 .. [OpenSSH] <http://www.openssh.com/>
253 250 .. [Paramiko] <http://www.lag.net/paramiko/>
254 251 .. [HMAC] <http://tools.ietf.org/html/rfc2104.html>
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