Module:Sensitive IP Addresses
This module provides an API for information about
IP addresses that Wikipedia considers sensitive. The intention is that this one API can be used for templates, Lua modules, and software using the
MediaWiki Action API such as JavaScript gadgets and bots.
Usage
From templates
Templates wishing to make use of this API need to use an intermediary Lua module to parse the results of API queries. One such module, used to create a wikitable summary of sensitive IPs, exists at Module:Sensitive IP addresses/summary.
From Lua
To load this module from Lua modules, use:
local querySensitiveIPs = require('Module:Sensitive IP addresses/API').query
The query function is called with named parameters. For example:
local result = querySensitiveIPs{
test = {'1.2.3.4', '5.6.7.8'}
}
Parameters
The following parameters are available to the query function:
test
- an array of IP addresses and/or IP ranges to test for sensitivity. IP addresses and ranges can be IPv4 or IPv6, and ranges must be in CIDR notation.
entities
- an array of entity IDs to get information about. An entity is a country or organization which is considered sensitive, and for which blocks should be handled with care. Entity IDs are defined in Module:Sensitive IP addresses/list along with the rest of the sensitive IP data. For example, ushr
is the ID for the United States House of Representatives. If the special ID all
is contained in the array, information about all entities will be included in the result.
format
- the format to return results in. Use json
to return a JSON-formatted string, and use lua
to return a Lua table. If this option is not specified, a Lua table is returned by default.
Results
By default, the query function returns a Lua table, but it can return a JSON object if the format
option is set to json
. Whether Lua or JSON, the structure of the object returned is similar to the structure of query results from the MediaWiki Action API.
Top-level object
The top level object contains exactly one child object. If the query executed successfully, this object has a key of sensitiveips
and contains the query results.
{
"sensitiveips": {
[query results]
}
}
If there were any errors when executing the query, the child of the top-level object has a key of error
and contains error information. The error object has three keys: code
, the error ID; info
, the error message; and *
, a message about where to find the API documentation. The error IDs all have a prefix of "sipa". For example:
{
"error": {
"code": "sipa-invalid-test-string",
"info": "test string #1 'foo' was not a valid IP address or CIDR string",
"*": "See https://en.wikipedia.org/key/Module:Sensitive_IP_addresses/API for API usage"
}
}
Sensitive IPs object
If the query was successful, the sensitiveips
child object will be present and can contain the following objects and arrays:
matches
- an array of IP address objects or IP range objects, where the corresponding IP address or IP range string was specified in the test
query option, and where Wikipedia regards that IP address or IP range as being sensitive. If no IPs or ranges were tested for, or if no matches were found, this array will not be present in the results.
matched-ranges
- an object with CIDR IP range strings as keys, and matched-range objects as values, where the IP range matches one of the IP addresses or IP ranges tested for with the test
query option. If no IPs or ranges were tested for, or if no matches were found, this object will not be present.
entities
- an object with entity IDs as keys, and entity objects as values. An entity is a country or organization which has IP addresses that Wikipedia considers sensitive. Entity IDs are defined in Module:Sensitive IP addresses/list; for example, ushr
is the ID for the United States House of Representatives. Entities will be included in this object if an IP range belonging to them is matched by one of the IP addresses or IP ranges tested for with the test
query option, or if their entity ID is specified in the entities
query option.
entity-ids
- an array of entity ID strings, in the order they are defined in Module:Sensitive IP addresses/list. The entity IDs in this array correspond one-to-one with the entity ID keys of the entities
result object. This array can be useful for outputting the IDs in the same order that they were defined in the list.
IP address objects
An IP address object represents a single IPv4 or IPv6 address that matches a sensitive IP range. IP address objects contain the following fields:
ip
- the string representation of the IP address, e.g. "1.2.3.4" or "2001:d8::ffff:ab:cdef".
type
- the string "ip" (used to differentiate between IP address objects and IP range objects).
ip-version
- the version of the IP protocol the address uses. This is either "IPv4" or "IPv6".
matches-range
- the sensitive IP range that the address matches, in CIDR notation.
entity-id
- the entity ID of the entity that owns the sensitive IP range that the address matches.
IP range objects
An IP range object represents an IPv4 or IPv6 range that overlaps with a sensitive IP range. IP range objects contain the following fields:
range
- the CIDR string representation of the range, e.g. "1.2.3.0/24" or "2001:d8::ffff:ab:0/16".
type
- the string "range" (used to differentiate between IP range objects and IP address objects).
ip-version
- the version of the IP protocol the range uses. This is either "IPv4" or "IPv6".
matches-range
- the sensitive IP range that the tested range overlaps, in CIDR notation.
entity-id
- the entity ID of the entity that owns the sensitive IP range that the tested range overlaps.
Entity objects
An entity object represents a country or organization that has IP ranges which Wikipedia considers sensitive. Entity objects may contain the following fields:
id
- the entity ID. This is a unique string used to identify the entity. This field is always present.
name
- the name of the entity. This is a plain string, containing no wikitext, and is always present.
description
- a description of the entity. This is a string, and may contain wikitext. This field is optional, and may not be present.
reason
- the reason that the entity's IP ranges are sensitive. The possible reasons are political
and technical
.
ipv4-ranges
- an array of IPv4 CIDR strings that belong to the entity, and are considered as sensitive by Wikipedia. This field is optional, and may not be present.
ipv6-ranges
- an array of IPv6 CIDR strings that belong to the entity, and are considered as sensitive by Wikipedia. This field is optional, and may not be present.
notes
- notes about the entity or its ranges. This field is optional, and may not be present.
Examples
Here are some examples of some queries from Lua and the results they produce.
No matches
Query:
querySensitiveIPs{
test = {'1.2.3.4'}
}
Result:
{
["sensitiveips"] = {
}
}
One match
Query:
querySensitiveIPs{
test = {'156.33.5.76'}
}
Result:
{
["sensitiveips"] = {
["matches"] = {
{
["type"] = "ip",
["ip"] = "156.33.5.76",
["ip-version"] = "IPv4",
["matches-range"] = "156.33.0.0/16",
["entity-id"] = "ussenate",
},
},
["matched-ranges"] = {
["156.33.0.0/16"] = {
["range"] = "156.33.0.0/16",
["ip-version"] = "IPv4",
["entity-id"] = "ussenate",
},
},
["entities"] = {
["ussenate"] = {
["id"] = "ussenate",
["name"] = "United States Senate",
["description"] = "the [[United States Senate]]",
["reason"] = "political",
["ipv4Ranges"] = {
"156.33.0.0/16",
},
["ipv6Ranges"] = {
"2620:0:8a0::/48",
"2600:803:618::/48",
}
},
},
["entity-ids"] = {
"ussenate",
},
},
}
One match, JSON output
Query:
Query:
querySensitiveIPs{
format = 'json',
test = {'156.33.5.76'}
}
Result:
{
"sensitiveips":{
"matches":[
{
"type": "ip",
"ip": "156.33.5.76",
"ip-version": "IPv4",
"matches-range": "156.33.0.0/16",
"entity-id": "ussenate"
}
],
"matched-ranges": {
"156.33.0.0/16": {
"range": "156.33.0.0/16",
"ip-version": "IPv4",
"entity-id": "ussenate"
}
},
"entities": {
"ussenate": {
"id": "ussenate",
"name": "United States Senate",
"description": "the [[United States Senate]]",
"reason": "political",
"ipv6Ranges": [
"2620:0:8a0::/48",
"2600:803:618::/48"
],
"ipv4Ranges": [
"156.33.0.0/16"
]
}
},
"entity-ids": [
"ussenate"
]
}
}
Entity IDs
querySensitiveIPs{
format = 'json',
entities = {'usdhs', 'usdoj'}
}
Result:
{
"sensitiveips": {
"entities": {
"usdoj": {
"id": "usdoj",
"name": "United States Department of Justice",
"description": "the [[United States Department of Justice]]",
"reason": "political",
"ipv4Ranges": [
"149.101.0.0/16"
]
},
"usdhs": {
"id": "usdhs",
"name": "United States Department of Homeland Security",
"description": "the [[United States Department of Homeland Security]]",
"reason": "political",
"ipv4Ranges": [
"65.165.132.0/24",
"204.248.24.0/24",
"216.81.80.0/20"
]
}
},
"entity-ids": [
"usdoj",
"usdhs"
]
}
}
Invalid IP error
Query:
querySensitiveIPs{
test = {'foo'}
}
Result:
{
["error"] = {
["code"] = "sipa-invalid-test-string",
["info"] = "test string #1 'foo' was not a valid IP address or CIDR string"
["*"] = "See https://en.wikipedia.org/key/Module:Sensitive_IP_addresses/API for API usage",
}
}
-- This module provides functions for handling sensitive IP addresses.
-- Load modules
local mIP = require('Module:IP')
local IPAddress = mIP.IPAddress
local Subnet = mIP.Subnet
local IPv4Collection = mIP.IPv4Collection
local IPv6Collection = mIP.IPv6Collection
-- Lazily load the jf-JSON module
local JSON
-------------------------------------------------------------------------------
-- Helper functions
-------------------------------------------------------------------------------
local function deepCopy(val)
-- Make a deep copy of a value, but don't worry about self-references or
-- metatables as mw.clone does. If a table in val has a self-reference,
-- you will get an infinite loop, so don't do that.
if type(val) == 'table' then
local ret = {}
for k, v in pairs(val) do
ret[k] = deepCopy(v)
end
return ret
else
return val
end
end
local function deepCopyInto(source, dest)
-- Do a deep copy of a source table into a destination table, ignoring
-- self-references and metatables. If a table in source has a self-reference
-- you will get an infinite loop.
for k, v in pairs(source) do
if type(v) == 'table' then
dest[k] = {}
deepCopyInto(v, dest[k])
else
dest[k] = v
end
end
end
local function removeDuplicates(t)
-- Return a copy of an array with duplicate values removed.
local keys, ret = {}, {}
for i, v in ipairs(t) do
if not keys[v] then
table.insert(ret, v)
keys[v] = true
end
end
return ret
end
-------------------------------------------------------------------------------
-- SensitiveEntity class
-- A country or organization for which blocks must be handled with care.
-- Media organizations may inspect block messages for IP addresses and ranges
-- belonging to these entities and those messages may end up in the press.
-------------------------------------------------------------------------------
local SensitiveEntity = {}
SensitiveEntity.__index = SensitiveEntity
SensitiveEntity.reasons = {
-- The reasons that an entity may be sensitive. Used to verify data in
-- Module:Sensitive IP addresses/list.
political = true,
technical = true,
}
do
-- Private methods
local function addRanges(self, key, collectionConstructor, ranges)
if ranges and ranges[1] then
self[key] = collectionConstructor()
for i, range in ipairs(ranges) do
self[key]:addSubnet(Subnet.new(range))
end
end
end
-- Constructor
function SensitiveEntity.new(data)
local self = setmetatable({}, SensitiveEntity)
-- Set data
self.data = data
addRanges(self, 'v4Collection', IPv4Collection.new, data.ipv4Ranges)
addRanges(self, 'v6Collection', IPv6Collection.new, data.ipv6Ranges)
return self
end
end
function SensitiveEntity:matchesIPOrRange(str)
-- Returns true, matchObj, queryObj if there is a match for the IP address
-- string or CIDR range str in the sensitive entity. Returns false
-- otherwise. matchObj is the Subnet object that was matched, and queryObj
-- is the IPAddress or Subnet object corresponding to the input string.
-- Get the IPAddress or Subnet object for str
local isIP, isSubnet, obj
isIP, obj = pcall(IPAddress.new, str)
if isIP and not obj then
isIP = false
end
if not isIP then
isSubnet, obj = pcall(Subnet.new, str)
if not isSubnet or not obj then
error(string.format(
"'%s' is not a valid IP address or CIDR string",
str
), 2)
end
end
-- Try matching the object to the appropriate collection
local function isInCollection(collection, obj, isIP)
if isIP then
if collection then
local isMatch, matchObj = collection:containsIP(obj)
return isMatch, matchObj, obj
else
return false
end
else
if collection then
local isMatch, matchObj = collection:overlapsSubnet(obj)
return isMatch, matchObj, obj
else
return false
end
end
end
if obj:isIPv4() then
return isInCollection(self.v4Collection, obj, isIP)
else
return isInCollection(self.v6Collection, obj, isIP)
end
end
-------------------------------------------------------------------------------
-- Sensitive IP API
-------------------------------------------------------------------------------
-- This API is used by external tools and gadgets, so it should be kept
-- backwards-compatible. Clients query the API with a query table, and the
-- API returns a response table. The response table is available as a Lua table
-- for other Lua modules, and as JSON for external clients.
-- Example query tables:
--
-- Query IP addresses and ranges:
-- {
-- test = {'1.2.3.4', '4.5.6.0/24', '2001:db8::ff00:12:3456', '2001:db8::ff00:12:0/112'},
-- }
--
-- Query specific entities:
-- {
-- entities = {'ussenate', 'ushr'}
-- }
--
-- Query all entities:
-- {
-- entities = {'all'}
-- }
--
-- Query all entities and format the result as a JSON string:
-- {
-- entities = {'all'},
-- format = 'json'
-- }
--
-- Combined query:
-- {
-- test = {'1.2.3.4', '4.5.6.0/24', '2001:db8::ff00:12:3456', '2001:db8::ff00:12:0/112'},
-- entities = {'ussenate', 'ushr'}
-- }
-- Example response:
--
-- {
-- sensitiveips = {
-- matches = {
-- {
-- ip = '1.2.3.4',
-- type = 'ip',
-- ['ip-version'] = 'IPv4',
-- ['matches-range'] = '1.2.3.0/24',
-- ['entity-id'] = 'entityid'
-- },
-- {
-- range = '4.5.6.0/24',
-- type = 'range',
-- ['ip-version'] = 'IPv4',
-- ['matches-range'] = '4.5.0.0/16',
-- ['entity-id'] = 'entityid'
-- }
-- },
-- ['matched-ranges'] = {
-- ['1.2.3.0/24'] = {
-- range = '1.2.3.0/24',
-- ['ip-version'] = 'IPv4',
-- ['entity-id'] = 'entityid'
-- },
-- ['4.5.0.0/16'] = {
-- range = '4.5.0.0/16',
-- ['ip-version'] = 'IPv4',
-- ['entity-id'] = 'entityid'
-- }
-- },
-- entities = {
-- ['entityid'] = {
-- id = 'entityid',
-- name = 'The entity name',
-- description = 'A description of the entity',
-- ['ipv4-ranges'] = {
-- '1.2.3.0/24',
-- '4.5.0.0/16'
-- '6.7.0.0/16'
-- },
-- ['ipv6-ranges'] = {
-- '2001:db8::ff00:12:0/112'
-- },
-- notes = 'Notes about the entity or its ranges'
-- }
-- }
-- ['entity-ids'] = {
-- 'entityid'
-- }
-- }
-- }
--
-- Response with errors:
--
-- {
-- error = {
-- code = 'example-error',
-- info = 'There was an error',
-- ['*'] = 'See https://en.wikipedia.org/key/Module:Sensitive_IP_addresses for API usage'
-- }
-- }
local function query(options)
-- Make entity objects
local entities, entityIndexes = {}, {}
local data = mw.loadData('Module:Sensitive IP addresses/list')
for i, entityData in ipairs(data) do
entities[entityData.id] = SensitiveEntity.new(entityData)
entityIndexes[entityData.id] = i -- Keep track of the original order
end
local function makeError(code, info, format)
local ret = {['error'] = {
code = code,
info = info,
['*'] = 'See https://en.wikipedia.org/key/Module:Sensitive_IP_addresses/API for API usage',
}}
if format == 'json' then
return mw.text.jsonEncode(ret)
else
return ret
end
end
-- Construct result
local result = {
matches = {},
['matched-ranges'] = {},
entities = {},
['entity-ids'] = {}
}
if type(options) ~= 'table' then
return makeError(
'sipa-options-type-error',
string.format(
"type error in argument #1 of 'query' (expected table, received %s)",
type(options)
)
)
elseif not options.test and not options.entities then
return makeError(
'sipa-blank-options',
"the options table didn't contain a 'test' or an 'entities' key",
options.format
)
end
if options.test then
if type(options.test) ~= 'table' then
return makeError(
'sipa-test-type-error',
string.format(
"'test' options key was type %s (expected table)",
type(options.test)
),
options.format
)
end
for i, testString in ipairs(options.test) do
if type(testString) ~= 'string' then
return makeError(
'sipa-test-string-type-error',
string.format(
"type error in item #%d in the 'test' array (expected string, received %s)",
i,
type(testString)
),
options.format
)
end
for k, entity in pairs(entities) do
-- Try to match the range with the current sensitive entity.
local success, isMatch, matchObj, queryObj = pcall(
entity.matchesIPOrRange,
entity,
testString
)
if not success then
-- The string was invalid.
return makeError(
'sipa-invalid-test-string',
string.format(
"test string #%d '%s' was not a valid IP address or CIDR string",
i,
testString
),
options.format
)
end
if isMatch then
-- The string was a sensitive IP address or subnet.
-- Add match data
local match = {}
-- Quick and dirty hack to find if queryObj is an IPAddress object.
local isIP = queryObj.getNextIP ~= nil and queryObj.isInSubnet ~= nil
if isIP then
match.type = 'ip'
match.ip = tostring(queryObj)
else
match.type = 'range'
match.range = tostring(queryObj)
end
match['ip-version'] = queryObj:getVersion()
match['matches-range'] = matchObj:getCIDR()
match['entity-id'] = entity.data.id
table.insert(result.matches, match)
-- Add the matched range data.
result['matched-ranges'][match['matches-range']] = {
range = match['matches-range'],
['ip-version'] = match['ip-version'],
['entity-id'] = match['entity-id'],
}
-- Add the entity data for the entity we matched.
result.entities[match['entity-id']] = deepCopy(
entities[match['entity-id']].data
)
-- Add the entity ID for the entity we matched.
table.insert(result['entity-ids'], match['entity-id'])
end
end
end
end
-- Add entity data requested explicitly.
if options.entities then
if type(options.entities) ~= 'table' then
return makeError(
'sipa-entities-type-error',
string.format(
"'entities' options key was type %s (expected table)",
type(options.test)
),
options.format
)
end
-- Check the type of all the entity strings, and check if 'all' has
-- been specified.
local isAll = false
for i, entityString in ipairs(options.entities) do
if type(entityString) ~= 'string' then
return makeError(
'sipa-entity-string-type-error',
string.format(
"type error in item #%d in the 'entities' array (expected string, received %s)",
i,
type(entityString)
),
options.format
)
end
if entityString == 'all' then
isAll = true
end
end
if isAll then
-- Add all the entity data.
-- As the final result will contain all the entity data, we can
-- just create the entities and entity-ids subtables from scratch
-- without worrying about what any existing values might be.
result.entities = {}
result['entity-ids'] = {}
for i, entityData in ipairs(data) do
result.entities[entityData.id] = deepCopy(entityData)
result['entity-ids'][i] = entityData.id
end
else
-- Add data for the entities specified.
-- Insert the entity and entity-id subtables if they aren't already
-- present.
for i, entityString in ipairs(options.entities) do
if entities[entityString] then
result.entities[entityString] = deepCopy(
entities[entityString].data
)
table.insert(result['entity-ids'], entityString)
end
end
result['entity-ids'] = removeDuplicates(result['entity-ids'])
table.sort(result['entity-ids'], function(s1, s2)
return entityIndexes[s1] < entityIndexes[s2]
end)
end
end
-- Add any missing reason fields from entities.
for id, entityData in pairs(result.entities) do
entityData.reason = entityData.reason or 'political'
end
-- Wrap the result in an outer layer like the MediaWiki Action API does.
result = {sensitiveips = result}
if options.format == 'json' then
-- Load jf-JSON
JSON = JSON or require('Module:jf-JSON')
JSON.strictTypes = true -- Necessary for correct blank-object encoding
-- Decode a skeleton result JSON string. This ensures that blank objects
-- are re-encoded as blank objects and not as blank arrays.
local jsonResult = JSON:decode([[{"sensitiveips": {
"matches": [],
"matched-ranges": {},
"entities": {},
"entity-ids": []
}}]])
for i, key in ipairs{'matches', 'matched-ranges', 'entities', 'entity-ids'} do
deepCopyInto(result.sensitiveips[key], jsonResult.sensitiveips[key])
end
return JSON:encode(jsonResult)
elseif options.format == nil or options.format == 'lua' then
return result
elseif type(options.format) ~= 'string' then
return makeError(
'sipa-format-type-error',
string.format(
"'format' options key was type %s (expected string or nil)",
type(options.format)
)
)
else
return makeError(
'sipa-invalid-format',
string.format(
"invalid format '%s' (expected 'json' or 'lua')",
type(options.format)
)
)
end
end
--------------------------------------------------------------------------------
-- Exports
--------------------------------------------------------------------------------
local p = {}
function p._isValidSensitivityReason(s)
-- Return true if s is a valid sensitivity reason; otherwise return false.
return s ~= nil and SensitiveEntity.reasons[s] ~= nil
end
function p._getSensitivityReasons(separator, conjunction)
-- Return an string of valid sensitivity reasons, ordered alphabetically.
-- The reasons are separated by an optional separator; if conjunction is
-- specified it is used instead of the last separator, as in
-- mw.text.listToText.
-- Get an array of valid sensitivity reasons.
local reasons = {}
for reason in pairs(SensitiveEntity.reasons) do
reasons[#reasons + 1] = reason
end
table.sort(reasons)
-- Convert arguments if we are being called from wikitext.
if type(separator) == 'table' and type(separator.getParent) == 'function' then
-- separator is a frame object
local frame = separator
separator = frame.args[1]
conjunction = frame.args[2]
end
-- Return a formatted string
return mw.text.listToText(reasons, separator, conjunction)
end
-- Export the API query function
p.query = query
return p