Query business risk control API

Query Business Wind Control API

Functional description

Submit cell phone number and p, query business style control.

Call Address

Support Android、iOS and Web Use of the Platform**

POST https://api.verification.jpush.cn/v2/web/queryBusinessRisk

Call Authentication

See for more information REST API Overview Authentication Note.

Example request

curl --insecure -X POST -v https://api.verification.jpush.cn/v2/web/queryBusinessRisk -H "Content-Type: application/json" -u "7d431e42dfa6a6d693ac2d04:5e987ac6d2e04d95a9d8f0d1" -d '{ "phone": 13554164901, "exID": "1234566", "ip": "127.0.0.1" }'

           curl --insecure -X POST -v https://api.verification.jpush.cn/v2/web/queryBusinessRisk -H "Content-Type: application/json" -u "7d431e42dfa6a6d693ac2d04:5e987ac6d2e04d95a9d8f0d1" -d '{
 "phone": 13554164901,
 "exID": "1234566",
 "ip": "127.0.0.1"
 }'

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** Request parameters**

Keyword	Type	Options	Meaning
phone	String	Required	Ask for risk cell number.
ip	String	Optional	Query risk ip
exID	String	Optional	Developer custom id, not required

Response Example

Request succeeded

{ "id": 576044766492467200, "code": 0, "content": "success", "exID": "", "score": 900, "tags": [ "F24004" ], "detail": { "F24004": { "score": 900 } } }

           {
 "id": 576044766492467200,
 "code": 0,
 "content": "success",
 "exID": "",
 "score": 900,
 "tags": [
 "F24004"
 ],
 "detail": {
 "F24004": {
 "score": 900
 }
 }
}

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** Request failed**

{ "code": 1802, "content": "auth failed" }

          {
 "code": 1802,
 "content": "auth failed"
}

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** Response parameters**

Keyword	Type	Meaning
id	Long	Drift. Could be empty if the request goes wrong.
score	String	Risk rating
exID	Integer	Developer custom id if request is empty
tags	String[]	Tab Pool
detail	Object	Risk details
detail.[tag]	Object	Risk labels for details
detail.[tag].score	Integer	Risk label corresponding risk rating
code	Integer	Return Code
content	String	Response Code Reference

** Back score Annotations**

score The field indicates the risk of the current number, the higher the score, the greater the risk, and the value range is: [0,] 900]。
Based on Jiguang The experience of the security certification team.score The operational meaning of field values is as follows (for information purposes only, it can be adapted from the actual scene):

Value	Risk level	MeaningDescription
0	Low risk	Normal release
300	Medium risk	Markable observation of user follow-up before further decision-making
600	Medium and high risk	Further security clearance or direct operational restrictions
900	High risk	Direct operational constraints

** Back Tags Annotations**

There are differences in the labels returned in different business scenarios, as follows:

Code	Label	MeaningDescription
(empty)	Normal	Normal
F20001	Custom White List	Self-defined white list of business developers
F20002	Custom Blacklist	Self-defined blacklist of business developers
F21001	Blacklist	Blacklisted account cell phone numbers, devices, etc.
F21002	Account behavioural risk	Identify the risk of cell phone behaviour through account behaviour models.
F21003	Cell phone risk	Unusual risks, such as illegal cell phone numbers, virtual segments, etc., have been identified through account cell phone status.
F21004	Mailbox domain name anomaly	Unusual risk identified through blacklist and status of account mailbox domain names
F21005	The account number is abnormal.	Identification of account abnormality risk through parameters such as account number IP, equipment environment, etc.
F21006	BatchRegistrationAccount risk	There's a lot of cheating through the use of more equipment and machine change.RegistrationAccount
F21007	User small number risk	Recognize real people manuallyRegistrationMultiple Platforms
F21008	The pig-kill account.	The hog-killer fraud that was identified through the history of the related account and the identity of the pig-killer. Household
F21009	Advertising flow account number	Identified accounts of advertising channel fraud through related account history and advertising channel characteristics
F23001	IP Environmental Anomalous	IP for very good IP or malicious IP paragraphs
F23002	IP Blacklist	IP Blacklist for Hit Risk
F23003	IP behaviour abnormal	IP behaviour abnormal, risk of cheating
F23004	IP Anomalous Gathering	IP, abnormally concentrated. There's a risk of gang cheating.
F24001	Device Blacklist	High-risk equipment, mainly in the categories of high-risk equipment risk labels, black-product feature equipment, etc.
F24002	Equipment amassion abnormal.	Anomalous performance of equipment at ip, environment, etc.
F24003	Equipment behaviour abnormal.	There's been anomalous behavior in the history of the equipment with crowdsourcing, brushing, etc.
F24004	The equipment environment is abnormal.	Fraudulent equipment environment, including script environment, simulators, etc.
F25001	Cell phone blacklist.	We hit a blacklist.
F25002	Cell phone's out of order.	There are anomalies in cell phone status and format, such as illegal cell phone numbers, virtual segments, etc.
F25003	Cell phone behavior is abnormal.	An abnormality risk was identified through mobile phone behaviour models.
F25004	Cell phone numbers are gathering abnormally.	Unusual concentration or group risk identified through cell phone cluster model
F25005	Kill the pig's phone number.	We've identified the risk of a pig-killer fraud through a blacklist and a pig-killer model.
F25006	Advertising guide cell phone number	The risk of advertising channel fraud is identified through a blacklist with cell phone numbers and an advertising guide model.
F32001	Marketing activities, wool	By marketing behavior and Logging, identifying the risk of gimmicks like machines, scripts, etc.
F32002	It's a marketing event.	By marketing behavior and Recording of the real people's wool risk.
F32003	Risk of fraudulent marketing activities	Identification of suspected risk of marketing fraud through analysis of marketing activity behaviour models
F33001	Content fraud risk	Activation of scenes by means of an associated account, by means of a letter, a compliment, etc. and History, identifying fraud risks
F33002	Content flow risk	Activation of scenes by means of an associated account, by means of a letter, a compliment, etc. and Historical records, identify the flow risk.
F33003	False brushing risk	Activation of scenes by means of an associated account, by means of a letter, a compliment, etc. and Historic record, identifying the risk of fraudulent brushing.
F33004	Emotional fraud risk	Activation of scenes through associated account numbers, comments, nicknames, etc. and Historic records.
F33005	Fraud risk of enrichment	Activation of scenes through associated account numbers, comments, nicknames, etc. and Historical record, identifying the risk of fraud
F33006	Flow of fraud risk	Activation of scenes through associated account numbers, comments, nicknames, etc. and Historical records, identifying the risk of diversion fraud
F33007	Counterfeiting fraud risk	Activation of scenes through associated account numbers, comments, nicknames, etc. and History.
F33008	Fraud Blacklist	There is a risk of historical fraud in equipment connection networks
F34001	Suspected reptile risk	Identification of suspected machine reptile risk through content access records and behaviour
F35001	Value of fraud risk	Identification of fraud risk through filling behaviour and historical records
F35002	Unusual refund risk	Identification of the risk of an abnormal refund through the conduct of the filling and historical record
F36001	Unusual channel activated.	Activation of counterfeit equipment through crowdsourcing, virtual equipment, machine scripts, etc.
F36002	Abnormal Advertising Click	Counterfeiting devices through crowdsourcing, virtual equipment, machine scripts, etc.
F37001	It's like a cow party.	Identification of suspected bison through the actions of electricians and historical records
F38001	Suspected recording	It's suspected of being a fake device.