khskekec/libre-link-up-http-dump.md

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HTTP dump of Libre Link Up used in combination with FreeStyle Libre 3

Raw

libre-link-up-http-dump.md

LibreLinkUp HTTP-Dump

This document describes the HTTP communication of LibreLinkUp which functions as follower app to receive cgm data. Some data in the responses were masked.

Context

This dump was created on an android device with LibreLinkUp app. Capturing was done with HttpToolkit over adb.

API Url

The global api url is https://api.libreview.io. If you are placed in europe you can use https://api-eu.libreview.io instead.

Headers

The following list includes general purpose headers but also specific ones which are required to get correct responses:

General purpose

'accept-encoding': 'gzip'
'cache-control': 'no-cache'
'connection': 'Keep-Alive'
'content-type': 'application/json'

Specific

The following headers are required and needs to be setted to get correct responses. There might be alternative values which are not known.

'product': 'llu.android'
'version': '4.2.1',

Request Flow

To get cgm data from the api it is required to fire at least three requests:

Login and retrieve JWT Token
Get connections of patients to get patientId
Retrieve cgm data of specific patient

Login

This request expects credentials and will return a JWT Token which is required to call auth-needed endpoints.

Endpoint POST /llu/auth/login

Request Body

{
  "email": "[email protected]",
  "password": "$yOurVerySecretPasSw0rd!"
}

Response

{
  "status": 0,
  "data": {
    "user": {
      "id": "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx",
      "firstName": "John",
      "lastName": "Doe",
      "email": "[email protected]",
      "country": "DE",
      "uiLanguage": "de-DE",
      "communicationLanguage": "de-DE",
      "accountType": "pat",
      "uom": "1",
      "dateFormat": "2",
      "timeFormat": "2",
      "emailDay": [
        1
      ],
      "system": {
        "messages": {
          "firstUsePhoenix": 1652399492,
          "firstUsePhoenixReportsDataMerged": 1652399492,
          "lluGettingStartedBanner": 1652399555,
          "lluNewFeatureModal": 1652399526,
          "lluOnboarding": 1652399536,
          "lvWebPostRelease": "3.9.47"
        }
      },
      "details": {},
      "created": 1652399492,
      "lastLogin": 1653140180,
      "programs": {},
      "dateOfBirth": 627609600,
      "practices": {},
      "devices": {},
      "consents": {
        "llu": {
          "policyAccept": 1652399485,
          "touAccept": 1652399485
        }
      }
    },
    "messages": {
      "unread": 0
    },
    "notifications": {
      "unresolved": 0
    },
    "authTicket": {
      "token": "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpZCI6IjZlZGFjNDk2LWQyNGUtMTFlYy04ZTVkLTAyNDJhYzExMDAwMiIsImZpcnN0TmFtZSI6IkhhbGltZSBTZWxjdWsiLCJsYXN0TmFtZSI6Iktla2VjIiwiY291bnRyeSI6IkRFIiwicmVnaW9uIjoiZXUiLCJyb2xlIjoicGF0aWVudCIsInVuaXRzIjoxLCJwcmFjdGljZXMiOltdLCJjIjoxLCJzIjoibGx1LmFuZHJvaWQiLCJleHAiOjE2Njg2OTIzNTh9.MdEzdJ3NrpYS4WVAcuy87Gxzk7EJFHzCtei-y7_XXXX",
      "expires": 1668692358,
      "duration": 15552000000
    },
    "invitations": [
      "xxxxxxxxx"
    ]
  }
}

The JWT Token is present in data.authTicket.token and is valid for nearly 6 month which is quite long. This is extremly long and actually you cannot invalidate this token why you should not share it with anyone.

For the next requests you have to set this token in the headers:

'authorization': Bearer [YOUR_JWT_TOKEN]

Get connections

To be able to retrieve cgm data you have to determine the patientId of the person who is sharing his data with you.

Endpoint GET /llu/connections

Response

{
  "status": 0,
  "data": [
    {
      "id": "xxxxx",
      "patientId": "xxxxxxx",
      "country": "DE",
      "status": 2,
      "firstName": "John",
      "lastName": "Doe",
      "targetLow": 70,
      "targetHigh": 130,
      "uom": 1,
      "sensor": {
        "deviceId": "",
        "sn": "xxxxx",
        "a": 1652400270,
        "w": 60,
        "pt": 4
      },
      "alarmRules": {
        "c": true,
        "h": {
          "on": true,
          "th": 130,
          "thmm": 7.2,
          "d": 1440,
          "f": 0.1
        },
        "f": {
          "th": 55,
          "thmm": 3,
          "d": 30,
          "tl": 10,
          "tlmm": 0.6
        },
        "l": {
          "on": true,
          "th": 70,
          "thmm": 3.9,
          "d": 1440,
          "tl": 10,
          "tlmm": 0.6
        },
        "nd": {
          "i": 20,
          "r": 5,
          "l": 6
        },
        "p": 5,
        "r": 5,
        "std": {}
      },
      "glucoseMeasurement": {
        "FactoryTimestamp": "5/21/2022 1:38:50 PM",
        "Timestamp": "5/21/2022 3:38:50 PM",
        "type": 1,
        "ValueInMgPerDl": 91,
        "TrendArrow": 3,
        "TrendMessage": null,
        "MeasurementColor": 1,
        "GlucoseUnits": 1,
        "Value": 91,
        "isHigh": false,
        "isLow": false
      },
      "glucoseItem": {
        "FactoryTimestamp": "5/21/2022 1:38:50 PM",
        "Timestamp": "5/21/2022 3:38:50 PM",
        "type": 1,
        "ValueInMgPerDl": 91,
        "TrendArrow": 3,
        "TrendMessage": null,
        "MeasurementColor": 1,
        "GlucoseUnits": 1,
        "Value": 91,
        "isHigh": false,
        "isLow": false
      },
      "glucoseAlarm": null,
      "patientDevice": {
        "did": "2d97357e-d250-11ec-b409-0242ac110004",
        "dtid": 40068,
        "v": "3.3.1",
        "ll": 65,
        "hl": 130,
        "u": 1653016896,
        "fixedLowAlarmValues": {
          "mgdl": 60,
          "mmoll": 3.3
        },
        "alarms": false
      },
      "created": 1652399545
    }
  ],
  "ticket": {
    "token": "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpZCI6IjZlZGFjNDk2LWQyNGUtMTFlYy04ZTVkLTAyNDJhYzExMDAwMiIsImZpcnN0TmFtZSI6IkhhbGltZSBTZWxjdWsiLCJsYXN0TmFtZSI6Iktla2VjIiwiY291bnRyeSI6IkRFIiwicmVnaW9uIjoiZXUiLCJyb2xlIjoicGF0aWVudCIsInVuaXRzIjoxLCJwcmFjdGljZXMiOltdLCJjIjoxLCJzIjoibGx1LmFuZHJvaWQiLCJleHAiOjE2Njg2OTIzNTh9.MdEzdJ3NrpYS4WVAcuy87Gxzk7EJFHzCtei-y7_XXXX",
    "expires": 1668692358,
    "duration": 15552000000
  }
}

The datapart includes all persons who are sharing their data with you. To retrieve cgm data you need data[0].patientId.

Get cgm data

Now both prerequirements (JWT Token and Patient ID) are met and you can retrieve the cgm data.

Endpoint GET /llu/connections/{patientId}/graph

Response

{
  "status": 0,
  "data": {
    "connection": {
      "id": "xxxxxxx",
      "patientId": "xxxxxxx",
      "country": "DE",
      "status": 2,
      "firstName": "John",
      "lastName": "Doe",
      "targetLow": 70,
      "targetHigh": 130,
      "uom": 1,
      "sensor": {
        "deviceId": "",
        "sn": "XXXXXXXXXX",
        "a": 1652400270,
        "w": 60,
        "pt": 4
      },
      "alarmRules": {
        "c": true,
        "h": {
          "on": true,
          "th": 130,
          "thmm": 7.2,
          "d": 1440,
          "f": 0.1
        },
        "f": {
          "th": 55,
          "thmm": 3,
          "d": 30,
          "tl": 10,
          "tlmm": 0.6
        },
        "l": {
          "on": true,
          "th": 70,
          "thmm": 3.9,
          "d": 1440,
          "tl": 10,
          "tlmm": 0.6
        },
        "nd": {
          "i": 20,
          "r": 5,
          "l": 6
        },
        "p": 5,
        "r": 5,
        "std": {}
      },
      "glucoseMeasurement": {
        "FactoryTimestamp": "5/21/2022 1:38:50 PM",
        "Timestamp": "5/21/2022 3:38:50 PM",
        "type": 1,
        "ValueInMgPerDl": 91,
        "TrendArrow": 3,
        "TrendMessage": null,
        "MeasurementColor": 1,
        "GlucoseUnits": 1,
        "Value": 91,
        "isHigh": false,
        "isLow": false
      },
      "glucoseItem": {
        "FactoryTimestamp": "5/21/2022 1:38:50 PM",
        "Timestamp": "5/21/2022 3:38:50 PM",
        "type": 1,
        "ValueInMgPerDl": 91,
        "TrendArrow": 3,
        "TrendMessage": null,
        "MeasurementColor": 1,
        "GlucoseUnits": 1,
        "Value": 91,
        "isHigh": false,
        "isLow": false
      },
      "glucoseAlarm": null,
      "patientDevice": {
        "did": "xxxxxxx",
        "dtid": 40068,
        "v": "3.3.1",
        "ll": 65,
        "hl": 130,
        "u": 1653016896,
        "fixedLowAlarmValues": {
          "mgdl": 60,
          "mmoll": 3.3
        },
        "alarms": false
      },
      "created": 1652399545
    },
    "activeSensors": [
      {
        "sensor": {
          "deviceId": "xxxxxx",
          "sn": "xxxxx",
          "a": 1652400270,
          "w": 60,
          "pt": 4
        },
        "device": {
          "did": "xxxxxx",
          "dtid": 40068,
          "v": "3.3.1",
          "ll": 65,
          "hl": 130,
          "u": 1653016896,
          "fixedLowAlarmValues": {
            "mgdl": 60,
            "mmoll": 3.3
          },
          "alarms": false
        }
      },
      {
        "sensor": {
          "deviceId": "xxxxx",
          "sn": "xxxxxx",
          "a": 1652399154,
          "w": 60,
          "pt": 4
        },
        "device": {
          "did": "xxxxxxxxx",
          "dtid": 40068,
          "v": "3.3.1",
          "ll": 70,
          "hl": 250,
          "u": 1652399060,
          "fixedLowAlarmValues": {
            "mgdl": 60,
            "mmoll": 3.3
          },
          "alarms": false
        }
      },
      {
        "sensor": {
          "deviceId": "xxxxx",
          "sn": "xxxxx",
          "a": 1652391830,
          "w": 60,
          "pt": 4
        },
        "device": {
          "did": "xxxxx",
          "dtid": 40068,
          "v": "3.3.1",
          "ll": 70,
          "hl": 250,
          "u": 1652396851,
          "fixedLowAlarmValues": {
            "mgdl": 60,
            "mmoll": 3.3
          },
          "alarms": false
        }
      }
    ],
    "graphData": [
      {
        "FactoryTimestamp": "5/21/2022 1:39:50 AM",
        "Timestamp": "5/21/2022 3:39:50 AM",
        "type": 0,
        "ValueInMgPerDl": 117,
        "MeasurementColor": 1,
        "GlucoseUnits": 1,
        "Value": 117,
        "isHigh": false,
        "isLow": false
      },
      {
        "FactoryTimestamp": "5/21/2022 1:44:51 AM",
        "Timestamp": "5/21/2022 3:44:51 AM",
        "type": 0,
        "ValueInMgPerDl": 115,
        "MeasurementColor": 1,
        "GlucoseUnits": 1,
        "Value": 115,
        "isHigh": false,
        "isLow": false
      },
      {
        "FactoryTimestamp": "5/21/2022 1:49:50 AM",
        "Timestamp": "5/21/2022 3:49:50 AM",
        "type": 0,
        "ValueInMgPerDl": 115,
        "MeasurementColor": 1,
        "GlucoseUnits": 1,
        "Value": 115,
        "isHigh": false,
        "isLow": false
      },
      {
        "FactoryTimestamp": "5/21/2022 1:54:51 AM",
        "Timestamp": "5/21/2022 3:54:51 AM",
        "type": 0,
        "ValueInMgPerDl": 116,
        "MeasurementColor": 1,
        "GlucoseUnits": 1,
        "Value": 116,
        "isHigh": false,
        "isLow": false
      },
      {
        "FactoryTimestamp": "5/21/2022 1:59:50 AM",
        "Timestamp": "5/21/2022 3:59:50 AM",
        "type": 0,
        "ValueInMgPerDl": 116,
        "MeasurementColor": 1,
        "GlucoseUnits": 1,
        "Value": 116,
        "isHigh": false,
        "isLow": false
      },
      {
        "FactoryTimestamp": "5/21/2022 2:04:50 AM",
        "Timestamp": "5/21/2022 4:04:50 AM",
        "type": 0,
        "ValueInMgPerDl": 118,
        "MeasurementColor": 1,
        "GlucoseUnits": 1,
        "Value": 118,
        "isHigh": false,
        "isLow": false
      },
      {
        "FactoryTimestamp": "5/21/2022 2:09:50 AM",
        "Timestamp": "5/21/2022 4:09:50 AM",
        "type": 0,
        "ValueInMgPerDl": 118,
        "MeasurementColor": 1,
        "GlucoseUnits": 1,
        "Value": 118,
        "isHigh": false,
        "isLow": false
      },
      {
        "FactoryTimestamp": "5/21/2022 2:14:51 AM",
        "Timestamp": "5/21/2022 4:14:51 AM",
        "type": 0,
        "ValueInMgPerDl": 115,
        "MeasurementColor": 1,
        "GlucoseUnits": 1,
        "Value": 115,
        "isHigh": false,
        "isLow": false
      }
    ]
  },
  "ticket": {
    "token": "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpZCI6IjZlZGFjNDk2LWQyNGUtMTFlYy04ZTVkLTAyNDJhYzExMDAwMiIsImZpcnN0TmFtZSI6IkhhbGltZSBTZWxjdWsiLCJsYXN0TmFtZSI6Iktla2VjIiwiY291bnRyeSI6IkRFIiwicmVnaW9uIjoiZXUiLCJyb2xlIjoicGF0aWVudCIsInVuaXRzIjoxLCJwcmFjdGljZXMiOltdLCJjIjoxLCJzIjoibGx1LmFuZHJvaWQiLCJleHAiOjE2Njg2OTIzNTl9.LK8Ejr2IDKGM7oiObVYMHC8HV2bPcv6obt7UiEFXXXX",
    "expires": 1668692359,
    "duration": 15552000000
  }
}

The last measurement is present in glucoseMeasurement:

{
  "FactoryTimestamp": "5/21/2022 1:38:50 PM",
  "Timestamp": "5/21/2022 3:38:50 PM",
  "type": 1,
  "ValueInMgPerDl": 91,
  "TrendArrow": 3,
  "TrendMessage": null,
  "MeasurementColor": 1,
  "GlucoseUnits": 1,
  "Value": 91,
  "isHigh": false,
  "isLow": false
}

Instead you can find historical measurements in graphData. The data has the same shape as above.

Contact

Selcuk Kekec

E-mail: [email protected]

gjkoolen commented Feb 2, 2026

Hello everyone. I wrote a Python script that reads out my glucose level every 5 minutes, to send me a Telegram message when my sugar is not following a (very simple) model. So it warns me when I have to use insulin. I use this for more than a year and it helped me reduce my HbA1C significantly. The script runs on a Raspberry Pi Zero. The only drawback is that every time I eat (and thus use insulin), I send a Telegram message to the bot. This information is needed for the model.
This glucose checker is very useful when for instance the whole night my level is high, but just under the alarm level. I will be awakened by the (annoying) Telegram message receive sound. Or when glucose level starts rising again 2 hours after a meal. Also then I am alerted and can compensate with insulin, to remain well under the alarm level.
The code consists of 2 services: the glucose checker service and Telegram bot service. Connected by an MQTT broker.
It is on my wish list to train an ML model, based on glucose data from the past.
If anyone is interested in the code, or in having more information, please let me know.

Mynuggets-dev commented Feb 2, 2026 via email

this seems good in concept but why are you sharing info with the bot and not just storing the data to a cache and getting the bot to access that data, ' work smarter not harder '

…

On Tue, Feb 3, 2026 at 12:27 AM gjkoolen ***@***.***> wrote: ***@***.**** commented on this gist. ------------------------------ Hello everyone. I wrote a Python script that reads out my glucose level every 5 minutes, to send me a Telegram message when my sugar is not following a (very simple) model. So it warns me when I have to use insulin. I use this for more than a year and it helped me reduce my HbA1C significantly. The script runs on a Raspberry Pi Zero. The only drawback is that every time I eat (and thus use insulin), I send a Telegram message to the bot. This information is needed for the model. This glucose checker is very useful when for instance the whole night my level is high, but just under the alarm level. I will be awakened by the (annoying) Telegram message receive sound. Or when glucose level starts rising again 2 hours after a meal. Also then I am alerted and can compensate with insulin, to remain well under the alarm level. The code consists of 2 services: the glucose checker service and Telegram bot service. Connected by an MQTT broker. It is on my wish list to train an ML model, based on glucose data from the past. If anyone is interested in the code, or in having more information, please let me know. — Reply to this email directly, view it on GitHub <https://gist.github.com/khskekec/6c13ba01b10d3018d816706a32ae8ab2#gistcomment-5966491> or unsubscribe <https://github.com/notifications/unsubscribe-auth/BO5CRSP5REUJR6GALLYHALL4J5GFHBFKMF2HI4TJMJ2XIZLTSOBKK5TBNR2WLKJRGEYTAOBXG4YTNJDOMFWWLKDBMN2G64S7NFSIFJLWMFWHKZNEORZHKZNENZQW2ZN3ORUHEZLBMRPXAYLSORUWG2LQMFXHIX3BMN2GS5TJOR4YFJLWMFWHKZNEM5UXG5FENZQW2ZNLORUHEZLBMRPXI6LQMWWHG5LCNJSWG5C7OR4XAZNLI5UXG5CDN5WW2ZLOOSTHI33QNFRXHEMCUR2HS4DFURTWS43UUV3GC3DVMWUTCMJWGQZTGMZVHCTXI4TJM5TWK4VGMNZGKYLUMU> . You are receiving this email because you commented on the thread. Triage notifications on the go with GitHub Mobile for iOS <https://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675> or Android <https://play.google.com/store/apps/details?id=com.github.android&referrer=utm_campaign%3Dnotification-email%26utm_medium%3Demail%26utm_source%3Dgithub> .

Mynuggets-dev commented Feb 2, 2026 via email

I use the same idea in my app, all backend is python, everything displayed in compiled data from 1 ' current levels ' every 1 min with postgres db . Are you using middleware etc for the bot not letting it directly touch data etc? I have to ask, were you born with diabetes? " Or when glucose level starts rising again 2 hours after a meal. Also then I am alerted and can compensate with insulin " line makes no sense, you should be compensating with insulin before eating, not reacting to an older level rise, if getting higher all night, best to go see a trained professional or your GP and revise your care plans and doses, don't use apps to ' fix ' yourself, you're not broken.

…

gjkoolen commented Feb 2, 2026

@Mynuggets-dev Good questions. My Python script only stores data of the last 30 minutes, and uses that to determine if all is well. No DB needed. The Telegram bot is only to bridge between my house MQTT and external Telegram. The bot only relays between my phone and the Python script (via Telegram and MQTT). I got diabetes when I was 43 (in 2009).
Before each meal I administer insulin, and then usually it goes up and then down to normal level after 3 hrs. However, sometimes at t=2 hrs the Python script notices that the level goes not down anymore, but up again (depending on meal). In such cases I get a message, I compensate, and the final curve looks very good. My doctor asked me how I got my levels so flat, and I told him I use control techniques (is also my job) and this Python script.
Same at nighttime: usually very good, but sometimes I miscalculate, and then it's good to receive a message so I can compensate.
Freestyle Libre has a "bug" in my opinion: if my level is above alarm level before I go to sleep, I compensate (of course), but if I don't compensate enough, it can remain the whole night above the alarm level without raising any alarm. Abbott should automatically repeat any alarm after 3 hours in my opinion. Also for such cases this Python script is good.
Hope this explains :-)

Mynuggets-dev commented Feb 2, 2026

@Mynuggets-dev Good questions. My Python script only stores data of the last 30 minutes, and uses that to determine if all is well. No DB needed. The Telegram bot is only to bridge between my house MQTT and external Telegram. The bot only relays between my phone and the Python script (via Telegram and MQTT). I got diabetes when I was 43 (in 2009). Before each meal I administer insulin, and then usually it goes up and then down to normal level after 3 hrs. However, sometimes at t=2 hrs the Python script notices that the level goes not down anymore, but up again (depending on meal). In such cases I get a message, I compensate, and the final curve looks very good. My doctor asked me how I got my levels so flat, and I told him I use control techniques (is also my job) and this Python script. Same at nighttime: usually very good, but sometimes I miscalculate, and then it's good to receive a message so I can compensate. Freestyle Libre has a "bug" in my opinion: if my level is above alarm level before I go to sleep, I compensate (of course), but if I don't compensate enough, it can remain the whole night above the alarm level without raising any alarm. Abbott should automatically repeat any alarm after 3 hours in my opinion. Also for such cases this Python script is good. Hope this explains :-)

yeah in the librelinkup i found they do like data sanitizing and its compressing high / low readings ( 20mins time for insulin for the fat cells etc so 30min could be half the issues for a good source of data ) that's why i just log the readings raw data and compile it myself, all my analytics are python functions i created based on Australian standards etc ( i like the pretty look but advice not to use as a direct refence, and i have handling incase trying to view more data than i have etc eg

and i have discord accounts that can link to a bot etc

and working on widgets too, i get alot of ideas from posts like these and issues, so thanks to anyone that posts for help or ideas 💕

Mynuggets-dev commented Feb 2, 2026

ive been trying to add something to auto log mealtimes based on levels, but thats hard cause if you do it right it shouldnt detect the rapid changes 🤔

Mynuggets-dev commented Feb 2, 2026

feel free to try it, only thing i ask is please don't use it like a source of truth, it can be flawed with my ' skill level ' https://diabetes.mynuggets.dev/

gjkoolen commented Feb 4, 2026

@Mynuggets-dev Great that you exposed your scripting with others with your website! It looks good. Nice example for other developers. I hope one day I will provide machine-learned alerting service to others. At the moment I am too busy with other things. Keep going!

khskekec/libre-link-up-http-dump.md

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LibreLinkUp HTTP-Dump

Context

API Url

Headers

General purpose

Specific

Request Flow

Login

Get connections

Get cgm data

Contact

gjkoolen commented Feb 2, 2026

Uh oh!

Mynuggets-dev commented Feb 2, 2026 via email

Uh oh!

Mynuggets-dev commented Feb 2, 2026 via email

Uh oh!

gjkoolen commented Feb 2, 2026

Uh oh!

Mynuggets-dev commented Feb 2, 2026

Uh oh!

Mynuggets-dev commented Feb 2, 2026

Uh oh!

Mynuggets-dev commented Feb 2, 2026

Uh oh!

gjkoolen commented Feb 4, 2026

Uh oh!