Tag Archives: Diameter

5G / LTE Milenage Security Exploit – Dumping the Vectors

I’ve written about Milenage and SIM based security in the past on this blog, and the component that prevents replay attacks in cellular network authentication is the Sequence Number (Aka SQN) stored on the SIM.

Think of the SQN as an incrementing odometer of authentication vectors. Odometers can go forward, but never backwards. So if a challenge comes in with an SQN behind the odometer (a lower number), it’s no good.

Why the SQN is important for Milenage Security

Every time the SIM authenticates it ticks up the SQN value, and when authenticating it checks the challenge from the network doesn’t have an SQN that’s behind (lower than) the SQN on the SIM.

Let’s take a practical example of this:

The HSS in the network has SQN for the SIM as 8232, and generates an authentication challenge vector for the SIM which includes the SQN of 8232.
The SIM receives this challenge, and makes sure that the SQN in the SIM, is equal to or less than 8232.
If the authentication passes, the new SQN stored in the SIM is equal to 8232 + 1, as that’s the next valid SQN we’d be expecting, and the HSS incriments the counters it has in the same way.

By constantly increasing the SQN and not allowing it to go backwards, means that even if we pre-generated a valid authentication vector for the SIM, it’d only be valid for as long as the SQN hasn’t been authenticated on the SIM by another authentication request.

Imagine for example that I get sneaky access to an operator’s HSS/AuC, I could get it to generate a stack of authentication challenges that I could use for my nefarious moustache-twirling purposes whenever I wanted.

This attack would work, but this all comes crumbling down if the SIM was to attach to the real network after I’ve generated my stack of authentication challenges.

If the SQN on the SIM passes where it was when the vectors were generated, those vectors would become unusable.

It’s worth pointing out, that it’s not just evil purposes that lead your SQN to get out of Sync; this happens when you’ve got subscriber data split across multiple HSSes for example, and there’s a mechanism to securely catch the HSS’s SQN counter up with the SQN counter in the SIM, without exposing any secrets, but it just ticks the HSS’s SQN up – It never rolls back the SQN in the SIM.

The Flaw – Draining the Pool

The Authentication Information Request is used by a cellular network to authenticate a subscriber, and the Authentication Information Answer is sent back by the HSS containing the challenges (vectors).

When we send this request, we can specify how many authentication challenges (vectors) we want the HSS to generate for us, so how many vectors can you generate?

TS 129 272 says the Number-of-Requested-Vectors AVP is an Unsigned32, which gives us a possible pool of 4,294,967,295 combinations. This means it would be legal / valid to send an Authentication Information Request asking for 4.2 billion vectors.

Source TS 129 272

It’s worth noting that that won’t give us the whole pool.

Sequence numbers (SQN) shall have a length of 48 bits.

TS 133 102

While the SQN in the SIM is 48 bits, that gives us a maximum number of values before we “tick over” the odometer of 281,474,976,710,656.

If we were to send 65,536 Authentication-Information-Requests asking for 4,294,967,295 a piece, we’d have got enough vectors to serve the sub for life.

Except the standard allows for an unlimited number of vectors to be requested, this would allow us to “drain the pool” from an HSS to allow every combination of SQN to be captured, to provide a high degree of certainty that the SQN provided to a SIM is far enough ahead of the current SQN that the SIM does not reject the challenges.

Can we do this?

Our lab has access to HSSes from several major vendors of HSS.

Out of the gate, the Oracle HSS does not allow more than 32 vectors to be requested at the same time, so props to them, but the same is not true of the others, all from major HSS vendors (I won’t name them publicly here).

For the other 3 HSSes we tried from big vendors, all eventually timed out when asking for 4.2 billion vectors (don’t know why that would be *shrug*) from these HSSes, it didn’t get rejected.

This is a lab so monitoring isn’t great but I did see a CPU spike on at least one of the HSSes which suggests maybe it was actually trying to generate this.

Of course, we’ve got PyHSS, the greatest open source HSS out there, and how did this handle the request?

Well, being standards compliant, it did what it was asked – I tested with 1024 vectors I’ll admit, on my little laptop it did take a while. But lo, it worked, spewing forth 1024 vectors to use.

So with that working, I tried with 4,294,967,295…

And I waited. And waited.

And after pegging my CPU for a good while, I had to get back to real life work, and killed the request on the HSS.

In part there’s the fact that PyHSS writes back to a database for each time the SQN is incremented, which is costly in terms of resources, but also that generating Milenage vectors in LTE is doing some pretty heavy cryptographic lifting.

The Risk

Dumping a complete set of vectors with every possible SQN would allow an attacker to spoof base stations, and the subscriber would attach without issue.

Historically this has been very difficult to do for LTE, due to the mutual network authentication, however this would be bypassed in this scenario.

The UE would try for a resync if the SQN is too far forward, which mitigates this somewhat.

Cryptographically, I don’t know enough about the Milenage auth to know if a complete set of possible vectors would widen the attack surface to try and learn something about the keys.

Mitigations / Protections

So how can operators protect ourselves against this kind of attack?

Different commercial HSS vendors handle this differently, Oracle limits this to 32 vectors, and that’s what I’ve updated PyHSS to do, but another big HSS vendor (who I won’t publicly shame) accepts the full 4294967295 vectors, and it crashes that thread, or at least times it out after a period.

If you’ve got a decent Diameter Routing Agent in place you can set your DRA to check to see if someone is using this exploit against your network, and to rewrite the number of requested vectors to a lower number, alert you, or drop the request entirely.

Having common OP keys is dumb, and I advocate to all our operator customers to use OP keys that are unique to each SIM, and use the OPc key derived anyway. This means if one SIM spilled it’s keys, the blast doesn’t extend beyond that card.

In the long term, it’d be good to see 3GPP limit the practical size of the Number-of-Requested-Vectors AVP.

2G/3G Impact

Full disclosure – I don’t really work with 2G/3G stacks much these days, and have not tested this.

MAP is generally pretty bandwidth constrained, and to transfer 280 billion vectors might raise some eyebrows, burn out some STPs and take a long time…

But our “Send Authentication Info” message functions much the same as the Authentication Information Request in Diameter, 3GPP TS 29.002 shows we can set the number of vectors we want:

5GC Vulnerability

This only impacts LTE and 5G NSA subscribers.

TS 29.509 outlines the schema for the Nausf reference point, used for requesting vectors, and there is no option to request multiple vectors.

Summary

If you’ve got baddies with access to your HSS / HLR, you’ve got some problems.

But, with enough time, your pool could get drained for one subscriber at a time.

This isn’t going to get the master OP Key or plaintext Ki values, but this could potentially weaken the Milenage security of your system.

Tuning SCTP Init with Linux’s SCTP module

The other side of the SCTP connection didn’t like my SCTP parameters.

My SCTP INIT looked like this:

By default, Linux includes support for the ECN and Supported Address Types parameters in the SCTP INIT.

But the other side did not like this, it sent back an ERROR stating that:

Okay, apparently it doesn’t like the fact that we support Forward Transmission Sequence Numbers – So how to turn it off?

I’m using P1Sec’s PySCTP library to interact with the SCTP stack, and I couldn’t find any referneces to this in the code, but then I rememberd that PySCTP is just a wrapper for libsctp so I should be able to control it from there.

The Manual (of course) has the answers.

Inside `/proc/sys/net/sctp` we can see all the parameters we can control.

To disable the Forward TSN I need to disable the feature that controls it – Forward Transmission Sequence numbers are introduced in the Partial Reliability Extension (RFC 3758). So it was just a matter of disabling that with:

sysctl -w net.sctp.prsctp_enable=1

And lo, now my SCTP INITs are happy!

Creating a Fixed Line IMS subscriber in PyHSS

I generally do this with Python or via the Swagger UI for the Web UI, but here’s how we can create a fixed-line IMS subscriber in PyHSS, so we can register it with a softphone, without using EAP-AKA.


Firstly we create the AuC object for this password combo.

curl -X 'PUT' \
'http://10.97.0.36:8080/auc/' \
-H 'accept: application/json' \
-H 'Content-Type: application/json' \
-d '{
"ki": "yoursippassword123",
"opc": "",
"amf": "8000",
"sqn": "1"
}'

Get back the AuC ID from the JSON body, we’ll use this to provision the Sub:

 "auc_id": 110,

Next we create the subscriber, the speeds will be 0 as there is no data on the service, but we will add an default APN so the validation passes:

curl -X 'PUT' \
'http://10.97.0.36:8080/subscriber/' \
-H 'accept: application/json' \
-H 'Content-Type: application/json' \
-d '{
"default_apn": 1,
"roaming_rule_list": null,
"apn_list": "0",
"subscribed_rau_tau_timer": 600,
"msisdn": "123451000001",
"ue_ambr_dl": 0,
"ue_ambr_ul": 0,
"imsi": "001001000090001",
"nam": 2,
"enabled": true,
"roaming_enabled": null,
"auc_id": 110
}'

Alright, that’s the basics done, now we’ll create the IMS subscriber.

Provision it:

curl -X 'PUT' \
'http://10.97.0.36:8080/ims_subscriber/' \
-H 'accept: application/json' \
-H 'Content-Type: application/json' \
-d '{
"pcscf_realm": null,
"scscf_realm": null,
"pcscf_active_session": null,
"scscf_peer": null,
"msisdn": "123451000001",
"pcscf_timestamp": null,
"sh_template_path": "default_sh_user_data.xml",
"msisdn_list": "123451000001",
"pcscf_peer": null,
"last_modified": "2024-04-25T00:33:37Z",
"imsi": "001001000090001",
"xcap_profile": null,
"ifc_path": "default_ifc.xml",
"sh_profile": "\n<!-- This container for the XCAP Data for the Subscriber -->\n<RepositoryData>\n <ServiceIndication>ApplicationServer</ServiceIndication>\n <SequenceNumber>0</SequenceNumber>\n <ServiceData>\n <!-- This is the actual XCAP Data for the Subscriber -->\n \n <!-- XCAP Default Template (no XCAP Data stored in Database) -->\n <simservs xmlns=\"http://uri.etsi.org/ngn/params/xml/simservs/xcap\" xmlns:cp=\"urn:ietf:params:xml:ns:common-policy\">\n <originating-identity-presentation active=\"true\" />\n <originating-identity-presentation-restriction active=\"true\">\n <default-behaviour>presentation-not-restricted</default-behaviour>\n </originating-identity-presentation-restriction>\n <communication-diversion active=\"true\">\n <!-- No Answer Time -->\n <NoReplyTimer>20</NoReplyTimer>\n <cp:ruleset>\n <!-- Call Forward All Rule -->\n <cp:rule id=\"rule0\">\n <cp:conditions>\n <communication-diverted />\n </cp:conditions>\n <cp:actions>\n <forward-to>\n <target>sip:[email protected]</target>\n </forward-to>\n </cp:actions>\n </cp:rule>\n <!-- Call Forward Not Registered Rule -->\n <cp:rule id=\"rule1\">\n <cp:conditions>\n <not-registered />\n </cp:conditions>\n <cp:actions>\n <forward-to>\n <target>sip:[email protected]</target>\n </forward-to>\n </cp:actions>\n </cp:rule>\n <!-- Call Forward No Answer Rule -->\n <cp:rule id=\"rule2\">\n <cp:conditions>\n <no-answer />\n </cp:conditions>\n <cp:actions>\n <forward-to>\n <target>sip:[email protected]</target>\n </forward-to>\n </cp:actions>\n </cp:rule>\n <!-- Call Forward Busy Rule -->\n <cp:rule id=\"rule3\">\n <cp:conditions>\n <busy />\n </cp:conditions>\n <cp:actions>\n <forward-to>\n <target>sip:[email protected]</target>\n </forward-to>\n </cp:actions>\n </cp:rule>\n <!-- Call Forward Unreachable Rule -->\n <cp:rule id=\"rule4\">\n <cp:conditions>\n <not-reachable />\n </cp:conditions>\n <cp:actions>\n <forward-to>\n <target>sip:[email protected]</target>\n </forward-to>\n </cp:actions>\n </cp:rule>\n </cp:ruleset>\n </communication-diversion>\n \n <incoming-communication-barring active=\"true\">\n <cp:ruleset>\n <cp:rule id=\"rule0\">\n <cp:conditions />\n <cp:actions>\n <allow>true</allow>\n </cp:actions>\n </cp:rule>\n </cp:ruleset>\n </incoming-communication-barring>\n\n <outgoing-communication-barring active=\"false\">\n </outgoing-communication-barring>\n </simservs>\n\n </ServiceData>\n \n</RepositoryData>\n",
"pcscf": null,
"scscf": null,
"scscf_timestamp": null
}'

And with that we’re done,

We can now register 001001000090001 at our IMS, with password yoursippassword123 which has the MSISDN / phone number 123451000001.

Easy!

Transport Keys & A4 / K4 Keys in EPC & 5GC Networks

If you’re working with the larger SIM vendors, there’s a good chance they key material they send you won’t actually contain the raw Ki values for each card – If it fell into the wrong hands you’d be in big trouble.

Instead, what is more likely is that the SIM vendor shares the Ki generated when mixed with a transport key – So what you receive is not the plaintext version of the Ki data, but rather a ciphered version of it.

But as long as you and the SIM vendor have agreed on the ciphering to use, an the secret to protect it with beforehand, you can read the data as needed.

This is a tricky topic to broach, as transport key implementation, is not covered by the 3GPP, instead it’s a quasi-standard, that is commonly used by SIM vendors and HSS vendors alike – the A4 / K4 Transport Encryption Algorithm.

It’s made up of a few components:

  • K2 is our plaintext key data (Ki or OP)
  • K4 is the secret key used to cipher the Ki value.
  • K7 is the algorithm used (Usually AES128 or AES256).

I won’t explain too much about the crypto, but here’s an example from IoT Connectivity’s KiOpcGenerator tool:

def aes_128_cbc_encrypt(key, text):
"""
implements aes 128b encryption with cbc.
"""
keyb = binascii.unhexlify(key)
textb = binascii.unhexlify(text)
encryptor = AES.new(keyb, AES.MODE_CBC, IV=IV)
ciphertext = encryptor.encrypt(textb)
return ciphertext.hex().upper()

It’s important when defining your electrical profile and the reuqired parameters, to make sure the operator, HSS vendor and SIM vendor are all on the same page regarding if transport keys will be used, what the cipher used will be, and the keys for each batch of SIMs.

Here’s an example from a Huawei HSS with SIMs from G&D:

%%LST K4: HLRSN=1;%%
RETCODE = 0 SUCCESS0001:Operation is successful

        "K4SNO" "ALGTYPE"     "K7SNO" "KEYNAME"
        1       AES128        NONE    G+D

We’re using AES128, and any SIMs produced by G&D for this batch will use that transport key (transport key ID 1 in the HSS), so when adding new SIMs we’ll need to specify what transport key to use.

NB-IoT Flows for NIDD

In our last post we covered the basics of NB-IoT Non-IP Data Deliver (NIDD), and if that acronym soup wasn’t enough for you, we’re going to take a deep dive into the flows for attaching, sending, receiving and closing a NIDD session.

The attach for NIDD is very similar to the standard attach for wideband LTE, except the MME establishes a connection on the T6a Diameter interface toward the SCEF, to indicate the sub is online and available.

The NIDD Attach

The SCEF is now able to send/receive NIDD traffic from the subscriber on the T6a interface, but in reality developers don’t / won’t interact with Diameter, so the SCEF exposes the T8 API that developers can interact with to access an abstraction layer to interact with the SCEF, and then through onto the UE.

If you’re wondering what the status of Open Source SCEF implementations are, then you may have already guessed we’re working on one! PyHSS should have support for NB-IoT SCEF features in the future.

NB-IoT provides support for Non-IP Data Delivery (NIDD) over 3GPP Networks, but to handle this, some new network elements are introduced, in a home network scenario that’s the SCEF and the SCF/AS.

On the 3GPP side the SCEF it communicates to the MME via the T6a Interface, which is based upon Diameter.

On the side towards our IoT Service Consumers (in the standards referred to as “SCS/AS” or “Service Capabilities Server Application Servers” (catchy names as always), via the RESTful HTTP based T8 interface.

I’ve written about Non-IP Data support in 5G for transporting Ethernet, but there’s another non-IP use case in 3GPP networks – This time for NB-IoT services.

Procedures

S1 Attach

The start of the S1 Attach procedure is very similar to a regular S1 attach.

The initial S1 PDU Connectivity Request indicates in the ESM Message Container that the PDN Type is Non IP.

S1 PDU Connectivity Request from attach procedure

Other than that, the initial attach procedure looks very similar to the regular S1 attach procedure.

On the S6a interface the Update Location Request from the MME to the HSS indicates that this is an EUTRAN-NB-IoT Radio Access Type.

And the Update Location Answer APN Configuration contains some additional AVPs on the APN to indicate that the APN supports Non-IP-PDN-Type and that the SCEF is used for Data Delivery.

The SCEF-ID (Diameter Host) and SCEF-Realm (Diameter realm) to serve this user is also specified in the APN Configuration in the Update Location Answer.

This is how our MME determines where to send the T6a traffic.

With this, the MME sends a Connection Management Request (CMR) towards the SCEF specified in the SCEF-ID returned by the HSS.

The Connection Management Request / Response

The MME now sends a Diameter T6a Connection Management Request to the SCEF in the Update Location Answer,

In it we have a Session-Id, which continues for the life of our NIDD session, the service-selection which contains our APN (In our case “non-ip”) and the User-Identifier AVP which contains the MSISDN and/or IMSI of the subscriber.

To accept this, the SCEF sends back a Connection-Management-Answer to confirm we’re all good to go:

At this point our SCEF now knows about the subscriber who’s just attached to our network, and correlates it with the APN and the session-ID.

On the S1 side the connection is confirmed and we’re ready to roll.

Mobile Originated Data Request / Response

When the UE wants to send NIDD it’s carried in NAS messaging, so we see an Uplink NAS transport from the UE and inside the NAS payload itself is our HEX data.

Our MME grabs this out and sends it in the form of of a Mobile-Originated-Data-Request (MODR) to the SCEF, along with the same Session-ID that was setup earlier:

At this stage our Non-IP Data is exposed over the T8 RESTful API, which we won’t cover in this post.

Getting started with PyHSS

PyHSS is our open source Home Subscriber Server, it’s written in Python, has a variety of different backends, and is highly perforate (We benchmark to 10K transactions per second) and infinitely scaleable.

In this post I’ll cover the basics of setting up PyHSS in your enviroment and getting some Diameter peers connected.

For starters, we’ll need a database (We’ll use MySQL for this demo) and an account on that database for a MySQL user.

So let’s get that rolling (I’m using Ubuntu 24.04):

sudo apt update
sudo apt install mysql-server

Next we’ll create the MySQL user for PyHSS to use:

CREATE USER 'pyhss_user'@'%' IDENTIFIED BY 'pyhss_password';
GRANT ALL PRIVILEGES ON *.* TO 'pyhss_user'@'%' WITH GRANT OPTION;
FLUSH PRIVILEGES;

We’ll also need Redis as well (PyHSS uses Redis for inter-service communications and for caching), so go ahead an install that for your distro:

sudo apt install redis-server

So that’s our prerequisites sorted, let’s clone the PyHSS repo:

git clone https://github.com/nickvsnetworking/pyhss /etc/pyhss

And install the requirements with pip from the PyHSS repo:

pip3 install -r requirements.txt

Next we’ll need to configure PyHSS, for that we update the config file (config.yaml) with the settings we want to use.

We’ll start by setting the bind_ip to a list of IPs you want to listen on, and your transport – We can use either TCP or SCTP.

For Diameter, we will set OriginHost and OriginRealm to match the Diameter hostname you want to use for this peer, and the Realm of your Diameter network.

Lastly we’ll need to set the database parameters, updating the database: section to populate your credentials, setting your username and password and the database to match your SQL installation we setup at the start.

With that done, we can start PyHSS, which we do using systemctl.

Because there’s multiple microservices that make up PyHSS, there’s multiple systemctl files use to run PyHSS as a service, they’re all in the /systemd folder.

We’ll copy them all to our systemd folder.

cp /etc/pyhss/systemd/ /lib/systemd/system/
systemctl daemon-reload
systemctl start pyhss

And with that we’ve got PyHSS running and ready for a Diameter peer to connect.

Now you should be able to bring our Diameter peers up.

If you’re using something like Kamailio, with C-Diameter Peer, you can read about the config for that here, or FreeDiameter you can read about here.

In the next post, we’ll cover subscriber provisioning via the API.

The power of the PyHSS EIR

The Equipment Identity Register (EIR) is a pretty handy function in 3GPP networks.

Via the Diameter based S13 interface, the MME, is able to query the EIR to ask if a given IMEI & IMSI combination should be allowed to attach.

This allows stolen / grey market / unauthorized devices (IMEIs) to be rejected from the network, the EIR can have a list of “bad” IMEIs that if seen will reject the request.

It also allows us to lock a SIM (IMSI) to a given device (IMEI) or type of device – We can use this for say a Fixed Wireless service, to lock the SIMs (IMSIs) to a range of modems (IMEI Prefixes).

Lastly it gives us insight and analytics into the devices used on the network, by mapping the IMEI to a device, we can say that IMEI 1234567890 is an Apple iPhone 12 Pro Max, or a Nokia Fastmile 5G-24W-A.

PyHSS supports all these capabilities, so let’s have a look at how we’d manage / access them.

Setting up EIR Rules

These rules are set via the RESTful API in PyHSS.

The Equipment Identity Register built into PyHSS supports matching in one of two modes, set by regex_mode.

In Exact Mode (regex_mode: 0) matches are based on an exact matching IMEI, and matching the IMSI if set (If IMSI is set to nothing (”), then only the IMEI is evaluated).

Exact Mode is suited for IMEI/IMSI locking, to ensure a SIM is locked to a particular device, or to blacklist stolen devices.

Regex Mode (regex_mode: 1) matches based on Regex, this is suited for whitelisting IMEI prefixes for say, specific validated vendors.

The match_response_code maps to the Equipment-Status AVP output, so specified values are:

  • 0 : ‘Whitelist’
  • 1: ‘Blacklist’
  • 2: ‘Greylist’

Some end to end examples of this provisioned into the API:

IMSI / IMEI Binding

{
      'imei': '1234', 
      'imsi': '567',
      'regex_mode': 0, 
      'match_response_code': 0
}

If IMSI is equal to 567 and is in use in IMEI 1234, then the response code returned is 0 (Whitelist).

IMEI Matching (Blacklist lost / stolen devices)

{
      'imei': '99881232',
      'imsi': '', 
      'regex_mode': 0, 
      'match_response_code': 1
}

If the IMEI is equal to 99881232 used with any IMSI, then the response code returned is 1 (Blacklist). This would be used for devices reported stolen.

IMEI Prefix Match (Blacklist / Whitelist all devices of type)

{
      'imei': '^666.*',
      'imsi': '', 
      'regex_mode': 1, 
      'match_response_code': 1
}

If the IMEI starts with 666, then the response code returned is 1 (Blacklist).

IMEI & IMSI Regex Match

{
      'imei': '^777.*',
      'imsi': '^1234123412341234$', 
      'regex_mode': 1, 
      'match_response_code': 2
}

If the IMEI starts with 777 and the IMSI is 1234123412341234 then return 2 (Greylist).

No Match Behaviour

If there is no match from the backend, then the config parameter no_match_response dictates the response code returned (Blacklist/Whitelist/Greylist).

Mapping Type Allocation Codes (TACs) to IMEIs

There are several data feeds of the Type Allocation Codes (TACs) which map a given IMEI prefix to a model number.

TAC database extract

Unfortunately, this data is not freely available, so we can’t bundle it with PyHSS, but if you have the IMEI Database, you can load it into PyHSS using Redis, to allow us to report on this data.

In your config.yaml you’ll just need to set the tac_database parameter, which will read the data on startup.

PyHSS YAML Config extract

Triggering on SIM Swap

If we keep track of the current IMSI/IMEI combination used for each SIM/Device, we can get notified every time it changes.

You might want to use this to trigger OTA provisioning or clear old data in your IMS.

For that we can use the sim_swap_notify_webhook in the config to send a HTTP POST to a given endpoint to inform it that a SIM is now in a different device.

We also have to have imsi_imei_logging set to true in the Config in order to log the history.

Reporting on IMEIs

We can also log/capture historical data about IMSI/IMEI combinations.

We use this from a customer support perspective to be able to see if a customer has recently changed phones, so if they call support, our staff can ask the customer about it to help troubleshoot.

“I can see you were connected previously on a Samsung Galaxy S22, but now you’re using a Nokia 3310, did the issues happen before you moved phones?”

This is super handy.

We can get a general log of IMSI vs IMEI like this:

Feed of IMSI vs IMEI along with a timestamp and the response that was sent back

But what’s more useful is searching for a IMSI or an IMEI and then getting back a full list of devices / SIMs that have been used.

Searching for an IMSI I can see it’s only ever been used in this Samsung Galaxy

Lastly via Grafana we export all this data, which allows us to visualize this data and build dashboards showing the devices on the network.

Visualizing EIR Data in Grafana

PyHSS includes a Promethues exporter, when it comes to prom_eir_devices_total it lists each seen Type Allocation Code / UE in the network, along with the number we’ve seen of each.

Raw it looks like this:

But visualized in Grafana we can get a dashboard to give us a breakdown per vendor:

The meaning of 3GPP-Charging-Characteristics

How does one encode / interpret the value of this AVP / IE was the question I set out to answer.

TS 29.274 says:

For the encoding of this information element see 3GPP TS 32.298

TS 32.298 says:

The functional requirements for the Charging Characteristics as well as the profile and behaviour bits are further defined in normative Annex A of TS 32.251

TS 32.251 Annex A says:

The Charging Characteristics parameter consists of a string of 16 bits designated as Behaviours (B), freely defined by Operators, as shown in TS 32.298 [51]. Each bit corresponds to a specific charging behaviour which is defined on a per operator basis, configured within the PCN and pointed when bit is set to “1” value.

After a few circular references I found this is imported from 32.298.

Finally we find some solid answers hidden away in TS 132 215, under the Charging Characteristics Profile index.

Charging Characteristics consists of a string of 16 bits designated as Profile (P) and Behaviour (B), shown in Figure 4.
The first four bits (P) shall be used to select different charging trigger profiles, where each profile consists of the
following trigger sets:

  • S-CDR: activate/deactivate CDRs, time limit, volume limit, maximum number of charging conditions, tariff
    times;
  • G-CDR: same as SGSN, plus maximum number of SGSN changes;
  • M-CDR: activate/deactivate CDRs, time limit, and maximum number of mobility changes;
  • SMS-MO-CDR: activate/deactivate CDRs;
  • SMS-MT-CDR: active/deactivate CDRs.

The Charging Characteristics field allows the operator to apply different kind of charging methods in the CDRs.
A subscriber may have Charging Characteristics assigned to his subscription. These characteristics can be supplied by the HLR to the SGSN as part of the subscription information, and, upon activation of a PDP context, the SGSN forwards the charging characteristics to the GGSN on the Gn / Gp reference point according to the rules specified in Annex A of TS 32.251 [11].

This information can be used by the GSNs to activate CDR generation and control the
closure of the CDR or the traffic volume containers (see clause 5.1.2.2.23) and is included in CDRs transmitted to nodes handling the CDRs via the Ga reference point. It can also be used in nodes handling the CDRs (e.g., the CGF or the billing system) to influence the CDR processing priority and routing.

These functions are accomplished by specifying the charging characteristics as sets of charging profiles and the expected behaviour associated with each profile.

The interpretations of the profiles and their associated behaviours can be different for each PLMN operator and are not subject to standardisation. In the present document only the charging characteristic formats and selection modes are specified.

The functional requirements for the Charging Characteristics as well as the profile and behaviour bits are further defined in normative Annex A of TS 32.251 [11], including the definitions of the trigger profiles associated with each CDR type.

The format of charging characteristics field is depicted in Figure 4. Px (x =0..3) refers to the Charging Characteristics Profile index. Bits classified with a “B” may be used by the operator for non-standardised behaviour (see Annex A of TS 32.251 [11]).

Right, well hopefully next time someone goes looking for this info you’ll find it a bit more easily than I did!

Best Practices for SGW & PGW Deployment Architectures for Roaming

The S8 Home Routing approach for LTE Roaming works really well, as more and more operators are switching off their legacy circuit switched 2G/3G networks and shifting to LTE & VoLTE for roaming, we’re seeing more an more S8-HR deployments.

When LTE was being standardised in 2008, Local Breakout (LBO) and S8 Home Routing were both considered options for how roaming may look. Fast forward to today, and S8 Home routing is the only way roaming is done for modern deployments.

In light of this, there are some “best practices” in an “all S8 Home Routed” world, we’ve developed, that I thought I’d share.

The Basics

When roaming, the SGW in the Visited Network, sends user traffic back to the PGW in the Home Network.

This means Online/Offline charging, IMS, PCRF, etc, is all done in the Home PLMN. As long as data packets can get from the SGW in the Visited PLMN to the PGW in the Home PLMN, and authentication flows from the Visited MME to the HSS in the Home PLMN, you’re golden.

The Constraints

Of course real networks don’t look as simple as this, in reality a roaming scenario for a visited network has a lot more nodes, which need to be

Building Distributed Packet Core & IMS

Virtualization (VNF / CNF) has led operators away from “big iron” hardware for Packet Core & IMS nodes, towards software based solutions, which in turn offer a lot more flexibility.

Best practice for design of User Plane is to keep the the latency down, by bringing the user plane closer to the user (the idea of “Edge” UPFs in 5GC is a great example of this), and the move away from “big iron” in central locations for SGW and PGW nodes has been the trend for the past decade.

So to achieve these goals in the networks we build, we geographically distribute the core network.

This means we’ve got quite a few S-GW, P-GW, MME & HSS instances across the network.
There’s some real advantages to this approach:

From a redundancy perspective this allows us to “spread the load” and build far more resilient networks. A network with 20 smaller HSS instances spread around the country, is far more resilient than 2 massive ones, regardless of how many power feeds or redundant disks it may have.

This allows us to be more resource efficient. MNOs have always provisioned excess capacity to cater for the loss of a node. If we have 2 MMEs serving a country, then each node has to have at least 50% capacity free, so if one MME were to fail, the other MME could handle the additional load it from it’s dead friend. This is costly for resources. Having 20 MMEs means each MME has to have 5% capacity free, to handle the loss of one MME in the pool.

It also forces our infrastructure teams to manage infrastructure “as cattle” rather than pets. These boxes don’t get names or lovingly crafted, they’re automatically spun up and destroyed without thinking about it.

For security, we only use internal IP addresses for the nodes in our packet core, this provides another layer of protection for the “crown jewels” of our network, so no one messing with BGP filtering can accidentally open the flood gates to our core, as one US operator learned leaving a GGSN open to the world leading to the private information for 100 million customers being leaked.

What this all adds to, is of course, the end user experience.
For the end subscriber / customer, they get a better experience thanks to the reduced latency the connection provides, better uptime and faster call setup / SMS delivery, and less cost to deliver services.

I love this approach and could prothletise about it all day, but in a roaming context this presents some challenges.

The distributed networks we build are in a constant state of flux, new capacity is being provisioned in some areas, nodes things decommissioned in others, and our our core nodes are only reachable on internal IPs, so wouldn’t be reachable by roaming networks.

Our Distributed-Core Roaming Solution

To resolve this we’ve taken a novel approach, we’ve deployed a pair of S-GWs we call the “Roaming SGWs”, and a pair of P-GWs we call the “Roaming PGWs”, these do have public IPs, and are dedicated for use only by roaming traffic.

We really like this approach for a few reasons:

It allows us to be really flexible do what we want inside the network, without impacting roaming customers or operators who use our network for roaming. All the benefits I described from the distributed architectures can still be realised.

From a security standpoint, only these SGW/PGW pairs have public IPs, all the others are on internal IPs. This good for security – Our core network is the ‘crown jewels’ of the network and we only expose an edge to other providers. Even though IPX networks are supposed to be secure, one of the largest IPX providers had their systems breached for 5 years before it was detected, so being almost as distrustful of IPX traffic as Internet traffic is a good thing.
This allows us to put these PGWs / SGWs at the “edge” of our network, and keep all our MMEs, as well as our on-net PGW and SGWs, on internal IPs, safe and secure inside our network.

For charging on the SGWs, we only need to worry about collecting CDRs from one set of SGWs (to go into the TAP files we use to bill the other operators), rather than running around hoovering up SGW CDRs from large numbers of Serving Gateways, which may get blown away and replaced without warning.

Of course, there is a latency angle to this, for international roaming, the traffic has to cross the sea / international borders to get to us. By putting it at the edge we’re seeing increased MOS on our calls, as the traffic is as close to the edge of the network as can be.

Caveat: Increased S11 Latency on Core Network sites over Satellite

This is probably not relevant to most operators, but some of our core network sites are fed only by satellite, and the move to this architecture shifted something: Rather than having latency on the S8 interface from the SGW to the PGW due to the satellite hop, we’ve got latency between the MME and the SGW due to the satellite hop.

It just shifts where in the chain the latency lies, but it did lead to us having to boost some timers in the MME and out of sequence deliver detection, on what had always been an internal interface previously.

Evolution to 5G Standalone Roaming

This approach aligns to the Home Routed options for 5G-SA roaming; UPF chaining means that the roaming traffic can still be routed, as seems to be the way the industry is going.

SA roaming is in its infancy, without widely deployed SA networks, we’re not going to see common roaming using SA for a good long while, but I’ll be curious to see if this approach becomes the de facto standard going forward.

Where to from here?

We’re pretty happy with this approach in the networks we’ve been building.

So far it’s made IREG testing easier as we’ve got two fixed points the IPX needs to hit (The DRAs and the SGWs) rather than a wide range of networks.

Operators with a vast number of APNs they need to drop into different VRFs may have to do some traffic engineering here – Our operations are generally pretty flat, but I can see where this may present some challenges for established operators shifting their traffic.

I’d be keen to hear if other operators are taking this approach and if they’ve run into any issues, or any issues others can see in this, feel free to drop a comment below.

SMS over Diameter for Roaming SMS

I know what you’re thinking, again with the SMS transport talk Nick? Ha! As if we’re done talking about SMS. Recently we did something kinda cool – The world’s first SMS sent over NB-IoT (Satellite).

But to do this, we weren’t using IMS, it’s too heavy (I’ve written about NB-IoT’s NIDD functions and the past).

SGs-AP which is used for CSFB & SMS doesn’t span network borders (you can’t roam with SGs-AP), and with SMSoIP out of the question, that gave us the option of MAP or Diameter, so we picked Diameter.

This introduces the S6c and SGd Diameter interfaces, in the diagrams below Orange is the Home Network (HPMN) and the Green is the Visited Network (VPMN).

The S6c interface is used between the SMSc and the HSS, in order to retrieve the routing information. This like the SRI-for-SM in MAP.

The SGd interface is used between the MME serving the UE and the SMSc, and is used for actual delivery of the MO/MT messages.

I haven’t shown the Diameter Routing Agents in these diagrams, but in reality there would be a DRA on the VPLMN and a DRA on the HPMN, and probably a DRA in the IPX between them too.

The Attach

The attach looks like a regular roaming attach, the MME in the Visited PMN sends an Update Location Request to the HSS, so the HSS knows the MME that is serving the subscriber.

S6a Update Location Request to indicate the MME serving the Subscriber

The Mobile Terminated SMS Flow

Now we introduce the S6c interface and the SGd interfaces.

When the Home SMSc has a message to send to the subscriber (Mobile Terminated SMS) it runs a the Send-Routing-Info-for-SM-Request (SRR) dialog to the HSS.

The Send-Routing-Info-for-SM-Answer (SRA) back from the HSS contains the info on the MME Diameter Host name and Diameter Realm serving the subscriber.

S6t – Send-Routing-Info-for-SM request to get the MME serving the subscriber

With this info, we can now craft a Diameter Request that will get sent to the MME serving the subscriber, containing the SMS PDU to send to the UE.

SGd MT-Forward-Short-Message to deliver Mobile Terminated SMS to the serving MME

We make sure it’s sent to the correct MME by setting the Destination-Host and Destination-Realm in the Diameter request.

Here’s how the request looks from the SMSc towards our DRA:

As you can see the Destination Realm and Destination-Host is set, as is the User-Name set to the IMSI of the UE we want to send the message to.

And down the bottom you can see the SMS-TPDU, the same as it’s been all the way back since GSM days.

The Mobile Originated SMS Flow

The Mobile Originated flow is even simpler, because we don’t need to look up where to route it to.

The MME receives the MO SMS from the UE, and shoves it into a Diameter message with Application ID set to SGd and Destination-Realm set to the HPMN Realm.

When the message reaches the DRA in the HPMN it forwards the request to an SMSc and then the Home SMSc has the message ready to roll.

So that’s it, pretty straightforward to set up!

VoLTE / IMS – Analysis Challenge

It’s challenge time, this time we’re going to be looking at an IMS PCAP, and answering some questions to test your IMS analysis chops!

Here’s the packet capture:

Easy Questions

  • What QCI value is used for the IMS bearer?
  • What is the registration expiry?
  • What is the E-UTRAN Cell ID the Subscriber is served by?
  • What is the AMBR of the IMS APN?

Intermediate Questions

  • Is this the first or subsequent registration?
  • What is the Integrity-Key for the registration?
  • What is the FQDN of the S-CSCF?
  • What Nonce value is used and what does it do?
  • What P-CSCF Addresses are returned?
  • What time would the UE need to re-register by in order to stay active?
  • What is the AA-Request in #476 doing?
  • Who is the(opens in a new tab)(opens in a new tab)(opens in a new tab) OEM of the handset?
  • What is the MSISDN associated with this user?

Hard Questions

  • What port is used for the ESP data?
  • Which encryption algorithm and algorithm is used?
  • How many packets are sent over the ESP tunnel to the UE?
  • Where should SIP SUBSCRIBE requests get routed?
  • What’s the model of phone?

The answers for each question are on the next page, let me know in the comments how you went, and if there’s any tricky ones!

What’s the maximum speed for LTE and 5G?

Even before 5G was released, the arms race to claim the “fastest” speeds on LTE, NSA and SA networks has continued, with pretty much every operator claiming a “first” or “fastest”.

I myself have the fastest 5G network available* but I thought I’d look at how big the values are we can put in for speed, these are the Maximum Bitrate Values (like AMBR) we can set on an APN/DNN, or on a Charging Rule.

*Measurement is of the fastest 5G network in an eastward facing office, operated by a person named Nick, in a town in Australia. Other networks operated by people other than those named Nick in eastward facing office outside of Australia were not compared.

The answer for Release 8 LTE is 4294967294 bytes per second, aka 4295 Mbps 4.295 Gbps.

Not bad, but why this number?

The Max-Requested-Bandwidth-DL AVP tells the PGW the max throughput allowed in bits per second. It’s a Unsigned32 so max value is 4294967294, hence the value.

But come release 15 some bright spark thought we may in the not to distant future break this barrier, so how do we go above this?

The answer was to bolt on another AVP – the “Extended-Max-Requested-BW-DL” AVP ( 554 ) was introduced, you might think that means the max speed now becomes 2x 4.295 Gbps but that’s not quite right – The units was shifted.

This AVP isn’t measuring bits per second it’s measuring kilobits per second.

So the standard Max-Requested-Bandwidth-DL AVP gives us 4.3 Gbps, while the Extended-Max-Requested-Bandwidth gives us a 4,295 Gbps.

We add the Extended-Max-Requested-Bandwidth AVP (4295 Gbps) onto the Max-Requested Bandwidth AVP (4.3 Gbps) giving us a total of 4,4299.3 Gbps.

So the short answer:

Pre release 15: 4.3 Gbps

Post release 15: 4,4299.3 Gbps

Authenticating Fixed Line Subscribers into IMS

We recently added support in PyHSS for fixed line SIP subscribers to attach to the IMS.

Traditional telecom operators are finding their fixed line network to be a bit of a money pit, something they’re required to keep operating to meet regulatory obligations, but the switches are sitting idle 99% of the time. As such we’re seeing more and more operators move fixed line subs onto their IMS.

This new feature means we can use PyHSS to serve as the brains for a fixed network, as well as for mobile, but there’s one catch – How we authenticate subscribers changes.

Most banks of line cards in a legacy telecom switches, or IP Phones, don’t have SIM slots to allow us to authenticate, so instead we’re forced to fallback to what they do support.

Unfortunately for the most part, what is supported by these IP phones or telecom switches is SIP MD5 Digest Authentication.

The Nonce is generated by the HSS and put into the Multimedia-Authentication-Answer, along with the subscriber’s password and sent in the clear to the S-CSCF.

Subscriber with Password made up of all 1's MAA response from HSS for Digest-MD5 Auth

The HSS then generates the the Multimedia-Auth Answer, it generates a nonce (in the 3GPP-SIP-Authenticate / 609 AVP) and sends the Subscriber’s password in the 3GPP-SIP-Authorization (610) AVP in response back to the S-CSCF.

I would have thought a better option would be for the HSS to generate the Nonce and Digest, and then the S-CSCF to just send the Nonce to the Sub and compare the returned Digest from the Sub against the expected Digest from the HSS, but it would limit flexibility (realm adaptation, etc) I guess.

The UE/UA (I guess it’s a UA in this context as it’s not a mobile) then generates its own Digest from the Nonce and sends it back to the S-CSCF via the P-CSCF.

The S-CSCF compares the received Digest response against the one it generated, and if the two match, the sub is authenticated and allowed to attach onto the network.

SQN Sync in IMS Auth

So the issue was a head scratcher.

Everything was working on the IMS, then I go to bed, the next morning I fire up the test device and it just won’t authenticate to the IMS – The S-CSCF generated a 401 in response to the REGISTER, but the next REGISTER wouldn’t pass.

Wireshark just shows me this loop:

UE -> IMS: REGISTER
IMS -> UE: 401 Unauthorized (With Challenge)
UE -> IMS: REGISTER with response
IMS -> UE: 401 Unauthorized (With Challenge)
UE -> IMS: REGISTER with response
IMS -> UE: 401 Unauthorized (With Challenge)
UE -> IMS: REGISTER with response
IMS -> UE: 401 Unauthorized (With Challenge)

So what’s going on here?

IMS uses AKAv1-MD5 for Authentication, this is slightly different to the standard AKA auth used in cellular, but if you’re curious, we’ve covered by IMS Authentication and standard AKA based SIM Authentication in cellular networks before.

When we generate the vectors (for IMS auth and standard auth) one of the inputs to generate the vectors is the Sequence Number or SQN.

This SQN ticks over like an odometer for the number of times the SIM / HSS authentication process has been performed.

There is some leeway in the SQN – It may not always match between the SIM and the HSS and that’s to be expected.
When the MME sends an Authentication-Information-Request it can ask for multiple vectors so it’s got some in reserve for the next time the subscriber attaches, and that’s allowed.

Information stored on USIM / SIM Card for LTE / EUTRAN / EPC - K key, OP/OPc key and SQN Sequence Number

But there are limits to how far out our SQN can be, and for good reason – One of the key purposes for the SQN is to protect against replay attacks, where the same vector is replayed to the UE. So the SQN on the HSS can be ahead of the SIM (within reason), but it can’t be behind – Odometers don’t go backwards.

So the issue was with the SQN on the SIM being out of Sync with the SQN in the IMS, how do we know this is the case, and how do we fix this?

Well there is a resync mechanism so the SIM can securely tell the HSS what the current SQN it is using, so the HSS can update it’s SQN.

When verifying the AUTN, the client may detect that the sequence numbers between the client and the server have fallen out of sync.
In this case, the client produces a synchronization parameter AUTS, using the shared secret K and the client sequence number SQN.
The AUTS parameter is delivered to the network in the authentication response, and the authentication can be tried again based on authentication vectors generated with the synchronized sequence number.

RFC 3110: HTTP Digest Authentication using AKA

In our example we can tell the sub is out of sync as in our Multimedia Authentication Request we see the SIP-Authorization AVP, which contains the AUTS (client synchronization parameter) which the SIM generated and the UE sent back to the S-CSCF. Our HSS can use the AUTS value to determine the correct SQN.

SIP-Authorization AVP in the Multimedia Authentication Request means the SQN is out of Sync and this AVP contains the RAND and AUTN required to Resync

Note: The SIP-Authorization AVP actually contains both the RAND and the AUTN concatenated together, so in the above example the first 32 bytes are the AUTN value, and the last 32 bytes are the RAND value.

So the HSS gets the AUTS and from it is able to calculate the correct SQN to use.

Then the HSS just generates a new Multimedia Authentication Answer with a new vector using the correct SQN, sends it back to the IMS and presto, the UE can respond to the challenge normally.

This feature is now fully implemented in PyHSS for anyone wanting to have a play with it and see how it all works.

And that friends, is how we do SQN resync in IMS!

Getting to know the PCRF for traffic Policy, Rules & Rating

Misunderstood, under appreciated and more capable than people give it credit for, is our PCRF.

But what does it do?

Most folks describe the PCRF in hand wavy-terms – “it does policy and charging” is the answer you’ll get, but that doesn’t really tell you anything.

So let’s answer it in a way that hopefully makes some practical sense, starting with the acronym “PCRF” itself, it stands for Policy and Charging Rules Function, which is kind of two functions, one for policy and one for rules, so let’s take a look at both.

Policy

In cellular world, as in law, policy is the rules.

For us some examples of policy could be a “fair use policy” to limit customer usage to acceptable levels, but it can also be promotional packages, services like “free Spotify” packages, “Voice call priority” or “unmetered access to Nick’s Blog and maximum priority” packages, can be offered to customers.

All of these are examples of policy, and to make them work we need to target which subscribers and traffic we want to apply the policy to, and then apply the policy.

Charging Rules

Charging Rules are where the policy actually gets applied and the magic happens.

It’s where we take our policy and turn it into actionable stuff for the cellular world.

Let’s take an example of “unmetered access to Nick’s Blog and maximum priority” as something we want to offer in all our cellular plans, to provide access that doesn’t come out of your regular usage, as well as provide QCI 5 (Highest non dedicated QoS) to this traffic.

To achieve this we need to do 3 things:

  • Profile the traffic going to this website (so we capture this traffic and not regular other internet traffic)
  • Charge it differently – So it’s not coming from the subscriber’s regular balance
  • Up the QoS (QCI) on this traffic to ensure it’s high priority compared to the other traffic on the network

So how do we do that?

Profiling Traffic

So the first step we need to take in providing free access to this website is to filter out traffic to this website, from the traffic not going to this website.

Let’s imagine that this website is hosted on a single machine with the IP 1.2.3.4, and it serves traffic on TCP port 443. This is where IPFilterRules (aka TFTs or “Traffic Flow Templates”) and the Flow-Description AVP come into play. We’ve covered this in the past here, but let’s recap:

IPFilterRules are defined in the Diameter Base Protocol (IETF RFC 6733), where we can learn the basics of encoding them,

They take the format:

action dir proto from src to dst

The action is fairly simple, for all our Dedicated Bearer needs, and the Flow-Description AVP, the action is going to be permit. We’re not blocking here.

The direction (dir) in our case is either in or out, from the perspective of the UE.

Next up is the protocol number (proto), as defined by IANA, but chances are you’ll be using 17 (UDP) or 6 (TCP).

The from value is followed by an IP address with an optional subnet mask in CIDR format, for example from 10.45.0.0/16 would match everything in the 10.45.0.0/16 network.

Following from you can also specify the port you want the rule to apply to, or, a range of ports.

Like the from, the to is encoded in the same way, with either a single IP, or a subnet, and optional ports specified.

And that’s it!

So let’s create a rule that matches all traffic to our website hosted on 1.2.3.4 TCP port 443,

permit out 6 from 1.2.3.4 443 to any 1-65535
permit out 6 from any 1-65535 to 1.2.3.4 443

All this info gets put into the Flow-Information AVPs:

With the above, any traffic going to/from 1.23.4 on port 443, will match this rule (unless there’s another rule with a higher precedence value).

Charging Actions

So with our traffic profiled, the next question is what actions are we going to take, well there’s two, we’re going to provide unmetered access to the profiled traffic, and we’re going to use QCI 4 for the traffic (because you’ll need a guaranteed bit rate bearer to access!).

Charging-Group for Profiled Traffic

To allow for Zero Rating for traffic matching this rule, we’ll need to use a different Rating Group.

Let’s imagine our default rating group for data is 10000, then any normal traffic going to the OCS will use rating group 10000, and the OCS will apply the specific rates and policies based on that.

Rating Groups are defined in the OCS, and dictate what rates get applied to what Rating Groups.

For us, our default rating group will be charged at the normal rates, but we can define a rating group value of 4000, and set the OCS to provide unlimited traffic to any Credit-Control-Requests that come in with Rating Group 4000.

This is how operators provide services like “Unlimited Facebook” for example, a Charging Rule matches the traffic to Facebook based on TFTs, and then the Rating Group is set differently to the default rating group, and the OCS just allows all traffic on that rating group, regardless of how much is consumed.

Inside our Charging-Rule-Definition, we populate the Rating-Group AVP to define what Rating Group we’re going to use.

Setting QoS for Profiled Traffic

The QoS Description AVP defines which QoS parameters (QCI / ARP / Guaranteed & Maximum Bandwidth) should be applied to the traffic that matches the rules we just defined.

As mentioned at the start, we’ll use QCI 4 for this traffic, and allocate MBR/GBR values for this traffic.

Putting it Together – The Charging Rule

So with our TFTs defined to match the traffic, our Rating Group to charge the traffic and our QoS to apply to the traffic, we’re ready to put the whole thing together.

So here it is, our “Free NVN” rule:

I’ve attached a PCAP of the flow to this post.

In our next post we’ll talk about how the PGW handles the installation of this rule.

Kamailio Diameter Routing Agent Support

Recently I’ve been working on open source Diameter Routing Agent implementations (See my posts on FreeDiameter).

With the hurdles to getting a DRA working with open source software covered, the next step was to get all my Diameter traffic routed via the DRAs, however I soon rediscovered a Kamailio limitation regarding support for Diameter Routing Agents.

You see, when Kamailio’s C Diameter Peer module makes a decision as to where to route a request, it looks for the active Diameter peers, and finds a peer with the suitable Vendor and Application IDs in the supported Applications for the Application needed.

Unfortunately, a DRA typically only advertises support for one application – Relay.

This means if you have everything connected via a DRA, Kamailio’s CDP module doesn’t see the Application / Vendor ID for the Diameter application on the DRA, and doesn’t route the traffic to the DRA.

The fix for this was twofold, the first step was to add some logic into Kamailio to determine if the Relay application was advertised in the Capabilities Exchange Request / Answer of the Diameter Peer.

I added the logic to do this and exposed this so you can see if the peer supports Diameter relay when you run “cdp.list_peers”.

With that out of the way, next step was to update the routing logic to not just reject the candidate peer if the Application / Vendor ID for the required application was missing, but to evaluate if the peer supports Diameter Relay, and if it does, keep it in the game.

I added this functionality, and now I’m able to use CDP Peers in Kamailio to allow my P-CSCF, S-CSCF and I-CSCF to route their traffic via a Diameter Routing Agent.

I’ve got a branch with the changes here and will submit a PR to get it hopefully merged into mainline soon.

Diameter Routing Agents – Part 5 – AVP Transformations with FreeDiameter and Python in rt_pyform

In our last post we talked about why we’d want to perform Diameter AVP translations / rewriting on our Diameter Routing Agent.

Now let’s look at how we can actually achieve this using rt_pyform extension for FreeDiameter and some simple Python code.

Before we build we’ll need to make sure we have the python3-devel package (I’m using python3-devel-3.10) installed.

Then we’ll build FreeDiameter with the rt_pyform, this branch contains the rt_pyform extension in it already, or you can clone the extension only from this repo.

Now once FreeDiameter is installed we can load the extension in our freeDiameter.conf file:

LoadExtension = "rt_pyform.fdx" : "<Your config filename>.conf";

Next we’ll need to define our rt_pyform config, this is a super simple 3 line config file that specifies the path of what we’re doing:

DirectoryPath = "."        # Directory to search
ModuleName = "script"      # Name of python file. Note there is no .py extension
FunctionName = "transform" # Python function to call

The DirectoryPath directive specifies where we should search for the Python code, and ModuleName is the name of the Python script, lastly we have FunctionName which is the name of the Python function that does the rewriting.

Now let’s write our Python function for the transformation.

The Python function much have the correct number of parameters, must return a string, and must use the name specified in the config.

The following is an example of a function that prints out all the values it receives:

def transform(appId, flags, cmdCode, HBH_ID, E2E_ID, AVP_Code, vendorID, value):
    print('[PYTHON]')
    print(f'|-> appId: {appId}')
    print(f'|-> flags: {hex(flags)}')
    print(f'|-> cmdCode: {cmdCode}')
    print(f'|-> HBH_ID: {hex(HBH_ID)}')
    print(f'|-> E2E_ID: {hex(E2E_ID)}')
    print(f'|-> AVP_Code: {AVP_Code}')
    print(f'|-> vendorID: {vendorID}')
    print(f'|-> value: {value}')
    
    return value

Note the order of the arguments and that return is of the same type as the AVP value (string).

We can expand upon this and add conditionals, let’s take a look at some more complex examples:

def transform(appId, flags, cmdCode, HBH_ID, E2E_ID, AVP_Code, vendorID, value):
    print('[PYTHON]')
    print(f'|-> appId: {appId}')
    print(f'|-> flags: {hex(flags)}')
    print(f'|-> cmdCode: {cmdCode}')
    print(f'|-> HBH_ID: {hex(HBH_ID)}')
    print(f'|-> E2E_ID: {hex(E2E_ID)}')
    print(f'|-> AVP_Code: {AVP_Code}')
    print(f'|-> vendorID: {vendorID}')
    print(f'|-> value: {value}')
    #IMSI Translation - if App ID = 16777251 and the AVP being evaluated is the Username
    if (int(appId) == 16777251) and int(AVP_Code) == 1:
        print("This is IMSI '" + str(value) + "' - Evaluating transformation")
        print("Original value: " + str(value))
        value = str(value[::-1]).zfill(15)

The above look at if the App ID is S6a, and the AVP being checked is AVP Code 1 (Username / IMSI ) and if so, reverses the username, so IMSI 1234567 becomes 7654321, the zfill is just to pad with leading 0s if required.

Now let’s do another one for a Realm Rewrite:

def transform(appId, flags, cmdCode, HBH_ID, E2E_ID, AVP_Code, vendorID, value):

    #Print Debug Info
    print('[PYTHON]')
    print(f'|-> appId: {appId}')
    print(f'|-> flags: {hex(flags)}')
    print(f'|-> cmdCode: {cmdCode}')
    print(f'|-> HBH_ID: {hex(HBH_ID)}')
    print(f'|-> E2E_ID: {hex(E2E_ID)}')
    print(f'|-> AVP_Code: {AVP_Code}')
    print(f'|-> vendorID: {vendorID}')
    print(f'|-> value: {value}')
    #Realm Translation
    if int(AVP_Code) == 283:
        print("This is Destination Realm '" + str(value) + "' - Evaluating transformation")
    if value == "epc.mnc001.mcc001.3gppnetwork.org":
        new_realm = "epc.mnc999.mcc999.3gppnetwork.org"
        print("translating from " + str(value) + " to " + str(new_realm))
        value = new_realm
    else:
        #If the Realm doesn't match the above conditions, then don't change anything
        print("No modification made to Realm as conditions not met")
    print("Updated Value: " + str(value))

In the above block if the Realm is set to epc.mnc001.mcc001.3gppnetwork.org it is rewritten to epc.mnc999.mcc999.3gppnetwork.org, hopefully you can get a handle on the sorts of transformations we can do with this – We can translate any string type AVPs, which allows for hostname, realm, IMSI, Sh-User-Data, Location-Info, etc, etc, to be rewritten.

NB-IoT NIDD Basics

NB-IoT introduces support for NIDD – Non-IP Data Delivery (NIDD) which is one of the cool features of NB-IoT that’s gaining more widespread adoption.

Let’s take a deep dive into NIDD.

The case against IP for IoT

In the over 40 years since IP was standardized, we’ve shoehorned many things onto IP, but IP was never designed or optimized for low power, low throughput applications.

For the battery life of an IoT device to be measured in years, it has to be very selective about what power hungry operations it does. Transmitting data over the air is one of the most power-intensive operations an IoT device can perform, so we need to do everything we can to limit how much data is sent, and how frequently.

Use Case – NB-IoT Tap

Let’s imagine we’re launching an IoT tap that transmits information about water used, as part of our revolutionary new “Water as a Service” model (WaaS) which removes the capex for residents building their own water treatment plant in their homes, and instead allows dynamic scaling of waterloads as they move to our new opex model.

If I turn on the tap and use 12L of water, when I turn off the tap, our IoT tap encodes the usage onto a single byte and sends the usage information to our rain-cloud service provider.

So we’re not constantly changing the batteries in our taps, we need to send this one byte of data as efficiently as possible, so as to maximize the battery life.

If we were to transport our data on TCP, well we’d need a 3 way handshake and several messages just to transmit the data we want to send.

Let’s see how our one byte of data would look if we transported it on TCP.

That sliver of blue in the diagram is our usage component, the rest is overhead used to get it there. Seems wasteful huh?

Sure, TCP isn’t great for this you say, you should use UDP! But even if we moved away from TCP to UDP, we’ve still got the IPv4 header and the UDP header wasting 28 bytes.

For efficiency’s sake (To keep our batteries lasting as long as possible) we want to send as few messages as possible, and where we do have to send messages, keep them very short, so IP is not a great fit here.

Enter NIDD – Non-IP Data Delivery.

Through NIDD we can just send the single hex byte, only be charged for the single hex byte, and only stay transmitting long enough to send this single byte of hex (Plus the NBIoT overheads / headers).

Compared to UDP transport, NIDD provides us a reduction of 28 bytes of overhead for each message, or a 96% reduction in message size, which translates to real power savings for our IoT device.

In summary – the more sending your device has to do, the more battery it consumes.
So in a scenario where you’re trying to maximize power efficiency to keep your batter powered device running as long as possible, needing to transmit 28 bytes of wasted data to transport 1 byte of usable data, is a real waste.

Delivering the Payload

NIDD traffic is transported as raw hex data end to end, this means for our 1 byte of water usage data, the device would just send the hex value to be transferred and it’d pop out the other end.

To support this we introduce a new network element called the SCEFService Capability Exposure Function.

From a developer’s perspective, the SCEF is the gateway to our IoT devices. Through the RESTful API on the SCEF (T8 API), we can send and receive raw hex data to any of our IoT devices.

When one of our Water-as-a-Service Taps sends usage data as a hex byte, it’s the software talking on the T8 API to the SCEF that receives this data.

Data of course needs to be addressed, so we know where it’s coming from / going to, and T8 handles this, as well as message reliability, etc, etc.

This is a telco blog, so we should probably cover the MME connection, the MME talks via Diameter to the SCEF. In our next post we’ll go into these signaling flows in more detail.

If you’re wondering what the status of Open Source SCEF implementations are, then you may have already guessed I’m working on one!

Hopefully by now you’ve got a bit of an idea of how NIDD works in NB-IoT, and in our next posts we’ll dig deeper into the flows and look at some PCAPs together.

Diameter Routing Agents – Part 5 – AVP Transformations

Having a central pair of Diameter routing agents allows us to drastically simplify our network, but what if we want to perform some translations on AVPs?

For starters, what is an AVP transformation? Well it’s simply rewriting the value of an AVP as the Diameter Request/Response passes through the DRA. A request may come into the DRA with IMSI xxxxxx and leave with IMSI yyyyyy if a translation is applied.

So why would we want to do this?

Well, what if we purchased another operator who used Realm X, and we use Realm Y, and we want to link the two networks, then we’d need to rewrite Realm Y to Realm X, and Realm X to Realm Y when they communicate, AVP transformations allow for this.

If we’re an MVNO with hosted IMSIs from an MNO, but want to keep just the one IMSI in our HSS/OCS, we can translate from the MNO hosted IMSI to our internal IMSI, using AVP transformations.

If our OCS supports only one rating group, and we want to rewrite all rating groups to that one value, AVP transformations cover this too.

There are lots of uses for this, and if you’ve worked with a bit of signaling before you’ll know that quite often these sorts of use-cases come up.

So how do we do this with freeDiameter?

To handle this I developed a module for passing each AVP to a Python function, which can then apply any transformation to a text based value, using every tool available to you in Python.

In the next post I’ll introduce rt_pyform and how we can use it with Python to translate Diameter AVPs.