Hello once again fellow geek. In this post I will be continuing my series of NSPs (Network Security Perimeters). Over the past few posts in this series I’ve explained the problem NSPs solve, the components that make up an NSP, demonstrated NSPs through a Key Vault use case and an AI workload use case, and even shown how they can used to troubleshoot the dreaded Private Endpoints and forward web proxy problem we all run into. After reading those posts you are probably wondering why you aren’t seeing them more talked about in the Azure world. Besides the fact it’s not called “Frontier Network Agentic Security AI Perimeter”, the reason NSPs haven’t been getting the love they should is due to a technical gap that is finally in the process of being lifted.
The only way to work around this limitation is to place the delivery destination (LAW, storage account, event hub) in the same NSP. While this sounds like a simple solution, a given resource can only belong to a single NSP. If you attempt to add a resource to an NSP when it’s already associated to another NSP it will fail as seen below.
Resources can only be associated to a single NSP
If you’ve ever done logging as scale in Azure, you already see the problem with this limitation. When logging at scale in Azure, it’s very common to send logs to a centralized Log Analytics Workspace, Event Hub, or Storage Account. There are a number of benefits to doing this beyond the scope of this post which you can read about in the CAF (Cloud Adoption Framework) documentation. These resource are typically managed by a security team or a platform team and live in subscriptions controlled by those teams.
If you’re like, your first instinct is to create an outbound rule to allow the access to the Log Analytics Workspace. Good instinct, but not possible because today NSPs only support outbound rules of type FQDN and there is no FQDN for platform diagnostic logs that Microsoft provide today. A service tag would be the best bet, but sadly it is not yet supported for NSP outbound rules.
Centralized logging problem with NSPs
Up until very recently, NSPs in enforcement mode have been pretty much a non-starter for enterprise customers due to this limitation. Notice I say “enforcement”. If you aren’t using NSPs in learning (or transition mode) you are losing out on insanely valuable egress visibility you can’t get using any other means as I describe in my troubleshooting post.
The PG (Product Group) for NSPs is one of those amazing product groups who listens to the customer, wants to see their product adopted, and works their butt off. Just a few weeks ago they introduced a new feature into public preview that begins to address this technical limitation
The Solution
The solution for this technical problem is perimeter links. In the ARM (Azure Resource Manager) API, these are referred to as links and are a child resource of the Network Security Perimeter. Perimeter links allow traffic to flow between NSPs either per profile or for all profiles. This means we can slap a perimeter link between the NSP containing our resources that need to deliver our logs and the NSP containing the resource we’re delivering the logs to!
Perimeter links can be across a single profile or all profiles within an NSP
In the image below I’ve created a perimeter link between an NSP containing a storage account the NSP containing the log analytics workspace the storage account diagnostic log setting has been configured to deliver logs to. This link enables the traffic to flow freely between the two NSPs.
Perimeter link example
Once the perimeter link is created, new inbound and outbound access rules are created in each profile allowing the two NSPs to communicate with each other.
In the example above, once the perimeter link is in place and rules have been automatically created and taken affect (takes about 10-15 seconds) the spice will flow! Alright, logs will flow but I’ve been re-reading Dune so leave me alone in my nerdy world. In the screenshot below you can see the logs being blocked initially and then being allowed after the perimeter and its automatically created rules take affect.
The spice will flow!
The good and gotchas of perimeter links
So first some of the good things about perimeter links:
You can now do cross perimeter communication.
In my testing, terraform state doesn’t get botched up when the perimeter link triggers the automatic creation of the access rule. A reapply after didn’t complain and didn’t overwrite them.
Perimeter links work across subscriptions. Note there is a (as there should be) to make that work.
The biggest pain point of them right now is the maximum amount of perimeter links per NSP is 10. Obviously, this is no where near the scale needed for the centralized logging use case. However, this is still preview and I’m confident the PG will increase that limit (hopefully a shit ton) prior to GA.
Well folks, let me leave you with a few recommendations:
If you’re not using NSPs as a detective control for data exfiltration you are missing out. You need to make this a priority, if only for the visibility into egress.
This is preview, so muck around with it, but don’t go rolling this to prod.
Hello once again folks! Today I’m going to add yet another post to my BYO AI Gateway feature of Microsoft Foundry series. In my first post I gave a background on the use case for this feature, in the second post I walked the concepts required to understand the feature, the resources involved in the setup, and the schema of those resource objects. In this post I’m going to walk through the architecture I setup to play with this feature, why I made the choices I did, and dig into some of the actual Terraform code I put together to set this whole thing up. Let’s dive in!
The foundational architecture
When I wanted to experiment with this feature I wanted to test it in an architecture that is typical to my customer base. For this I chose the classic tried and true hub and spoke architecture. I opted out of VWAN and went with a traditional virtual network model because I prefer the visibility and control to that model during experimentation. When the hub becomes a managed VWAN Hub, I get that fancy overlay which makes invisible some of the magic of what is happening underneath. This model enables me to do packet captures at every step and manage routing at a very granular level, which is a must when playing with cutting edge features.
For this setup I have a lab I built out in Terraform which gives me that hub and spoke architecture, centralized DNS resolution, logging, and access to multiple regions. The multiple regions piece of the puzzle is key because feature availability across Foundry features and APIM v2 SKUs are still in flux. The lab also uses three spoke virtual networks. This gives allows me to plop pieces in different spokes to see how things behave and track traffic patterns. It also gives me flexibility when I need to wait for purge operations like when purging a Microsoft Foundry resource configured with a standard agent setup and clearing the lock on the delegated subnet for the VNet injection model. If you’ve mucked around with this you know sometimes it can be 15 minutes and sometimes it can be 2 days.
I drop one of three spokes into one of the “hero” regions. This is a region that gets new features sooner than ours. For example, in this lab I drop it into East US 2 while the hub and other two spokes go in West US 3 (where I’m less likely to run into an quota or capacity issues). East US 2 gives me the option to deploy APIM v2 Standard SKU. In the next section I’ll explain why I’m going with v2 for this experimentation.
Foundational architecture
AI Gateway Architecture
For an AI Gateway I decided to use APIM. My buddy Piotr Karpala has a great repository of 3rd-party AI Gateway solutions if you want to test this with something outside of APIM. I’m going to plop this into the “hero” region spoke in East US 2 to so I can deploy a v2 Standard SKU. The reason I’m using a v2 SKU is it provides another networking model that the classic SKUs do not, and that is Private Endpoint and VNet integration. In this model I block public traffic to the APIM service, create a Private Endpoint to enable private inbound access, and setup VNet integration to a delegated subnet to keep outbound traffic from any of the APIM instances flowing through my virtual network so I can mediate it and optionally inspect it. While the Private Endpoint is only supported for the Gateway and not the Developer Portal, I don’t care in this instance because I don’t plan on using the Developer Portal on an APIM acting as an AI Gateway. You can also create a private endpoint for a APIM v2 service instance that uses VNet injection, but it requires the Premium SKU and I’m super cheap, so I opted out of that.
APIM v2 with Private Endpoint and VNet Integration
The reason I picked this networking model for APIM is it makes it easy for me to inject the service into a Microsoft Foundry account configured with a standard agent and the managed virtual network model. In a future post I’ll dive more into the managed virtual network model. For now, just be aware that is exists, it’s in preview, and it doesn’t have many of the limitations the Foundry Agent Service VNet injection model has. There are considerations no doubt, but my personal take is it’s the better of the two strategically.
On the APIM instance I configured two backend objects, one for each Foundry instance. The backends are organized into a pooled backend so I could load balance across the two Foundry instances to maximize my TPM (tokens per minute). I defined four APIs. Two APIs support the Azure OpenAI inferencing and authoring API, one supports the Azure OpenAI v1 API, and the last is a simple custom Hello World API I use to test connectivity. I use two APIs for the Azure OpenAI inferencing and authoring API because one is designed to support APIM as an AI Gateway uses some custom policy snippets and the other is very generic and is used to test model gateway connections from Foundry purely so I’m familiar with the basics of them.
APIM APIs
Foundry Architecture
The Foundry architecture is quite simple. I deployed a single instance of Foundry configured to support standard agents and using a VNet injection model. A subnet is delegated in a different spoke to support the agent vnet injection and supporting Private Endpoints are deployed to a separate subnet in that same virtual network.
The whole setup looks something like the below:
Lab setup
Setting up the AI Gateway
At this point you should have a good understanding of what I’m working with. Let’s talk button pushing. The first thing you’ll need to do is get your AI Gateway setup. To setup the APIM instance I using the Terraform AzureRM and AzApi providers. Like I mentioned above, it was setup as a v2 with the standard SKU public network access disabled, inbound access restricted to private endpoints and outbound access configured for VNet integration. You can find the whole of the code in my lab repository if you’re curious. For the purposes of the post, I’ll only be including the relevant snippets.
One critical thing to take note of is whatever networking model you choose for APIM for this integration, you need to use a certificate issued by a trusted public CA (certificate authority). This is required because at the date of this post, the agent service does not support certificates issued by private CAs. Reason being, you have no ability to inject that root and intermediate certs into the trusted store of the agent compute. For this lab I used the Terraform Acme and Cloudflare providers. It’s actually not bad at all to have a fresh cert provisioned directly as part of the pipeline for labbing and the like, and best part is it’s free for cheap people like myself. There is a sample of that code in the repo.
As I mentioned in my last post, the BYO AI Gateway integration with Foundry supports static or dynamic setup. In the static model you define the models directly in the connection metadata you want to be made available to the connection (see my last post for an example). In the dynamic model the models can be fetched by an API call to the management.azure.com API. This latter option requires additional operations be defined in the API such as what you see below.
## Create an operation to support getting a specific deployment by name when using the Foundry APIM connection
You then define a policy for that operation to configure it to call the correct endpoint via the ARM API like below. Notice I used the authentication-managed-identity policy snippet to use the APIM managed identity to call the Foundry resource to fetch deployment information. If you’re sharing the API across backends, make sure all backends have all the same models deployed. If not, you’ll need to incorporate some additional logic to hit the backend for each pool to ensure you don’t return models that don’t exist in a specific backend. This will require your APIM instance managed identity to have at least the Azure RBAC Reader role over the Foundry resources.
## Create an policy for the get deployment by name operation to route to the Foundry APIM connection
In my lab, I defined these two operations for both the classic (OpenAI Inferencing and Authoring API) and v1 API. This allowed me to mess around with both static and dynamic APIM and Model Gateway connections.
Once you get Foundry hooked into APIM using this integration (and I’ll cover the Foundry part in the next post), you get access to some pretty neat information in the headers. As of the date of this post, these will be some of the headers you’ll see. You’ll notice my x-forwarded-for path includes my endpoint’s IP address as well as the IP of the container running in the managed Microsoft-compute environment (notice that is using CGNAT IP space which clears up why CGNAT is unsupported to be used by the customer when using agent with VNet injection). The x-ms-foundry-project-id is the unique project GUID of the project the agent was created under (could be useful for throttling and logging). The x-ms-foundry-agent-id is the unique agent identifier of the specific revision of the agent (again useful for logging and throttling). The x-ms-client-request-id is actually the Foundry project managed identity, not the agent identity which is important to note. If you want to use Entra for the BYO AI Gateway APIM connection, you’re going to be limited to this or API key. There is a connection authentication option to use the agent’s actual Entra ID Agent Identity, but I’ve only used that for the MCP Server feature of Foundry, never for this so I’m not sure if it works or is supported.
Using the information above, I crafted the policy below. It’s nothing fancy, but shows an example of throttling based on the project id and logging the agent identifier via the token metrics policy to potentially make chargeback more granular. Either way, these additional headers give you more to play with.
## Create an API Management policy for the OpenAI v1 API
I was going to go crazy and incorporate the Foundry setup and testing into this post as well but decided against it. There is a point when the brain melts and if mine is already melting, yours may be as well. I’ll walk through those pieces in the next post. You have a few main takeaways. First, let’s review the high level setup of your AI Gateway.
Create your backends that point to the Microsoft Foundry endpoints.
Import the relevant API. If at all possible, go with the v1 API. It will support access to other models besides OpenAI models and additional features.
Add the GET and LIST operations and define the relevant policies if you’re planning on supporting dynamic models vs static. Dynamic seems to make more sense to me, but I haven’t seen enough orgs adopt this yet to form a good opinion.
Craft your custom policies. I highly recommend you regularly review the headers being passed. They could change and even better data may be added to them.
Next, let’s talk about key gotchas.
The certificate used on your AI Gateway MUST be issued from a well-known public CA in order for it to be trusted by the agent running in Foundry comptue. If it isn’t, this integration will fail and may not fail in a way that is obvious the TLS session failure between the agent compute and the AI Gateway is to blame.
If you’re using APIM, think about the Private Endpoint and VNet integration pattern if you’re capable of using v2. If it won’t work for you, or you’re still using the classic SKU, if you want to support managed VNet you’ll need to incorporate an Application Gateway in front of your AI Gateway likely. This means more operational overhead and costs.
While every Foundry Agent (v2) is given an Entra ID Agent Identity created from the Entra ID Agent Blueprint associated to the project, when using the ProjectManagedIdentity authentication type, you’ll see the project’s managed identity in the logs. If you’re able to test with the agent identity authentication type, let me know.
Really noodle on how you can use the project headers for throttling and possibly chargeback. It makes a ton of sense if you’re aligning your Foundry account and project model correctly.
Welcome back to my third post in my NSP (Network Security Perimeter) series. In this post I’m going to start covering some practical use cases for NSPs and demonstrating how they work. I was going to group these use cases in a single post, but it would have been insanely long (and I’m lazy). Instead, I’ll be covering one per post. These use cases are likely scenarios you’ve run into and do a good job demonstrating the actual functionality.
A Quick Review
In my first post I broke PaaS services into compute-based PaaS and service-based PaaS. NSPs are focused on solving problems for service-based PaaS. These problems include a lack of outbound network controls to mitigate data exfiltration, inconsistent offerings for inbound network controls across PaaS services, scalability with inbound IP whitelisting, difficulty configuring and managing these controls at scale, and inconsistent quality of logs across services for simple fields you’d expect in a log like calling inbound IP address.
Compute-based PaaS vs Service-based PaaS
My second post walked through the components that make up a Network Security Perimeter and their relationships to each other. I walked through each of the key components including the Network Security Perimeter, profiles, access policies, and resource associations. If you haven’t read that post, you need to read it before you tackle this one. My focus in this post will be where those resources are used and will assume you grasp their function and relationships.
Network Security Perimeter components and their relationships
With that refresher out of the way, let’s get to the good stuff.
Use Case 1: Securing Azure Key Vaults
Azure Key Vault is Microsoft’s native PaaS offering for secure key, secret, and certificate storage. Secrets sometimes need to be accessed by Microsoft SaaS (software-as-a-service) and compute-based PaaS that do not support virtual network injection or a managed virtual network concept, such as some use cases for PowerBI. Vaults are used by 3rd-party products outside of Azure or from another CSP (cloud service provider). There are also use cases where a customer may be new to Azure and doesn’t yet have the necessary hybrid connectivity and Private DNS configuration to support the usage of Private Endpoints. In these scenarios, Private Endpoints are not an option and the traffic needs to come in the public endpoint of the vault. Here is our use case for NSPs.
Services accessing Key Vault for secrets
Historically, folks would try to solve this with IP whitelisting on the Key Vault service firewall. As I covered in my first post, this is a localized configuration to the resource and can be mucked with by the resource owner unless permissions are properly scoped or an Azure Policy is used to enforce a specific configuration. This makes it difficult to put network control in the hands of security while leaving the rest of the configuration of the resource to the resource owner. Another issue that sometimes pops up with this pattern is hitting the maximum of 400 prefixes for the service firewall rules.
NSPs provide us with a few advantages here:
Network security can be controlled by the NSP and that NSP can be controlled by the security team while leaving the rest of the resource configuration to the resource owner.
You can allow more than 400 inbound IP rules (up to 500 in my testing). Sometimes a few extra IP prefixes is all you needed back with the service firewall.
In this type of use case, we could do something like the below. Here we have a single Network Security Perimeter for our two categories of Key Vaults for a product line. Category 1 Key Vaults need to be accessed by 3rd-party SaaS and applications that do not have the necessary network path to use Private Endpoints. Category 2 are Key Vaults used by internally facing application within Azure and those Key Vaults need to be restricted to a Private Endpoint.
Public Key Vault
For this scenario we can build something like in the image above where we have a single NSP with two profiles. One profile will be used by our “public” Key Vaults. This profile will be associated with an access rule that allows a set of trusted IP addresses from a 3rd-party SaaS solution. The other profile will have no associated access rules, thus blocking all access to the Key Vault over the public endpoint. Both resource associations will be set to enforced to ensure the the NSP rules override the local service firewall rules.
Let’s take a look at this in action.
For this scenario, I have an NSP design setup exactly as above. The access rule applied to my public vault has the IP address of my machine as seen below:
Profile access rule for publicly-facing Key Vault
At this point my vault isn’t associated with the NSP yet and it has been configured to allow all public network access. Attempts at accessing the vault from a random public IP shows successful as would be expected.
Successful retrieval of secret from untrusted IP address prior to NSP association
Next I associate the vault to the NSP and set it to enforced mode. By default it will be configured in Transition mode (see my second post for detail on this) which means it will log whether the traffic would be allowed or denied but it won’t block the traffic. Since I want the NSP to override the local service firewall, I’m going to set it to enforced.
When trying to pull the secret from the vault using a machine with the trusted public IP listed in the access rule associated to the profile, I’m capable of getting the secret.
Successful call from trusted IP listed in NSP profile access rule
If I attempt to access the secret from an untrusted IP, even with the service firewall on the vault configured to allow all public network access, I’m rejected with the message below.
Denied call from an untrusted IP due to NSP
Review of the logs (NSPAccessLogs table) shows that the successful call was due to the access rule I put in place and the denied call triggered DefaultDenyAll rule.
Now what about my private vault? Let’s take a look at that one next.
Private Key Vault
For this scenario I’m going to use the second profile in the NSP. This profile doesn’t have any associated access rules which effectively blocks all traffic to the public endpoint originating from outside the NSP. My goal is to make this vault accessible only from a private endpoint.
First, I associate the resource to the NSP profile and configure it in enforced mode.
Private Key Vault associated to profile in enforced mode
This is another vault where I’ve configured the service firewall to allow all public network access. Attempting to access the resource throws the message indicating the NSP is blocking access.
Denied call from a public IP when NSP denies all public access
I’ve created a Private Endpoint for this vault as well. As I covered earlier in this series, NSPs are focused on public access and do not limit Private Endpoint access, so that means it doesn’t log access from a Private Endpoint, right? Wrong! A neat feature of NSP wrapped resources is those the NSPs will allow the traffic and log it as seen below.
NSP log entry showing access through Private Endpoint
In the above log entry you’ll see the traffic is labeled as private indicating it’s traffic being allowed through the DefaultAllowAll rule and the TrafficType set to Private because it’s coming in through a Private Endpoint. Interestingly enough, you also get the operation that was being performed in the request. I could have sworn these logs used to include the specific Private Endpoint resource ID the traffic ingressed from, but perhaps I imagined that or it was removed when the service graduated to GA (generally available).
Summing it up
In this post I gave an overview of a simple use case that many folks may have today. You could easily sub out Key Vault for any of the other supported PaaS that has a similar public endpoint access model and the setup will be the same. Here are some key takeaways:
NSPs allow you to enforce public access network controls regardless how the resource owner configures the service firewall on the resource.
Profiles seem to support a maximum of 500 IP prefixes for inbound and 500 for outbound. This is more than the 400 available in the service firewall. This is based on my testing and no idea if it’s a soft or hard limit.
NSPs provide a standardized log format for network access. No more looking at 30 different log schemas across different resources, half of which don’t contain network information or someone drank too much tequila and decided to mask an octet of the IP. Additionally, they will log network access attempts through Private Endpoints.
In my next post I’ll cover a use where we have two resources in the same NSP that communicate with each other.
Today I will be continuing my series on NSPs (Network Security Perimeters). In the last post I outlined the problems NSPs were built to solve. I covered how users of Azure have historically controlled inbound and outbound traffic for PaaS (platform-as-a-service) in Azure and the gaps and challenges of those designs. In this post I’m going to dig into the components that make up an NSP, what their function is, how they’re related, and how they work together.
A Quick Review
Before I dive into the gory details of NSP primitives, I want to do a quick refresh on terminology I’ll be using in this post. As I covered in the last post, I divide PaaS services in Azure into what I call compute-based PaaS and service-based PaaS. Service-based PaaS is PaaS where you upload data but don’t control the code executed by the PaaS whereas with compute-based PaaS you control the code executed within the service. NSPs shine in the service-based PaaS realm and that will be my focus for this series.
Compute-based PaaS vs Service-based PaaS
Securing service-based PaaS with the traditional tooling of IP whitelisting, service whitelisting, resource whitelisting, resource-specific outbound controls (and they are very rare) presented the problems below:
Issues at scale (IP whitelisting).
Certain features were not available in all PaaS (resource-based whitelisting or product-specific outbound controls).
The configuration for inbound network control features lived as properties of the resource and could be configured differently by different teams resulting in inconsistent configurations.
Logging widely differed across products.
All the challenges above demanded a better more standardized solution, and that’s where NSPs come in.
Where NSPs fit in
Network Security Perimeter Components
I’m a huge fan of breaking down any technology into the base components that make it up. It makes it way easier to understand how the hell these things work together holistically to solve a problem. Let’s do that.
Network Security Perimeter Hierarchy
At the highest level is the Network Security Perimeter resource. This is what I refer to as a top-level resource, meaning a resource that exists directly under an Azure Resource Provider and is visible under a resource group. The Network Security Perimeter resource exists in the Microsoft.Network resource provider, is regional in nature (vs global), and serve as the outer container for the logic of the NSP.
The resource is very simple and the only properties of note are name, location, and tags.
Network Security Perimeter
Profiles
Underneath the Network Security Perimeter resource is the Profile resource. The easiest way to think about a profile is that it’s a collection of inbound and outbound network access rules that you plan to tie to a resource or resources. Each Network Security Perimeter resource can have 1 or more profiles. It’s recommended you have less than 200 profiles, however, I have trouble thinking of a use case for that many unless you’re in an older and more legacy subscription model where you’re packing everything into as few subscriptions as possible (not where you should be these days).
From mucking around with profiles, I can see the use for putting resources in the same NSP into different profiles. For example, I may wrap an NSP around a Storage Account and the Key Vault which holds the CMK (customer-managed key) used to encrypt the Storage Account. I’d likely want one profile for the storage account with a large set of inbound rules and another profile for the Key Vault with a profile with no inbound or outbound rules restricting the Key Vault to be accessed by the Storage Account. My CI/CD pipeline could reach the Key Vault via a Private Endpoint as NSPs DO NOT affect traffic ingressing through the resource’s Private Endpoint. Resources within the same NSP can communicate with each other as long as they’re associated with a managed identity (according to docs, still want to test and validate this myself).
Network Security Perimeter Profiles
Access Rules
Next up you have the Access Rule resource which exists underneath the Profile resource. This is where the the rubber hits the road. Access rules should be familiar to you old folks like myself as they are very similar to firewall rules (at least today). You have a direction (inbound or outbound) and some type of type of property to filter by. For example, as of the date of this post, inbound traffic can support filtering on subscriptions (very similar to the resource whitelisting in Azure Storage) and IP-based rules (similar to IP whitelisting of traditional service firewall). Outbound traffic can be filtered by FQDN (fully qualified domain name). You can have up to 200 rules per profile (this is a hard limit).
If you’re nosy like I am, you may have glanced at the API reference. Inside the API reference, there are additional items that may someday come to fruition such as email addresses and phone numbers (really curious as to the use cases for these) and service tags (DAMN handy but not yet usable as of the date of this post).
Network Security Perimeter Profile Access Rules
Resource Association
The Resource Association resource exists underneath the Network Security Perimeter. Resource associations connect a supported Azure resource to Network Security Perimeter’s profile and dictate an access mode. There are two documented access modes today which include learning (since renamed transition mode in documentation), and enforced. Transition mode (or learning mode in the APIs) is the default mode and is the mode you’ll start with to understand the inbound and outbound traffic of the resources associated with the NSP. Only after you understand those patterns should you switch to enforced mode. In enforced mode the access rules applied the relevant profile will take effect and all inbound and outbound traffic outside the NSP will be blocked unless explicitly allowed.
Audit mode is a third mode that is available via the API but isn’t mentioned in main public documentation. Your use case for audit mode as far as I can see is if you (say you’re information security) want to audit inbound and outbound traffic out of PaaS resources that are associated to a Network Security Perimeter you do not control.
To answer a few questions that I know immediately popped in my head:
Yes, you can associate resources to a network security perimeter that is in different a subscription.
No, you cannot associate a resource to multiple profiles in enforced mode in the same Network Security Group. Associations to other profiles must be configured in access mode.
No, you cannot associate a resource to multiple profiles in enforced mode in different Network Security Groups. Associations to other profiles must be configured in access mode.
Network Security Perimeter Resource Associations
Transition and Enforcement Mode
I want to dig a bit more into transition and enforcement mode and how they affect the resource-level service firewall controls.
In transition mode (which is the default mode) the NSP will evaluate the access rules of the profile the resource is associated with and will log whether the traffic would be allowed or denied (if diagnostic logging is enabled which you most definitely should enable and I’ll cover quickly below but more in depth in a future post) by the NSP and will then fallback to obeying the rules defined in the resource’s service firewall. This is a stellar way for you to get a baseline on how much shit will break with your new rules (and oh yes will shit break for some folks out there).
Once you understand the traffic patterns and design rules around what you want to allow in via the public side of the PaaS, you can flip the resource association to enforced mode. Once you flip that switch, the associated resources will have public access blocked both inbound and outbound. If you have IP whitelisting defined, those rules are ignored. If you checked off the “Allow Microsoft trusted services”, those rules are ignored. As I mentioned above, access through a Private Endpoint is never affected by NSPs as NSPs are concerned with traffic ingressing or egressing from the public sides of the PaaS resource.
It’s worth noting that a new value of the publicNetworkAccess property has been introduced. The publicNetworkAccess property is a property standard to PaaS (I haven’t seen one without it yet). Typically, the two values are either Enabled or Disabled. The property will be typically be set to Enabled if you’re allowing all public access or are restricting it to specific IP addresses, trusted services, specific resources, or service endpoints. It will be typically Disabled when you are blocking all public access and restricting it to Private Endpoints. Note that I use the word typically because this is Azure and there seem to always be exceptions. The new value introduced is SecuredByPerimeter. If you set the publicNetworkAccess property to this the resource is completely locked down to public traffic except for what is allowed in the NSP (even if no NSP is applied). If you plan on transitioning to NSPs fully for controlling public access (once all the resources you need have been onboarded and cross-NSP linking has gone GA) this is the setting you’ll want to go with.
Logging
The best feature of NSPs (in this dude’s opinion) is the logging feature. Like other Azure resources, NSPs support diagnostic settings. These are configured on a per Network Security Perimeter resource and include a plethora of logs categories. These diagnostic settings allow you to turn on detailed logging of traffic that comes in and out of an NSP. This provides you a standard log for all inbound and outbound traffic vs relying on the resource-level logs which can vary greatly per service (again, looking at you AI Search!).
Imagine being able to confirm that a user’s machine is accessing resource over the Microsoft public backbone vs a Private Endpoint and being able to see exactly what IP they’re using to do it. I can’t tell you how helpful this would have been over the past few years where forward web proxies were in use and were incorrectly configured for DNS affecting access to Private Endpoints.
This is such a damn cool feature that it is deserving of its own deep dive post. I’ll be adding this over the next few weeks.
Summing it up
For the purposes of this post, I really want you to take away an understanding of the NSP primitives, what they do, and how they’re related. Do some noodling on how you think you’d use these primitives and what use cases you might apply them to.
Here are some key points to walk away with:
Network Security Perimeters rules apply only to public traffic, this means traffic incoming to the service’s public IP on the Microsoft public backbone or leaving the service the Microsoft public backbone. They do not affect traffic coming in through a Private Endpoint.
Resources can be associated to Network Security Perimeters across subscriptions.
Leverage transition mode (learning mode in the API) to understand what traffic is coming in and going out of your resources over the public endpoints and how your access rules may effect them.
For resources that support NSPs (and are generally available) think about deploying those resources (it’s only a few as of the date of this post) with the publicAccessProperty set to SecuredByPerimeter at creation to ensure all public network access is controlled by a Network Security Perimeter. This will force you to use NSPs to control that traffic. Auditing or enforcing with Azure Policy would be nice control on top.
Do some experimentation with the logging provided by NSPs. It will truly blow your mind how useful the logs are to troubleshooting networking issues and identifying network security threats.
Keep in mind that NSPs will block diagnostic logs from being sent to a Log Analytics Workspace, Storage Account, or Event Hub for any resources within the NSPs. If you use a centralized Log Analytics Workspace model today, you are best off keeping NSPs in transition mode until cross-NSP linking goes generally available.
PaaS resource accessing a resource within a NSP needs to have a managed identity if you’re using subscription-based inbound rule. If you try to use API keys (like trying to hit a Microsoft Foundry resource in an NSP using an AI Search resource set to use the API key of the Foundry resource) the access will fail.
Before I close this out, you’re probably wondering why I didn’t cover the Links resource. That resource was so special it deserved it’s own post.
In my next post I’ll walk through three common use cases for NSPs. I’ll cover how the problem was previously solved with service firewall controls and how it can be solved with NSPs. I’ll also walk through the configuration in the Portal and through Terraform. I’ll finish off this series (unless I think of anything else) with a deep dive into NSP logging.
Journey Of The Geek 