Today, you can use AWS Network Firewall to protect traffic flowing to and from containerized applications on Amazon Elastic Kubernetes Service (Amazon EKS) and Amazon Elastic Container Service (Amazon ECS) clusters. If you run AI and machine learning (ML) workloads on Amazon EKS—such as model inference, RAG pipelines, or JupyterHub—your containerized workloads require the same firewall protections you enforce for traditional applications. However, traditional firewall rules rely on IP addresses, and pod IPs in Kubernetes change frequently as containers scale or restart. Writing and maintaining static firewall rules based on these ephemeral IPs, CIDRs, and subnets is difficult and error-prone, which can leave gaps in your security posture.

Kubernetes Network Policies offer basic traffic control at the namespace level, operating at layers 3 and 4. Depending on your security requirements, you might need additional capabilities beyond what network policies provide: Layer 7 inspection, FQDN-based filtering, and protection from threats detected by managed IDS/IPS rules. Visibility into which pod or service generates blocked traffic is equally important, so you can troubleshoot faster and meet audit requirements.

You can use container attribute-based rules for Network Firewall to define firewall rules for your containerized workloads on both Amazon EKS and Amazon ECS using native container attributes, rather than relying on ephemeral IP addresses. For Amazon EKS, these attributes include namespaces, pod names, cluster names, and labels. This reduces the need to maintain IP-based rules in dynamic container environments. While this capability supports both Amazon EKS and Amazon ECS, this post focuses on Amazon EKS. Your containerized workloads get the same Network Firewall capabilities you use today.

There is no additional charge for the feature itself, because it’s included in the base tier of Network Firewall.

When you create a container association and link it to your EKS cluster, Network Firewall automatically discovers and tracks the pods that match your defined attributes (namespace, labels, cluster name) and resolves them to their current IP addresses. As pods scale up or restart, the firewall dynamically updates the IP-to-attribute mapping in near real-time and no manual rule updates are required. This approach keeps your firewall rules accurate in dynamic environments while minimizing performance impact on the EKS cluster. In multi-cluster environments, this feature enables centralized cross-cluster traffic inspection for any traffic that passes through the firewall.

Container attribute-based rules also enrich firewall alert logs with container context. Alert logs now include a new metadata field with the container association name associated with the matched rule. This gives security teams the ability to trace blocked, allowed, or alerted traffic directly back to the originating workload. Network Firewall exports these enriched logs to Amazon CloudWatch Logs and Amazon Simple Storage Service (Amazon S3), from where you can forward them to the SIEM of your choice. To bind these attribute groups to running workloads, Network Firewall continuously watches your EKS cluster for pod lifecycle events (create and delete) across the namespaces covered by your container association definition. This definition is stored in a container association, keyed by attribute name and value.

When published, you reference these @ aliases in stateful Suricata rules. The following are some common patterns:

• Pod group rules: Allow only payment-service pods to reach the external payment gateway over TLS:

  pass tls @ecommerce_pods any -> any 443 (msg:"allow ecommerce to payment gateway"; tls.sni; content:“checkip.amazonaws.com”; flow:to_server,established; sid:1; rev:1;)

• Layer 7 application rules : Enforce block from all pods from reaching malicious destinations:

  drop tls @all-pods any -> $EXTERNAL_NET any (msg:"Block malicious sites"; aws_domain_category:malicious-sites; sid:10; rev:1;)

At packet evaluation time, Network Firewall expands each @ reference against the current catalog. When pods scale, restart, or move between nodes, the controller refreshes group membership, and the firewall picks up the new IPs, hence no rule edits or operator intervention is required. Each match—whether alert, pass, or drop—streams to the logging destination of your choice with container context. This gives your team a real-time, auditable view of policy effectiveness and a feedback loop for tuning rules and pod-group definitions over time.

The Network Firewall container attribute-based rules for Amazon container workloads can be configured using the AWS Management Console for Amazon Virtual Private Cloud (Amazon VPC), AWS Command Line Interface (AWS CLI), or AWS SDK by creating a container association. This container association then can be used to create attribute-based Network Firewall rules.

This walkthrough requires an existing Network Firewall configured to filter traffic through your Amazon VPC. If you haven’t set one up yet, see Getting started with AWS Network Firewall.

Step 1 – Create a container association:

1. In the AWS VPC console, navigate to Network Firewall, select Container associations. Choose Create container association.
2. Enter a Name and optional Description for this container association.
3. Under Cluster configuration, select the Cluster type and select your EKS cluster from the Cluster drop down.
4. For Attribute filters, configure the EKS attribute to identify which pods to associate:
   • Attribute key: Enter the attribute key defined in your EKS cluster (for example, namespace, pod, cluster, or custom label key).
   • Attribute value: Enter an attribute key value defined in your EKS cluster.

Figure 1: Create container association

Step 2 – Create an attribute-based firewall rule:

1. In the AWS VPC console, navigate to Network Firewall, then select Network Firewall rule groups.
2. Select Create rule group.
3. For Rule group type, select Stateful rule group.
4. For Rule group format, select Suricata compatible rule string.
   
   

   Figure 2: Rule group selection

5. For Rule evaluation order, select Strict order. Choose Next.
6. Under Describe rule group, enter a Name, Description, and Capacity for the rule group. Choose Next.
   
   

   Figure 3: Describe rule group

7. Under IP set references, enter a variable name and from the resource ID drop-down, select the container association created in step 1.
8. Under Suricata compatible rule string, enter your Suricata rule string. The following is a sample string used for this post:

   pass tls @ecommerce_pods any -> any any (msg:"allow ecommerce to payment gateway"; flow:to_server; tls.sni; dotprefix; content:".checkip.amazonaws.com"; endswith; nocase; alert; sid:101; rev:1;)
   
   reject tls @ecommerce_pods any -> any 443 (msg:"block ecommerce pods to external ecommerce website"; flow:to_server; tls.sni; dotprefix; content:".amazon.com"; endswith; nocase; alert; sid:104; rev:1;)

   

   Figure 4: Configure rules

9. Choose Next.
10. Enter the details if required on the next options. For this post, we’re using the default values.
11. On the review and create page, choose Create rule group.

To verify these rules are working as expected, test using the curl command on a pod in the ecommerce namespace. A curl request to www.amazon.comshould fail, because action=rejectis defined in the Suricata rule string. Similarly, a request to the payment gateway URL should succeed, because action=passis defined in the Suricata rule string.

Test 1 – Allowed traffic:

kubectl exec -n ecommerce deployment/payment-service -- curl -sk --max-time 5 -w "\nHTTP_CODE:%{http_code}\n" https://checkip.amazonaws.com/

HTTP_CODE:200

Test 2 – Blocked traffic:

kubectl exec -n ecommerce deployment/payment-service -- curl -sk --max-time 5 https://www.amazon.com 2>&1

curl: (35) Recv failure: Connection reset by peer
command terminated with exit code 35

Container association can also be used in a Standard stateful rules format.

There are several important considerations when adopting this feature.

1. Source NAT (SNAT) must be disabled so that the Network Firewall can see pod IP addresses. If SNAT remains enabled, only the node IP will be visible, preventing granular pod-level egress controls.
2. This feature can’t enforce security on pod-to-pod traffic within the same node, because that traffic doesn’t traverse the Network Firewall endpoint. A separate solution is needed for this use case.
3. Performance impact can vary based on rule complexity and traffic volume.

In this post, you learned how container attribute-based rules for AWS Network Firewall solve the challenge of securing dynamic containerized workloads. You explored how the feature maps Kubernetes attributes such as namespaces, pod names, cluster names, and labels to firewall rules, eliminating the need to track ephemeral IP addresses. You walked through how to create a container association to link your EKS cluster attributes to Network Firewall, and then how to reference that association using IP set references in Suricata compatible rule strings. This gives you granular traffic control of your Amazon EKS workloads with the same Network Firewall capabilities as traditional applications including layer 7 inspection, FQDN filtering, TLS decryption, and managed IDS/IPS rules along with enriched logging that traces traffic back to the originating workload.

If you have feedback about this post, submit comments in the Comments section below.

When securing an Amazon Web Services (AWS) environment, teams naturally prioritize inbound controls, firewalls, WAFs, and access policies, because that’s where the most visible threats originate. Outbound traffic, on the other hand, tends to get less attention. It’s often left open by default to avoid breaking application dependencies and because the risk feels less immediate. But overlooking egress means missing a key layer of defense. Without visibility into what’s leaving your network, it’s harder to detect unintended data flows, whether from misconfigured services, overly broad permissions, or workloads with unauthorized access.

Real-world incidents highlight why egress controls deserve attention across both traditional cloud workloads and emerging AI-driven architectures.

In traditional cloud environments, application-level security issues remain a persistent threat. For example, when CVE-2025-55182 (React2Shell) was publicly disclosed in December 2025, multiple organized groups began exploitation attempts within hours, targeting unpatched React Server Components to achieve remote code execution. After a workload is accessed by an unauthorized party, they typically establish outbound command-and-control channels and begin exfiltrating data. Without egress controls in place, that outbound traffic can flow freely, and the unauthorized access might go unnoticed until a compliance audit, customer complaint, or incident notification forces discovery.

Agentic AI systems introduce a new dimension to this risk. The OWASP Top 10 for Agentic Applications identifies threats such as Agent Goal Hijack (ASI01), where unauthorized parties manipulate an autonomous agent’s objectives to silently exfiltrate data, and Unexpected Code Execution (ASI05), where an agent with unauthorized access generates and runs potentially damaging code that establishes reverse shells or transfers sensitive data to external endpoints. As organizations deploy AI agents with access to tools, APIs, and code interpreters, these agents become high-value targets, and their outbound network activity must be constrained with the same rigor as any other workload.

In both scenarios, the common thread is unauthorized outbound traffic. In this post, we show you how to implement layered egress detection and protection using AWS services working together to reduce unauthorized data transfer risk, whether the source is an application with unauthorized access or a manipulated AI agent.

Architecture overview

Figure 1: Hub-and-spoke egress control architecture

The following architecture, shown in Figure 1, illustrates one approach to implementing a hub-and-spoke network pattern for a multi-account AWS environment. Note that alternative designs might be appropriate depending on your organizational requirements and constraints.

Application workloads reside in spoke virtual private clouds (VPCs) that connect to an AWS Transit Gateway, which serves as the central hub for routing inter-VPC and internet-bound traffic while enforcing network segmentation through carefully crafted route tables. Spoke VPCs use VPC endpoints for secure AWS service access, keeping traffic within the AWS network where possible. VPC endpoint policies are applied as key data perimeter controls, restricting which principals can access AWS services and which resources can be accessed through these endpoints.

Internet-bound traffic is routed through a transit gateway-attached AWS Network Firewall, which inspects and filters outbound flows before they reach the internet. This centralized routing model scales horizontally by adding spoke VPCs without modifying the inspection infrastructure, making it well suited for organizations that have multiple AWS accounts.

It’s important to understand that Amazon Route 53 Resolver DNS Firewall must be deployed across your VPCs to filter DNS queries that resolve through the Route 53 VPC Resolver. (DNS queries sent directly to other DNS resolvers bypass it, but can be filtered with AWS Network Firewall.) The DNS firewall uses both managed and custom domain lists to filter DNS queries, blocking resolution of known unauthorized domains before any network connection is established.

Data perimeter controls are enforced at multiple layers: service control policies (SCPs) and resource control policies (RCPs) at the AWS Organizations level, VPC endpoint policies at the network level, and resource policies on individual services. AWS IAM Access Analyzer is deployed at the organization level to continuously detect publicly accessible or externally shared resources.

A detection layer comprising Amazon GuardDuty, AWS Security Hub, and IAM Access Analyzer provides continuous monitoring and threat detection. Findings are routed through an integration layer using Amazon EventBridge, which triggers AWS Lambda-based automated remediation and sends notifications using Amazon Simple Notification Service (Amazon SNS). This integration layer also feeds back into your network controls, automatically updating Network Firewall deny rules and DNS Firewall block lists based on detected threats.

Centralized observability is achieved through Amazon CloudWatch Logs and CloudWatch dashboards. Network Firewall flow logs and alert logs are collected centrally to support incident investigation and compliance reporting.

This architecture applies equally to traditional application workloads and AI-driven workloads. An AI agent running on Amazon Bedrock, for example, typically sits inside a spoke VPC. When that agent invokes an external API or attempts to reach the internet, its traffic follows the same path through Transit Gateway and Network Firewall as any Amazon Elastic Compute Cloud (Amazon EC2) or container workload. The agent doesn’t get a special lane out, it’s subject to the same domain allow-lists, the same DNS filtering, and the same data perimeter policies.

That said, agents often need outbound access to invoke external tools or third-party APIs as part of their normal operation, which makes allow-list design more nuanced. You will want to scope allowing domains tightly to the specific endpoints your agents legitimately need, rather than opening broad categories. Complementing these network-layer controls with application-layer guardrails such as Amazon Bedrock Guardrails—which can filter harmful content and detect prompt attacks before they reach the network layer—adds another layer of defense.

Preventive controls

The following preventive controls block data exfiltration before it occurs. Because they actively disrupt traffic, reserve them for activity that is confirmed or highly likely to be potentially damaging.

AWS Network Firewall

Consider this scenario: an unauthorized party compromises an EC2 instance in one of your spoke VPCs and attempts to exfiltrate sensitive data to an external server. Now consider an agentic AI scenario: an unauthorized party uses prompt injection to hijack an AI agent’s goal (OWASP ASI01), redirecting it to exfiltrate training data to an external endpoint. Network Firewall is designed to block this attempt because the unauthorized destination isn’t on the approved domain allow-list—the same control that stops an EC2 instance with unauthorized access— also stops a manipulated AI agent.

Without centralized egress inspection, that traffic flows directly to the internet through a NAT gateway. Network Firewall prevents this by providing centralized, Layers 3–7 deep packet inspection with advanced threat intelligence capabilities, including IP address, port, and protocol filtering; plus packet content inspection using Suricata-compatible rules.

In this architecture, Transit Gateway funnels internet-bound traffic from multiple spoke VPCs through Network Firewall for centralized inspection. The firewall endpoint becomes the target for 0.0.0.0/0 routes, routing outbound internet traffic for inspection before reaching NAT gateways for address translation. In both scenarios, Network Firewall blocks the exfiltration attempt at the network layer before data leaves your environment. Its key capabilities include:

• Domain name filtering: Block traffic to unauthorized destinations (such as a command-and-control server at *.untrusted-domain.com)
• IP and port rules: Define explicit allow-lists for external IPs your applications truly need, blocking everything else
• Domain category filtering: Block entire categories of domains that your workloads should never communicate with
• IDS and IPS: Detect and block known attack patterns in outbound traffic using Suricata-compatible rules
• Port and protocol enforcement: Help ensure only expected protocols use their designated ports (for example, only HTTPS on TCP port 443), preventing protocol tunneling
• Geographic IP filtering: Block outbound traffic to geographic regions where your organization has no business relationships
• TLS decryption: Inspect encrypted traffic to detect exfiltration attempts hidden within HTTPS connections
• Threat intelligence integration: Use managed threat intelligence (such as active threat defense that uses the Amazon threat intelligence system MadPot) feeds or custom Suricata rules to detect unexpected patterns
• Automatic scaling: Handles up to 100 Gbps per Availability Zone

For multi-account environments, AWS Firewall Manager can centrally deploy and manage Network Firewall across your organization’s accounts, helping maintain consistent egress rules everywhere. Additionally, AWS Network Firewall Proxy (in preview) offers explicit proxy capabilities with granular HTTP/HTTPS filtering—including URL path and HTTP method-level controls—for workloads that require application-layer inspection of outbound web traffic.

Route 53 Resolver DNS Firewall

DNS queries made through Route 53 VPC Resolver don’t pass through the outbound network path inspected by Network Firewall or third-party firewalls. Unauthorized parties can take advantage of this by encoding sensitive data within DNS queries to external servers, a technique known as DNS tunneling. This risk extends to agentic AI workloads. An agent with code execution capabilities (OWASP ASI05) could be tricked into running a script that encodes sensitive data (like customer records, model weights, API keys) into DNS queries directed at an externally controlled nameserver. DNS Firewall is designed to block these queries regardless of whether they originate from a traditional workload or an AI agent, because the filtering happens at the resolver level before any connection is established.

Because DNS traffic is essential for normal operations and often overlooked in security architectures, it represents a common unauthorized data exfiltration channel. Route 53 Resolver DNS Firewall closes this gap by filtering and potentially blocking outbound DNS queries from your VPCs. Its core capabilities consist of:

• Block unauthorized domains: AWS provides managed domain lists, including an Aggregate Threat List covering malware, ransomware, botnet, spyware, and DNS tunneling
• Enforce allow-lists: Permit only queries to approved domains, blocking everything else
• DNS Firewall Advanced features: AI and machine learning (AI/ML)-backed detection of DNS tunneling, Domain Generation Algorithms (DGAs), and dictionary DGAs

Configuration is straightforward: Create rule groups with domain match lists and actions (block, allow, and alert), then associate them with your VPCs. The DNS resolver applies these rules to every DNS query made from instances in the VPC through Route 53 Resolver. This prevents unauthorized parties from using DNS tunneling to exfiltrate data, a technique that completely bypasses inspection by firewalls in the egress VPC.

For a deeper look at the risks associated with DNS exfiltration and DNS Firewall Advanced capabilities, see Protect against advanced DNS threats with Amazon Route 53 Resolver DNS Firewall.

Data perimeters

A data perimeter is a set of preventive guardrails that allow only your trusted identities to access trusted resources from expected networks. While the preceding controls secure the network paths out of your environment, data perimeters secure the API-level paths, helping to ensure that even if an unauthorized party gains access to valid credentials, they can’t use AWS service APIs to move data to resources outside your organization.

This comprehensive approach uses three primary AWS capabilities working together:

1. Service control policies (SCPs): Organization-wide preventive controls that restrict what identities can do. In the context of egress protection, SCPs can prevent users from creating resources that bypass your egress controls (for example, preventing the creation of VPCs without DNS Firewall associations or blocking the use of services that could establish alternative outbound paths).
2. Resource control policies (RCPs): Controls that restrict API access to your resources. While RCPs aren’t directly egress controls, they act as a complementary layer. For example, they can block attempts to access your Amazon Simple Storage Service (Amazon S3) buckets from outside your organization at the resource level.
3. VPC endpoint policies: VPC endpoints enable private communication with AWS services without traffic going through the internet. VPC endpoint policies are resource-based AWS Identity and Access Management (IAM) policies that govern what can be accessed through that endpoint. This is where data perimeters most directly function as an egress control.

Consider the following VPC endpoint policy that restricts Amazon S3 access through the endpoint to only S3 buckets within your organization, directly preventing an insider or a workload with unauthorized access from copying data to an external S3 bucket:

{
  "Statement": [{
    "Sid": "DenyAccessToNonOrgBuckets",
    "Effect": "Deny",
    "Principal": "*",
    "Action": "s3:*",
    "Resource": "*",
    "Condition": {
      "StringNotEqualsIfExists": {
        "aws:ResourceOrgID": "<my-org-id>"
      }
    }
  }]
}

This policy is designed to deny any Amazon S3 operation through this VPC endpoint unless the target S3 bucket belongs to your organization. Without this control, a workload with unauthorized access could use aws s3 cp to copy sensitive data to an externally controlled bucket in a different AWS account.

Data perimeter policies don’t grant new permissions, they narrow what’s accessible by establishing guardrails, acting as a second authorization layer. By implementing these perimeters using IAM condition keys like aws:PrincipalOrgID, aws:ResourceOrgID, aws:SourceVpc, and aws:SourceVpce, you create layered permissions guardrails that help prevent unintended access patterns and configuration errors.

For more information on implementing perimeter controls, explore the Building a Data Perimeter AWS whitepaper.

Detective controls

The following detective controls surface data exfiltration attempts after they occur. Because they observe rather than disrupt traffic, you can apply them broadly to flag unexpected activity for investigation. Use the findings to identify recurring unauthorized patterns that can graduate into preventive controls.

Amazon GuardDuty: Detective control for egress threats

GuardDuty serves as your critical detection layer for egress protection, continuously monitoring for outbound threats that evade or take advantage of your preventive controls. GuardDuty identifies behavioral anomalies and attack patterns that indicate active data exfiltration attempts. Its egress-focused detection capabilities include:

• DNS-based data exfiltration detection: The Trojan:EC2/DNSDataExfiltration finding alerts when EC2 instances are transferring data through DNS channels. GuardDuty also identifies queries to DGA domains commonly used for command-and-control communication.
• Known malicious actor detection: Exfiltration:S3/MaliciousIPCaller triggers when Amazon S3 data APIs like GetObject or CopyObject are invoked from IP addresses on AWS threat intelligence feeds, signaling active data extraction attempts.
• Multi-step attack sequence correlation: GuardDuty Extended Threat Detection correlates multiple unexpected events to identify multi-stage exfiltration campaigns. For example, AttackSequence: S3/CompromisedData detects when unauthorized parties modify S3 bucket policies to broaden access and then systematically extract data using stolen credentials.

GuardDuty findings serve dual purposes in your egress strategy. Alerts about attempted exfiltration that failed confirm your preventive layers (Network Firewall, DNS Firewall, and data perimeters) are functioning effectively: the threat was detected because it progressed far enough to trigger behavioral analysis, but your controls blocked the actual data loss. Conversely, findings indicating successful exfiltration trigger immediate incident response workflows, enabling you to contain active incidents, revoke stolen credentials, and quarantine affected resources before significant damage occurs.

Integrate GuardDuty with Security Hub for centralized correlation across your security services and implement automated response through EventBridge and Lambda functions to enable real-time containment when high-severity exfiltration findings occur.

IAM Access Analyzer

IAM Access Analyzer helps identify potential data exfiltration paths by detecting resources accessible from outside your AWS account or organization. It uses automated reasoning technology to analyze resource-based policies and identify which of your resources can be accessed by external entities (principals outside your zone of trust), continuously monitoring public and cross-account access.

External access analyzers identify resources shared with external principals (such as other AWS accounts or public access). For example, when an S3 bucket is configured to allow access outside your zone of trust through bucket policies, ACLs, or access points, IAM Access Analyzer generates a finding with details about the access path, including the external principal and the level of access granted. Security teams can respond by taking immediate action to remove unintended access or by setting up automated notifications through EventBridge to engage development teams for remediation.

AWS Security Hub

Security Hub exposure findings provide a comprehensive view of potential security risks by correlating data from multiple AWS security services. These findings identify when resources might be vulnerable to data exfiltration by integrating intelligence from GuardDuty (for threat detection), Amazon Inspector (for vulnerability assessment), Security Hub CSPM (for configuration compliance), and Amazon Macie (for sensitive data discovery). For example, it can identify when a publicly exposed S3 bucket contains sensitive data and isn’t encrypted at rest, flagging it as a potential data exfiltration risk that requires immediate attention.

AWS Shield network security director (in preview) complements Security Hub by discovering and analyzing your network topology to identify resources with unrestricted outbound internet access, helping you detect potential egress blind spots across your environment.

Egress security strategy

You don’t need to implement all these controls at once. The following phased approach lets you build your egress security posture incrementally, at a pace that matches your organization’s operational maturity and risk tolerance.

• Phase 1 – Quick wins: Enable Route 53 DNS Firewall across your VPCs to close the DNS exfiltration gap. Enable GuardDuty across your accounts for baseline threat detection.
• Phase 2 – Foundational: Deploy organization-wide data perimeters (SCPs, RCPs, and VPC endpoint policies). Deploy Network Firewall as a transit gateway-attached firewall.
• Phase 3 – Efficient: Enable IAM Access Analyzer for continuous external access detection. Implement automated remediation through EventBridge and Lambda to update firewall rules in real time. Centralize findings in Security Hub with automated alerting.

Conclusion

Egress security isn’t a single control—it’s a layered strategy. Start by assessing your current posture across network filtering, DNS security, data perimeters, and detective controls. Identify the gaps, then follow the phased approach outlined in this post to close them incrementally. Regular testing through simulated exfiltration attempts validates that your controls work effectively. These controls apply with equal force to agentic AI workloads, where manipulated agents can become unintended exfiltration vectors. Put egress under control and turn your outbound blind spots into monitored checkpoints.

If you have feedback about this post, submit comments in the Comments section below.

AWS Network Firewall now supports native attachment to AWS Transit Gateway. Customers commonly use Transit Gateway to route traffic from Amazon Virtual Private Cloud (Amazon VPC) networks to a centralized inspection VPC (a VPC dedicated to hosting firewall endpoints for traffic inspection) where their network firewall endpoints are deployed. This centralized deployment model reduces the need to have Network Firewall endpoints in each VPC, optimizing costs and providing a centralized point of network security control.

Customers deploying Network Firewall in a centralized deployment model using Transit Gateway have traditionally set up a dedicated inspection VPC with firewall subnets and managed the associated routing to direct traffic through the firewall. With native attachment, Network Firewall attaches directly to Transit Gateway, eliminating the need for the inspection VPC and enabling capabilities such as flexible cost allocation through Transit Gateway metering policies.

In this post, we explain what a Transit Gateway-attached network firewall is, the technical capabilities it unlocks, reasons to migrate to it, and how to perform the migration. For detailed step-by-step guidance on how to perform the migration using Terraform, AWS CloudFormation, or manually in the AWS Management Console, see the accompanying migration guide repository.

A Transit Gateway-attached network firewall simplifies your network architecture by eliminating the need for a dedicated inspection VPC. Instead of creating an inspection VPC with firewall subnets and configuring the associated routing, you create your network firewall and specify which Transit Gateway instance you want to attach it to. AWS deploys the firewall endpoints into an AWS-managed VPC on your behalf. You don’t own or manage that VPC. From your perspective, the firewall appears as a Transit Gateway network function attachment that you route traffic to, similar to other Transit Gateway attachments.

You might want to migrate to a Transit Gateway-attached network firewall for the following reasons:

• Access to flexible cost allocation: With native attachment, you can use Transit Gateway metering policies to charge back account owners for traffic they send through the centralized firewall. Flexible cost allocation for Network Firewall traffic over a Transit Gateway is only available with a Transit Gateway-attached firewall. Without native attachment, you can only allocate Transit Gateway data processing charges, not the Network Firewall charges.
• Reduced architectural complexity: You can eliminate the inspection VPC, leaving one less VPC to manage along with its associated routing tables and subnets.

Before migrating to a Transit Gateway-attached network firewall, gather the following information and keep these key considerations in mind.

When you create your new Transit Gateway-attached network firewall, you will need:

• Transit Gateway ID: The ID of the Transit Gateway instance you will attach your network firewall to.
• Logging configuration: Create a new logging configuration (such as new Amazon CloudWatch log groups) for the new firewall. During migration, you will be running both firewalls simultaneously. Keeping the logs separate simplifies monitoring and troubleshooting each firewall during the migration period. After migration is complete, you can point the new firewall to your existing logging destinations.
• Firewall policy: Create a new firewall policy for the new firewall rather than reusing your existing one. During the migration period, a separate policy lets you make changes to the new firewall’s policy without affecting the existing firewall while both are running simultaneously. After migration is complete, you can attach your existing production policy to the new firewall.

There are some important considerations to address while planning for this change.

• Transit Gateway encryption: Check if you’re using Transit Gateway encryption support. If encryption is enabled and required for your security posture, native attachment to Network Firewall doesn’t currently support this capability. You will need to continue using your current firewall configuration.
• NAT gateway Elastic IPs: If you need to maintain the same public IPs (for example, for partner allowlisting), plan for this during migration. For more information, see the Preserving your NAT gateway Elastic IPs during migration section later in this post.
• Maintenance window: Plan to perform this migration during a dedicated maintenance window. Brief network outages will occur during parts of the process, such as when swapping Transit Gateway route table associations and replacing NAT gateways.

Leave your existing Network Firewall setup unchanged while setting up the new Transit Gateway-attached firewall. With this approach, you can minimize potential downtime and test the new configuration before migrating production traffic.

The migration process varies depending on your current architecture. The following sections walk through the two most common centralized Network Firewall architectures and the high-level migration process for each. For detailed step-by-step guidance on how to perform the migration using Terraform, CloudFormation, or manually in the console, see the migration guide repository.

In this architecture, shown in the following diagram, you have a dedicated inspection VPC with your network firewall endpoints, and a separate dedicated egress VPC with your NAT gateways.

Figure 1: Centralized egress traffic inspection with Network Firewall and Transit Gateway, with inspection and egress separated into two VPCs.

The high-level migration process for this architecture is:

1. Deploy a new egress VPC with a temporary NAT gateway. Creating a new VPC lets you leave the existing deployment unchanged while working on the migration.
2. Create your new network firewall with native attachment to your Transit Gateway.
3. Configure three new Transit Gateway route tables to define the traffic path through the new firewall: an inspection route table (associated with the new firewall), an egress route table (associated with the new egress VPC), and a temporary migrated spoke route table (for testing individual spoke VPCs on the new path).
4. Test the new firewall by moving a single spoke VPC to the new path. Verify connectivity and confirm the firewall is inspecting traffic by checking the alert logs for layer 7 (application layer) details. Layer 7 information in the alert logs indicates the firewall is seeing both directions of the traffic flow. If asymmetric routing were occurring, the firewall would only see one direction and would not be able to perform application-layer inspection, so the presence of layer 7 details confirms traffic is flowing symmetrically through the new firewall.
5. Migrate the remaining spoke VPCs. You can migrate VPCs incrementally, or when you’re confident in the new firewall deployment, update the default route in your existing spoke route table to point to the new Network Firewall network function attachment, which moves all remaining spokes that share that route table at once.
6. Optionally, preserve your original NAT gateway Elastic IPs by re-routing traffic back to your existing egress VPC (see Preserving your NAT gateway Elastic IPs during migration).
7. Decommission old resources after you’ve verified that traffic is flowing correctly. Which VPCs you remove depends on whether you preserved your original EIPs (see Preserving your NAT gateway Elastic IPs during migration).

Figure 2: Post-migration architecture for Architecture 1, with the inspection VPC eliminated and traffic flowing through the Transit Gateway-attached Network Firewall to a dedicated egress VPC.

For the complete walkthrough of how to perform this migration:

• Terraform migration guide
• CloudFormation migration guide
• Manual console migration guide

In this architecture, shown in the following diagram, you have a single VPC that contains both your network firewall endpoints and your NAT gateways.

Figure 3: Centralized egress traffic inspection with Network Firewall and Transit Gateway, with inspection and egress combined in one VPC.

The migration process for this architecture follows the same high-level steps as Architecture 1.

1. Deploy a new dedicated egress VPC with a temporary NAT gateway. Creating a new VPC lets you leave the existing deployment unchanged while working on the migration.
2. Create your new network firewall with native attachment to your Transit Gateway.
3. Configure three new Transit Gateway route tables to define the traffic path through the new firewall: an inspection route table, an egress route table, and a temporary migrated spoke route table.
4. Test the new firewall by moving a single spoke VPC to the new path. Verify connectivity and confirm the firewall is inspecting traffic by checking the alert logs for layer 7 (application layer) details. Layer 7 information in the alert logs indicates the firewall is seeing both directions of the traffic flow. If asymmetric routing were occurring, the firewall would only see one direction and would not be able to perform application-layer inspection, so the presence of layer 7 details confirms traffic is flowing symmetrically through the new firewall.
5. Migrate the remaining spoke VPCs. You can migrate VPCs incrementally, or once you are confident in the new firewall deployment, update the default route in your existing spoke route table to point to the new Network Firewall network function attachment, which moves all remaining spokes that share that route table at once.
6. Optionally, preserve your original NAT gateway Elastic IPs by transferring them to the new egress VPC.
7. Decommission the old combined VPC after you’ve verified that traffic is flowing correctly.

Figure 4: Post-migration architecture for Architecture 2, with the combined VPC eliminated and traffic flowing through the Transit Gateway-attached Network Firewall to a dedicated egress VPC.

For the complete walkthrough of how to perform this migration, see:

• Terraform migration guide
• CloudFormation migration guide
• Manual console migration guide

Both architectures deploy the same new resources and use the same phased cutover approach. The differences are in the starting Transit Gateway routing structure (Architecture 1 has three route tables across two VPCs, Architecture 2 has two route tables in one VPC) and what you clean up at the end (two old VPCs instead of one). Both architectures converge to the same end state. For a detailed comparison, see the migration guide repository.

Regardless of which architecture you’re migrating from, follow these best practices to minimize risk.

The migration guide repository includes starting architecture CloudFormation and Terraform templates for both architectures, so you can deploy the exact starting environment in a development or test account and run through the entire migration process before touching production.

Test before you migrate. Create your new Transit Gateway-attached firewall in parallel with your existing setup. Use a test VPC to validate the new configuration. Verify that logging is working correctly and that the firewall alert logs show layer 7 traffic details, which confirms there is no asymmetric routing. Test both allowed and blocked traffic scenarios before migrating production traffic.

Migrate in phases. Start with a single, non-critical workload VPC. Update only that VPC’s routes to use the new firewall attachment. Monitor and verify application behavior and performance with the application owner before proceeding. When planning your migration order, migrate spoke VPCs that have east-west traffic between each other at the same time. During the phased migration, spokes on different firewall paths will have their east-west traffic traverse two stateful firewalls. Because each stateful firewall independently tracks connection state, traffic that enters through one firewall and returns through another appears as untracked, causing the firewalls to drop or incorrectly handle the return traffic. When you’re confident in the new firewall deployment, you can update the default route in your existing spoke route table to point to the new firewall, which moves all remaining spokes that share that route table at once. Keep your old firewall configuration active until all traffic is migrated.

Prepare a rollback plan. Document your current route table configurations before making changes. Keep your existing firewall and inspection VPC active during migration. If issues arise, revert the route table changes to restore the previous configuration. Decommission old resources after you’ve verified applications are operating as expected.

Preserving your NAT gateway Elastic IPs during migration

An important consideration during migration is maintaining your existing NAT gateway Elastic IP addresses. Many organizations have these IPs allowlisted with external partners, third-party services, or in firewall rules. Changing these IPs would require coordination with multiple stakeholders and could disrupt business operations.

During migration, you need both your old and new deployments to operate simultaneously, so you can validate the new setup without impacting production traffic. This means creating temporary NAT gateways with temporary Elastic IPs in the new egress VPC.

After you’ve confirmed the new firewall deployment is stable and production traffic has been successfully migrated, you can restore your original Elastic IPs. The process differs depending on your architecture:

• For Architecture 1 (separate inspection and egress VPCs), your existing egress VPC and its NAT gateways are independent of the inspection VPC being decommissioned. You can keep them by re-associating the existing egress VPC’s Transit Gateway attachment with the new egress route table and updating the inspection route table to route traffic there instead of the temporary egress VPC. This is a Transit Gateway routing change that takes seconds, doesn’t require deleting or creating any NAT gateways, and doesn’t increase in complexity with the number of Availability Zones. After the re-association, you delete the temporary egress VPC.
• For Architecture 2 (combined inspection and egress VPC), the old VPC contains both the firewall endpoints and the NAT gateways. The simplest path is to decommission it and move the Elastic IPs to the new egress VPC. To do this, you delete the old NAT gateways to free the Elastic IPs, then create new NAT gateways in the new egress VPC with the original Elastic IPs. This requires a brief maintenance window while the new NAT gateways provision and must be repeated for each Availability Zone.

For the detailed step-by-step procedure, see the EIP preservation steps in the migration guide repository.

In this post, we explained what a Transit Gateway-attached network firewall is and how it differs from the traditional inspection VPC model, the reasons to migrate including reduced architectural complexity and flexible cost allocation, what to prepare before starting, and the high-level migration process for the two most common centralized inspection architectures. We also covered best practices for minimizing downtime, handling east-west traffic between spokes during phased migration, and preserving your existing NAT gateway Elastic IPs.

With a Transit Gateway-attached network firewall, AWS manages the firewall endpoints and the underlying VPC on your behalf, eliminating the inspection VPC from your architecture and enabling flexible cost allocation through Transit Gateway metering policies. The phased migration approach covered in this post lets you run both firewalls in parallel, validate the new path with a single spoke VPC, and cut over the rest of your traffic when you are ready.

For detailed step-by-step guidance using Terraform, CloudFormation, or the AWS Management Console for both architectures covered in this post, see the migration guide repository. The repository includes starting architecture templates so you can practice the full migration end-to-end in a test account before migrating your production environment.

If you have feedback about this post, submit comments in the Comments section below.

Network administrators face a persistent challenge: maintaining domain blocklists and allowlists that keep pace with the internet. New websites and services emerge daily, and keeping these lists current requires constant manual updates that leave gaps in coverage. This challenge intensifies when managing access to rapidly evolving categories like AI services, where new tools launch on a regular basis.

AWS Network Firewall is a managed, stateful network firewall and intrusion detection and prevention service for fine-grained control of your virtual private cloud (VPC) network traffic. With URL and domain category filtering, security teams can use predefined categories to control access instead of managing individual domains. AWS-managed URL and domain categories stay current automatically as new domains are registered, removing the need for manual list maintenance.

This feature is especially useful for organizations navigating AI governance. Instead of manually tracking every new AI service, you can control access to the entire Artificial Intelligence and Machine Learning category while creating exceptions for approved services. The same approach works for social media, streaming sites, gambling, and dozens of other categories, all with built-in audit trails for compliance reporting.

In this post, we walk through URL and domain category filtering configurations for AWS Network Firewall, from basic rules to exception handling and monitoring strategies that give you visibility into how your workloads interact with external services.

With URL and domain category filtering, you control website access using predefined categories instead of individually specifying sites in a domain list rule group. You can select from AWS-managed categories such as Social Networking, Gambling, or Artificial Intelligence and Machine Learning to implement and maintain filtering policies. AWS keeps these categories current automatically, so you don’t need to update firewall policies when new domains are registered.

Network Firewall offers two category filtering options. Domain category filters by domain name using the TLS Server Name Indication (SNI) field, with no decryption required. URL category filters by the full URL path, which requires TLS inspection for HTTPS traffic. To keep things straightforward, this post focuses on domain category filtering. To set up URL category filtering with TLS inspection, see Creating a TLS inspection configuration in Network Firewall.

To follow the steps in this post, start by making sure that you have the following prerequisites in place:

1. An existing Network Firewall deployment: This walkthrough assumes you have an existing Network Firewall deployment to filter egress traffic flows from your Amazon Virtual Private Cloud (Amazon VPC) in place. If you aren’t already using Network Firewall, see Getting started with AWS Network Firewall to set up your firewall before proceeding.
2. The HOME_NET variable set correctly at the firewall policy level: The rules in this post use the $HOME_NET variable to scope traffic to your internal network. In the AWS Management Console for Amazon VPC, select your firewall policy under the Firewall policies tab, select the Details tab, and check the policy variables section under HOME_NET variable override values. We recommend setting this to all RFC 1918 private IP address ranges: 10.0.0.0/8, 172.16.0.0/12, and 192.168.0.0/16. When you set $HOME_NET at the policy level, all rule groups associated with that policy inherit the value automatically. Network Firewall automatically maps $EXTERNAL_NET to the inverse of $HOME_NET, so configuring HOME_NET correctly also configures $EXTERNAL_NET.

Figure 1: Firewall policy details tab showing the HOME_NET variable override values set to RFC 1918 private IP address ranges

To get started quickly, you can create a domain category rule using the console’s built-in rule builder. In this example, we create a single alert rule for the Artificial Intelligence and Machine Learning category.

1. Open the AWS Management Console, search for and open the Amazon VPC console.
2. In the left navigation, scroll to Network Firewall and select Rule groups.
3. Choose Create rule group.
4. For Rule group type, select Stateful rule group.
5. For Rule group format, select Standard stateful rules.
6. For Rule evaluation order, select Strict order. Choose Next.
   
   

   Figure 2: Create Network Firewall rule group page showing Stateful rule group type, Standard stateful rules format, and Strict order evaluation selected

7. Enter Domain-Category-Rules for the Name, Domain Category Rules for the Description, and 50 for the Capacity. Choose Next.
8. In the rule group editor, select the Category Matching radio button.
9. Under Category Matching, select Match all selected categories.
10. Under AWS category type, select Domain Category from the dropdown.
11. Under Categories, select Artificial Intelligence and Machine Learning.
12. For Protocol, select TLS.
13. For Source, select Custom, then enter $HOME_NET in the dialog box.
14. Set the Destination IP to Any.
15. For Action, select Alert.
16. Choose Add rule to add this rule to the rule group. Choose Next.
    
    

    Figure 3: Completed category matching rule showing TLS protocol, $HOME_NET source, Any destination, and Alert action added to the rule group

17. Under Customer managed key, leave the default setting (Customize encryption settings should remain unchecked).
18. Under Add tags – optional, leave the default setting of no tags.
19. Choose Next, then Create rule group.

This rule generates an alert log entry each time a connection matches a domain in the Artificial Intelligence and Machine Learning category. It doesn’t block traffic. To block traffic, change the action to Drop or Reject in step 15.

The console rule builder is a quick way to get started, but we recommend using Suricata compatible rule strings for production deployments. Suricata rules give you full control over rule options, make rules straightforward to copy, edit, share, and back up, and support the majority of the Suricata engine. For more information, see Limitations and caveats for stateful rules in AWS Network Firewall.

The following walkthrough creates the same alert rule you built with the console rule builder, this time using a Suricata rule string.

In the Amazon VPC console, navigate to Network Firewall, then select Network Firewall rule groups.

1. Choose Create rule group.
2. For Rule group type, select Stateful rule group.
3. For Rule group format, select Suricata compatible rule string.
4. For Rule evaluation order, select Strict order. Choose Next.
   
   

   Figure 4: Create Network Firewall rule group page showing Stateful rule group type, Suricata compatible rule string format, and Strict order evaluation selected

5. Enter Suricata-Domain-Category-Rules for the Name, Suricata Domain Category Rules for the Description, and 50 for the Capacity. Choose Next.
6. Leave the Rule variables section empty. The $HOME_NET variable is inherited from the firewall policy, as configured in the prerequisites.
7. Leave IP set references empty.
8. Paste the following rule into the Suricata compatible rule string editor:

   alert tls $HOME_NET any -> $EXTERNAL_NET any (msg:"Artificial Intelligence and Machine Learning Category"; aws_domain_category:Artificial Intelligence and Machine Learning; sid:1000001;)

9. Choose Next.
   
   

   Figure 5: Suricata compatible rule string editor with the domain category alert rule pasted in and the rule variables section left empty

10. Under Customer managed key, leave the default setting (Customize encryption settings should remain unchecked).
11. Under Add tags – optional, leave the default setting of no tags. Choose Next.
12. Choose Create rule group.
13. After creating the rule group, return to your firewall policy and add it under Stateful rule groups. We recommend associating new rule groups in a development or test environment first to validate behavior before deploying to production.

The following table explains each component of this rule:

You can manage exceptions to keep business-critical websites accessible. For example, say you need to allow access to OpenAI while blocking all other AI and ML traffic. To do this, return to the Suricata-Domain-Category-Rules rule group you created earlier and replace the basic alert rule with the following ruleset. Select the Suricata-Domain-Category-Rules rule group, under the Rules section, choose Edit.

Figure 6: Selecting Suricata-Domain-Category-Rules rule group to edit with new rules

Paste in the following rules and choose Save rule group.

# Allow OpenAI (TLS)
pass tls $HOME_NET any -> $EXTERNAL_NET any (tls.sni; dotprefix; content:".openai.com"; nocase; endswith; flow:to_server; alert; msg:"Allow OpenAI over TLS"; sid:1000001;)

# Allow OpenAI (HTTP)
pass http $HOME_NET any -> $EXTERNAL_NET any (http.host; dotprefix; content:".openai.com"; nocase; endswith; flow:to_server; alert; msg:"Allow OpenAI over HTTP"; sid:1000002;)

# Block all other AI/ML category traffic (TLS)
reject tls $HOME_NET any -> $EXTERNAL_NET any (msg:"Block non-approved AI/ML sites over TLS"; aws_domain_category:Artificial Intelligence and Machine Learning; flow:to_server; alert; sid:1000003;)

# Block all other AI/ML category traffic (HTTP)
reject http $HOME_NET any -> $EXTERNAL_NET any (msg:"Block non-approved AI/ML sites over HTTP"; aws_url_category:Artificial Intelligence and Machine Learning; flow:to_server; alert; sid:1000004;)

Figure 7: Suricata compatible rule string editor with the exception-based ruleset containing pass rules for OpenAI and reject rules for the AI/ML category

With strict order evaluation, the firewall evaluates rules in the order you define them. The pass rules for OpenAI appear first, so matching traffic is allowed before the broader category block rules run.

To verify the rules are working as expected, test from a host that routes traffic through your network firewall. These commands suppress the response body and check the exit code of the curl request. If curl completes a TCP connection, it prints CONNECTION ALLOWED. If the firewall resets the connection, curl exits with a non-zero code and prints CONNECTION BLOCKED.

A request to openai.com should succeed because it matches the pass rule:

curl -s -o /dev/null https://openai.com && echo "CONNECTION ALLOWED" || echo "CONNECTION BLOCKED"

Result: CONNECTION ALLOWED

A request to chat.mistral.ai should be rejected because it matches the broader AI/ML category block rule:

curl -s -o /dev/null https://chat.mistral.ai && echo "CONNECTION ALLOWED" || echo "CONNECTION BLOCKED"

Result: CONNECTION BLOCKED

When you add a domain category rule to your firewall policy, Network Firewall performs a category lookup for every connection that matches the rule’s protocol and IP specifications. The rules in this post match on $HOME_NET any -> $EXTERNAL_NET any, which means the firewall looks up the category for all outbound traffic originating from your internal network. This is why it’s important to have the $HOME_NET variable configured correctly at the firewall policy level. With this configuration, a single category rule is enough for category metadata to appear in your firewall logs across all matching connections, not just connections that match the specific category in your rule.

Each log entry includes an aws_category field containing a JSON array of all categories the destination domain belongs to. A single domain can map to multiple categories. For example, a request to chat.mistral.ai produces a log entry with “aws_category": "[\"Social Networking\",\"Artificial Intelligence and Machine Learning\"]” because that domain belongs to both categories.

You can access firewall logs through Amazon CloudWatch, Amazon Simple Storage Service (Amazon S3), and Amazon Data Firehose. These logs show which categorized websites your workloads access, helping you track usage patterns and enforce acceptable use policies.

The following sample log entry shows what a blocked request to chat.mistral.ai looks like using the exception-based rules from the previous section. The alert.signature field contains the rule’s msg value, and the aws_category field lists all categories the destination domain belongs to:

{ 

     "firewall_name": "egress-and-east-west-firewall", 

     "availability_zone": "us-east-1a", 

     "event_timestamp": "1775599146", 

     "event": { 

          "aws_category": "[\"Social Networking\",\"Artificial Intelligence and Machine Learning\"]", 

          "tx_id": 0, 

          "app_proto": "tls", 

          "src_ip": "10.1.1.100", 

          "src_port": 58664, 

          "event_type": "alert", 

          "alert": { 

                    "severity": 3, 

                    "signature_id": 1000003, 

                    "rev": 1, "signature": 

                    "Block non-approved AI/ML sites over TLS", 

                    "action": "blocked", 

                    "category": "" 

          }, 

          "flow_id": 763153567844057, 

          "dest_ip": "172.66.2.203", 

          "proto": "TCP", 

          "verdict": { 

                    "action": "drop", 

                    "reject-target": "to_client", 

                    "reject": [ 

                         "tcp-reset" 

                    ] 

          }, 

          "tls": { 

               "sni": "chat.mistral.ai", 

               "version": "UNDETERMINED" 

          }, 

          "dest_port": 443, 

          "pkt_src": "geneve encapsulation", 

          "timestamp": "2026-04-07T21:59:06.906761+0000", 

          "direction": "to_server" 

     } 

} 

The aws_category field shows the domain belongs to both the “Social Networking” and “Artificial Intelligence and Machine Learning” categories. The verdict field confirms the connection was dropped with a TCP reset sent to the client.

Traffic that matches a pass rule with the alert keyword also generates a log entry with the aws_category field populated. For example, a connection to chat.openai.com that matches the OpenAI exception rule from the earlier section produces a log entry with alert.action set to “allowed” and the same category metadata. This means your queries capture both blocked and allowed traffic.

If you send your firewall logs to Amazon CloudWatch Logs, you can use CloudWatch Logs Insights to analyze category traffic patterns. A single connection can generate multiple log entries (for example, a reject rule log and a default action log for the same flow), so the following queries deduplicate by flow_id to count each connection only once. Because a single domain can belong to multiple categories, results are grouped by category combination. For example, traffic to a domain categorized as both “Social Networking” and “Artificial Intelligence and Machine Learning” appears as a single combined entry.

To get started, navigate to the CloudWatch console. In the left navigation pane under Logs, select Logs Insights. Under Query scope, leave Log group name selected, then select your AWS Network Firewall alert logs log group. For the time window, we recommend starting with the default of 1 hour to keep the queries light. Enter each of the following queries into the editor and choose Run query to review the results. Note that CloudWatch Logs Insights queries incur charges based on the amount of data scanned. See Amazon CloudWatch pricing for details.

Most accessed categories

This query shows which category combinations your workloads connect to most frequently:

fields @timestamp, event.aws_category, event.flow_id
| filter ispresent(event.aws_category) and event.aws_category != "[]"
| stats latest(event.aws_category) as categories by event.flow_id
| stats count(*) as connections by categories
| sort connections desc
| limit 20

Figure 8: CloudWatch Logs Insights query results showing the most frequently accessed category combinations sorted by connection count

Least accessed categories

This query reverses the sort order to surface category combinations with the fewest connections, helping you identify categories that might not be relevant to your environment or that warrant further investigation:

fields @timestamp, event.aws_category, event.flow_id
| filter ispresent(event.aws_category) and event.aws_category != "[]"
| stats latest(event.aws_category) as categories by event.flow_id
| stats count(*) as connections by categories
| sort connections asc
| limit 20

Figure 9: CloudWatch Logs Insights query results showing the least frequently accessed category combinations sorted by connection count ascending

Most accessed categories, allowed traffic only

The event.verdict.action field indicates the actual outcome of each connection:drop for blocked traffic and alert for allowed traffic. This query shows which category combinations have the most allowed connections:

fields @timestamp, event.aws_category, event.flow_id, event.verdict.action
| filter ispresent(event.aws_category) and event.aws_category != "[]"
| stats latest(event.aws_category) as categories, latest(event.verdict.action) as verdict by event.flow_id
| filter verdict = "alert"
| stats count(*) as connections by categories
| sort connections desc
| limit 20

Figure 10: CloudWatch Logs Insights query results showing the most accessed category combinations filtered to allowed traffic only

Most accessed categories, blocked traffic only

The same query filtered to blocked connections. Change the verdict filter to drop:

fields @timestamp, event.aws_category, event.flow_id, event.verdict.action
| filter ispresent(event.aws_category) and event.aws_category != "[]"
| stats latest(event.aws_category) as categories, latest(event.verdict.action) as verdict by event.flow_id
| filter verdict = "drop"
| stats count(*) as connections by categories
| sort connections desc
| limit 20

Figure 11: CloudWatch Logs Insights query results showing the most accessed category combinations filtered to blocked traffic only

Drill down into a specific category

This query uses a like filter to find all traffic where the aws_category field contains a specific category, regardless of what other categories the domain also belongs to. In this example, the query returns all domains your workloads have connected to that map to the Artificial Intelligence and Machine Learning category, broken down by domain and verdict. Replace the category name in the like filter to investigate any category.

fields @timestamp, event.tls.sni, event.aws_category, event.verdict.action, event.flow_id
| filter ispresent(event.aws_category) and event.aws_category like /Artificial Intelligence and Machine Learning/
| stats latest(event.tls.sni) as sni, latest(event.verdict.action) as verdict by event.flow_id
| stats count(*) as connections by sni, verdict
| sort connections desc
| limit 20

Figure 12: CloudWatch Logs Insights query results showing a drill down into the Artificial Intelligence and Machine Learning category with connections broken down by domain and verdict

Bandwidth consumption by category

This query shows which category combinations consume the most egress bandwidth. It correlates flow logs (which contain byte counts) with alert logs (which contain category data) using the shared flow_id field. To run this query, select both your alert log group and your flow log group in CloudWatch Logs Insights.

fields @timestamp
| filter ispresent(event.netflow.bytes) or ispresent(event.aws_category)
| stats sum(event.netflow.bytes) as flowBytes, latest(event.aws_category) as categories by event.flow_id
| filter ispresent(categories) and categories != "[]"
| stats sum(flowBytes) as totalBytes by categories
| sort totalBytes desc
| limit 20

Figure 13: CloudWatch Logs Insights query results showing bandwidth consumption by category combination sorted by total bytes descending

These queries help you identify which categories your workloads access by volume, surface blocked and allowed traffic patterns, and pinpoint where the bulk of your egress bandwidth is going.

In this post, you walked through how to set up URL and domain category filtering on AWS Network Firewall, from creating your first category rule using both the console rule builder and Suricata compatible rule strings, to managing exceptions for approved services and monitoring category traffic patterns with CloudWatch Logs Insights. With AWS-managed categories that stay current automatically, you can control access to broad classes of websites without maintaining individual domain lists, and the built-in aws_category log field gives you the visibility to track how your workloads interact with external services.

This feature is available in all AWS commercial regions where AWS Network Firewall is supported.

To learn more, visit the AWS Network Firewall product page and the feature documentation.

If you’re looking to strengthen your organization’s security posture on Amazon Web Services (AWS) but aren’t sure where to start, then we’re here to help. Security Activation Days are complimentary, virtual, hands-on workshops designed to help you get practical experience with AWS security services in a single session.

Each Security Activation Day is a 3–6 hour virtual workshop where you work directly with AWS security services in real-world scenarios. Through a combination of presentations, demos, and workshops, you will get hands-on practice guided by AWS security specialists either in your own environment or in an AWS-provided sandbox.

Topics rotate across the full spectrum of AWS security, identity, and governance services, including threat detection and response, identity and access management, network and application protection, data protection, and governance and compliance. You will leave with actionable knowledge you can apply to your workloads immediately—not a to-do list of things to research later.

Security Activation Days are made for builders—security engineers, cloud architects, and DevOps teams who want to go deeper on specific AWS security capabilities. Whether you’re evaluating a service for the first time or looking to operationalize something you’ve already deployed, these sessions meet you where you are.

With over 6,400 attendees across 90 events so far in 2026, Security Activation Days consistently earn a 4.8 out of 5 satisfaction rating. Participants tell us the hands-on format is what makes the difference: there’s no substitute for actually configuring a service and seeing the results in real time.

We run Security Activation Days year-round across all time zones, with new sessions added regularly. Find a session, show up ready to learn, and start building today.

If you have feedback about this post, submit comments in the Comments section below.

Turning on DNSSEC makes your domain more secure — but if it’s misconfigured, newer certificate validation rules can stop SSL renewals in their tracks.

Hey there,

You know that satisfying click when you finally turn on DNSSEC? It feels like adding a shiny new deadbolt to your domain’s front door. You’re doing the responsible thing: locking down your DNS against spoofing and hijacks, and making the internet just a bit safer.

Continue reading DNSSEC: The Extra Security Layer That Can Break Your Padlock at Sucuri Blog.

Last month, while working on a WordPress cleanup case, a customer reached out with a strange complaint: their website looked completely normal to them and their visitors, but Google search results were showing something very different.

Instead of normal titles and descriptions, Google was displaying casino and gambling-related content. We have been seeing rising cases of spam on WordPress websites. What made this even more confusing was where the spam was appearing.

Continue reading Shadow Directories: A Unique Method to Hijack WordPress Permalinks at Sucuri Blog.

Hackers bypass the FortiCloud SSO login authentication to create new accounts and change device configurations.

The post New Wave of Attacks Targeting FortiGate Firewalls appeared first on SecurityWeek.

aiFWall is a firewall protection for AI deployments built to use AI to improve its own performance.

The post aiFWall Emerges From Stealth With an AI Firewall appeared first on SecurityWeek.

Artificial intelligence has shifted to being the primary engine for market leadership. To compete, enterprises are shifting from general-purpose computing to AI factories, specialized infrastructures designed to manage the entire lifecycle of AI. However, this transition requires robust security without sacrificing performance and efficiency.

We are proud to announce that Palo Alto Networks Prisma^® AIRS™, accelerated on the NVIDIA BlueField data processing unit (DPU), is now part of the NVIDIA Enterprise AI Factory validated design.

The integrated solution embeds zero trust security directly into the AI infrastructure, providing comprehensive protection without impacting AI performance. By deploying Palo Alto Networks Prisma^® AIRS™ Network Intercept directly onto the NVIDIA BlueField and extending to the cloud, Prisma AIRS establishes an essential zero trust governance fabric for the AI factory, enabling enterprises to accelerate innovation while maintaining control.

This critical architectural shift enables optimal AI performance and infrastructure efficiency by offloading security processing to an isolated domain, while leveraging the DPU's hardware acceleration via NVIDIA DOCA to enforce security policies at line speed. The implementation also leverages real-time workload information captured using DOCA Argus, which is then passed to Cortex XSIAM^® where it is used for AI-driven responses using the Cortex XSOAR^® orchestration platform.

Rich Campagna, SVP Product Management, Palo Alto Networks said:

The AI Factory is the new engine for value creation, and securing it is a board-level imperative. The validation of Palo Alto Networks Prisma AIRS accelerated with NVIDIA BlueField within the NVIDIA Enterprise AI Factory enables a new security architecture for the AI era. We are embedding trust directly into the infrastructure, giving leaders the confidence to safeguard their proprietary intelligence and deploy AI bravely.

Kevin Deierling, senior vice president of Networking at NVIDIA said:

AI is transforming every industry and security must evolve to protect AI factories. To be scalable, security must be distributed and embedded within the AI infrastructure. This is achieved with NVIDIA BlueField running Palo Alto Networks Prisma AIRS to deliver robust, runtime security for the AI factory, with optimal AI performance and efficiency.

Deploy AI Bravely with a Future-Proof Foundation

The Future of Secure AI Factories

In addition to deploying Palo Alto Networks Prisma AIRS on NVIDIA BlueField in a distributed model, it’s essential to maintain a centralized Hyperscale Security Firewall (HSF) cluster at the ingress and egress points of the AI factory to enforce a defense-in-depth strategy. Beyond network segmentation, individual workloads can selectively route traffic through hyperscale clusters to detect advanced application-layer threats and prevent lateral movement. These hyperscale firewall clusters scale elastically with demand, delivering session resiliency and the high availability required for critical AI operations.

This architecture fundamentally improves the Total Cost of Ownership (TCO) for AI infrastructure. By isolating security functions on BlueField, enterprises enable 100% of host computing resources to be dedicated to AI applications. This elimination of resource contention allows the AI Factory to maximize token throughput and capital efficiency.

This validated design is the blueprint for immediate efficiency. It provides a seamless path for enterprises to shift from general-purpose clusters to secure AI factory infrastructure without costly overhauls. More importantly, this collaboration establishes an unparalleled roadmap for future-proofing your investment. By securing operations with the high-performance NVIDIA BlueField-3 today, the architecture is inherently ready for the next generation, NVIDIA BlueField-4. This forward compatibility helps AI factories immediately handle gigascale demands, scaling up to 6X the compute power and doubling the bandwidth when BlueField-4 becomes available.

The inclusion of the Palo Alto Networks Prisma AIRS platform in the NVIDIA Enterprise AI Factory Validated Design bolsters enterprise AI security. By establishing the zero trust governance fabric of Prisma AIRS runtime security on NVIDIA BlueField, organizations gain a comprehensive defense. Proprietary and sensitive data is secured throughout the entire stack, and models are protected from adversarial threats, such as prompt injection attacks. With Prisma AIRS, the world's most comprehensive AI security platform, leaders gain the confidence to innovate and deploy AI bravely. This validated design is the essential blueprint for securely accelerating your market leadership without compromising security.

Join our "How to Secure the AI Factory" breakout session at NVIDIA GTC 2026, March 16-19, in San Jose, CA to hear more about this transformative solution and accelerate your AI innovation securely.

The post Palo Alto Networks Announces Support for NVIDIA Enterprise AI Factory appeared first on Palo Alto Networks Blog.

We recently handled a case where a customer reported strange SEO behavior on their website. Regular visitors saw a normal site. No popups. No redirects. No visible spam.

However, when they checked their site on Google, the search results were flooded with eBay-type-looking websites and “Situs Toto” gambling spam.

This is a professional-grade SEO cloaking attack. The malware turns the application into a double agent: it serves your genuine website content to real people but swaps it for a massive list of gambling ads the second a search engine bot crawls the page.

Continue reading Google Sees Spam, You See Your Site: A Cloaked SEO Spam Attack at Sucuri Blog.

Encountering the ERR_TOO_MANY_REDIRECTS error (also called a redirect loop error) can be frustrating, especially when your website was working fine just moments ago. This issue is common across browsers such as Chrome, Firefox, and Edge and it typically means your site has entered a redirection loop.

In this post, you’ll learn what the error means, why it occurs, ways to identify where the redirect is coming from, and how to fix it effectively – including an important section on redirect types, which often play a direct role in causing this issue.

Continue reading How to Fix the ERR_TOO_MANY_REDIRECTS Error at Sucuri Blog.

Kent Ickler & Jordan Drysdale // BHIS Webcast and Podcast This post accompanies BHIS’s webcast recorded on August 7, 2018, Active Directory Best Practices to Frustrate Attackers, which you can view below. […]

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