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Introduction:
Microsoft Defender for Cloud’s new “Blast Radius” feature represents a paradigm shift from reactive alerting to proactive risk assessment. By leveraging the power of the Microsoft Sentinel graph, it allows security teams to visualize and quantify the potential impact of a security compromise before it escalates into a full-blown incident. This capability is crucial for prioritizing remediation efforts based on the criticality of assets and their interconnectedness within a modern, hybrid cloud environment.
Learning Objectives:
- Understand the core concept of “Blast Radius” and its role in Attack Path Analysis.
- Learn how to navigate and interpret the Blast Radius visualization within Microsoft Defender for Cloud.
- Acquire the technical skills to leverage related KQL queries and security tools for deeper investigation.
You Should Know:
- Navigating the Blast Radius in Microsoft Defender for Cloud
The Blast Radius feature is integrated directly into the security alerts within Microsoft Defender for Cloud. When a resource is compromised, the Blast Radius visualization maps all interconnected assets, highlighting the potential propagation paths for an attacker.
Step‑by‑step guide:
- Log in to the Azure Portal and navigate to Microsoft Defender for Cloud.
- Go to the Security alerts page and select a high-severity alert, such as “Suspicious process executed on a resource.”
- In the alert details pane, locate and click on the “Blast Radius” tab.
- The interactive graph will load, showing the initially compromised resource at the center. Lines connecting to other assets represent potential attack paths.
- Click on any node (asset) in the graph to see its security recommendations and configuration details, allowing you to understand its vulnerability context.
2. KQL Query for Asset Criticality Scoring
While the GUI provides a visual, a Kusto Query Language (KQL) query can help you programmatically assess the criticality of assets within a potential blast radius based on their sensitivity and exposure.
Step‑by‑step guide:
SecurityAlert | where ProviderName contains "Defender" | extend CompromisedEntity = tostring(parse_json(Entities)[bash].Address) | join (SecurityRecommendation) on $left.CompromisedEntity == $right.Asset | where RecommendationName == "Virtual machines should be migrated to new Azure Resource Manager resources" | summarize CriticalRecommendations = dcount(RecommendationName) by CompromisedEntity | project CompromisedEntity, CriticalityScore = CriticalRecommendations | sort by CriticalityScore desc
This query:
- Starts with all security alerts from Defender (
SecurityAlert). - Parses the `Entities` field to extract the first compromised machine name.
- Performs a join with the `SecurityRecommendation` table to find all security recommendations for that specific asset.
- Filters for a specific, high-criticality recommendation (e.g., running on legacy ARM) as an example of a critical finding.
- Summarizes the count of these critical recommendations per compromised entity to generate a simple criticality score.
- Projects and sorts the results, showing the most critical assets at the top of the list.
3. PowerShell for Enumerating Resource Connections
To understand the blast radius, you must first map the resource connections. This PowerShell script uses the Az module to list all resources connected to a specific Virtual Network, a common attack path.
Step‑by‑step guide:
Connect to Azure Account
Connect-AzAccount
Define the Resource Group and Virtual Network
$resourceGroupName = "Your-RG-Name"
$vnetName = "Your-VNet-Name"
Get the VNet
$vnet = Get-AzVirtualNetwork -ResourceGroupName $resourceGroupName -Name $vnetName
Get all Network Interfaces in the VNet
$nicsInVnet = Get-AzNetworkInterface | Where-Object { $_.IpConfigurations.Subnet.Id -split "/"[-3] -eq $vnet.Name }
Get the VMs associated with those NICs
foreach ($nic in $nicsInVnet) {
if ($nic.VirtualMachine -ne $null) {
$vmId = $nic.VirtualMachine.Id
$vm = Get-AzResource -ResourceId $vmId
Write-Output "VM in VNet Blast Radius: $($vm.Name)"
}
}
This script:
1. Authenticates to your Azure tenant.
2. Defines the target Virtual Network.
3. Retrieves the specific VNet object.
- Gets all network interfaces that have IP configurations within the subnets of that VNet.
- Iterates through each NIC, checks if it’s attached to a Virtual Machine, and outputs the VM name, effectively mapping one layer of the blast radius.
4. Bash Script for On-Premises Network Segment Mapping
The blast radius concept also applies to on-premises infrastructure. This bash script uses `nmap` to discover active hosts and their open ports within a specific subnet.
Step‑by‑step guide:
!/bin/bash Define the target subnet SUBNET="192.168.1.0/24" Perform a ping sweep and TCP SYN scan on common ports nmap -sn $SUBNET -oG - | grep "Status: Up" | cut -d " " -f 2 > live_hosts.txt echo "Live hosts found:" cat live_hosts.txt echo "Scanning for open services on live hosts..." nmap -sS -p 22,80,443,135,139,445,3389 -iL live_hosts.txt -oN service_scan.txt echo "Scan complete. Results saved to service_scan.txt"
This script:
1. Defines the target IP subnet.
- Uses `nmap -sn` to perform a ping sweep and discover live hosts, saving their IPs to a file.
- Reads the list of live hosts and performs a TCP SYN scan (
-sS) on a set of common, critical ports (SSH, HTTP, HTTPS, RPC, SMB, RDP). - Outputs the results, providing a basic map of the network segment’s “blast radius” for a hypothetical initial compromise.
5. Azure CLI Command for Security Posture Assessment
A key part of reducing blast radius is hardening resources. This Azure CLI command quickly checks the secure score for a subscription, which is a direct measure of your security posture.
Step‑by‑step guide:
Set the active subscription (if you have multiple) az account set --subscription "Your-Subscription-Name-or-ID" Get the secure score from Microsoft Defender for Cloud az security secure-scores show --name "ascScore" --output table
This command:
- Ensures you are operating in the correct Azure subscription.
- Queries the `ascScore` resource, which is the overall secure score for the subscription.
- The output in table format gives a high-level percentage, indicating how many of the recommended security controls you have implemented. A low score implies a larger potential blast radius for any attack.
6. KQL Hunt for Lateral Movement Potential
Once an initial compromise occurs, attackers seek to move laterally. This hunting query identifies logon events from a potentially compromised source IP to multiple different hosts, a key indicator of lateral movement.
Step‑by‑step guide:
SecurityEvent | where EventID == 4624 // Successful Logon | where SubjectLogonId == "0x3e7" // Filter for network logons (or adjust as needed) | where IpAddress startswith "10." // Focus on internal RFC1918 IPs | summarize UniqueTargetMachines = dcount(Computer), TargetList = make_set(Computer) by IpAddress | where UniqueTargetMachines > 5 // Alert if a single IP logs into more than 5 unique machines | project SuspiciousIP = IpAddress, NumberOfMachinesTargeted = UniqueTargetMachines, MachinesTargeted = TargetList
This query:
- Filters Windows Security Events for successful logons (Event ID 4624).
- Focuses on network logons (Logon Type 3, often represented by `SubjectLogonId` “0x3e7” in some schemas; adjust for your environment).
3. Filters for internal IP addresses.
- Summarizes the data by source IP address, counting the number of unique target machines and creating a list of them.
- Flags any source IP that has successfully logged into more than 5 unique machines, which could indicate credential reuse and lateral movement attempts, expanding the blast radius.
-
Mitigating Blast Radius with NSG Flow Logs Analysis
Network Security Groups (NSGs) are primary controls for segmenting networks and containing blast radius. Analyzing their flow logs can reveal unintended and potentially dangerous allowed traffic.
Step‑by‑step guide:
AzureNetworkAnalytics_CL
| where FlowType_s == "AllowedFlow"
| where DestPort_d == 445 // SMB port, commonly used for lateral movement and ransomware
| where SrcIP_s !in ('168.63.129.16') // Azure's metadata service IP
| summarize TotalBytes=sum(Bytes_s), FlowCount=count() by SrcIP_s, DestIP_s, DestPort_d
| sort by TotalBytes desc
This query (for NSG Flow Logs sent to a Log Analytics workspace):
1. Queries the `AzureNetworkAnalytics_CL` table for allowed flows.
- Focuses on traffic to a critical port like 445 (SMB), which is a common vector for lateral movement and ransomware propagation.
3. Filters out known, benign Azure infrastructure IPs.
- Summarizes the total bytes and flow count by source IP, destination IP, and destination port.
- Sorting by total bytes helps identify the most active, and potentially risky, SMB connections that should be investigated for necessity, as they significantly widen the blast radius.
What Undercode Say:
- Context is King: The Blast Radius feature is not just a map; it’s a contextual risk calculator. Its true value lies in overlaying asset criticality, existing vulnerabilities, and security controls onto the connection graph.
- Shift-Left for Defense: This tool enables a “shift-left” mentality for defenders, allowing them to identify and sever critical attack paths before an incident occurs, fundamentally changing security from a reactive to a proactive discipline.
The introduction of Blast Radius analysis marks a significant evolution in cloud-native security tools. It moves beyond siloed alerts and empowers analysts to think like an attacker, visualizing the entire kill chain from a single entry point. The ultimate goal is not just to see how big a breach could be, but to actively shrink that potential surface through targeted hardening and segmentation. By integrating this visualization with automated scripts and queries for asset criticality and network analysis, security teams can systematically reduce their organization’s overall risk profile.
Prediction:
The integration of graph-based Blast Radius analysis will become the standard for all major cloud security platforms within two years. This technology will rapidly evolve, incorporating AI to not only map existing paths but also to predict future attack paths based on emergent attacker TTPs (Tactics, Techniques, and Procedures). This will give rise to fully automated “security posture simulation” engines, allowing defenders to stress-test their environments against hypothetical compromises and continuously optimize their defenses against the most likely and most damaging attack scenarios, effectively allowing them to win the fight before it even begins.
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IT/Security Reporter URL:
Reported By: Fisherandrea What – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
