Today we are announcing the general availability of Amazon Lightsail for Research, a new offering that makes it easy for researchers and students to create and manage a high-performance CPU or a GPU research computer in just a few clicks on the cloud. You can use your preferred integrated development environments (IDEs) like preinstalled Jupyter, RStudio, Scilab, VSCodium, or native Ubuntu operating system on your research computer.
You no longer need to use your own research laptop or shared school computers for analyzing larger datasets or running complex simulations. You can create your own research environments and directly access the application running on the research computer remotely via a web browser. Also, you can easily upload data to and download from your research computer via a simple web interface.
You pay only for the duration the computers are in use and can delete them at any time. You can also use budgeting controls that can automatically stop your computer when it’s not in use. Lightsail for Research also includes all-inclusive prices of compute, storage, and data transfer, so you know exactly how much you will pay for the duration you use the research computer.
Get Started with Amazon Lightsail for Research To get started, navigate to the Lightsail for Research console, and choose Virtual computers in the left menu. You can see my research computers naming “channy-jupyter” or “channy-rstudio” already created.
Choose Create virtual computer to create a new research computer, and select which software you’d like preinstalled on your computer and what type of research computer you’d like to create.
In the first step, choose the application you want installed on your computer and the AWS Region to be located in. We support Jupyter, RStudio, Scilab, and VSCodium. You can install additional packages and extensions through the interface of these IDE applications.
Next, choose the desired virtual hardware type, including a fixed amount of compute (vCPUs or GPUs), memory (RAM), SSD-based storage volume (disk) space, and a monthly data transfer allowance. Bundles are charged on an hourly and on-demand basis.
Standard types are compute-optimized and ideal for compute-bound applications that benefit from high-performance processors.
Monthly data transfer allowance*
GPU types provide a high-performance platform for general-purpose GPU computing. You can use these bundles to accelerate scientific, engineering, and rendering applications and workloads.
Monthly data transfer allowance*
* AWS created the Global Data Egress Waiver (GDEW) program to help eligible researchers and academic institutions use AWS services by waiving data egress fees. To learn more, see the blog post.
After making your selections, name your computer and choose Create virtual computer to create your research computer. Once your computer is created and running, choose the Launch application button to open a new window that will display the preinstalled application you selected.
Lightsail for Research Features As with existing Lightsail instances, you can create additional block-level storage volumes (disks) that you can attach to a running Lightsail for Research virtual computer. You can use a disk as a primary storage device for data that requires frequent and granular updates. To create your own storage, choose Storage and Create disk.
You can also create Snapshots, a point-in-time copy of your data. You can create a snapshot of your Lightsail for Research virtual computers and use it as baselines to create new computers or for data backup. A snapshot contains all of the data that is needed to restore your computer from the moment when the snapshot was taken.
When you restore a computer by creating it from a snapshot, you can easily create a new one or upgrade your computer to a larger size using a snapshot backup. Create snapshots frequently to protect your data from corrupt applications or user errors.
You can use Cost control rules that you define to help manage the usage and cost of your Lightsail for Research virtual computers. You can create rules that stop running computers when average CPU utilization over a selected time period falls below a prescribed level.
For example, you can configure a rule that automatically stops a specific computer when its CPU utilization is equal to or less than 1 percent for a 30-minute period. Lightsail for Research will then automatically stop the computer so that you don’t incur charges for running computers.
In the Usage menu, you can view the cost estimate and usage hours for your resources during a specified time period.
Now Available Amazon Lightsail for Research is now available in the US East (Ohio), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Paris), Europe (Stockholm), and Europe (Sweden) Regions.
Tweet VMware Skyline Advisor Pro releases new proactive Findings every month. Findings are prioritized by trending issues in VMware Technical Support, issues raised through post escalation review, security vulnerabilities, issues raised from VMware engineering, and nominated by customers. For the month of February, we released 56 new Findings. Of these, there are 19 Findings based … Continued
A couple days ago, I had the honor of doing a live stream on generative AI, discussing recent innovations and concepts behind the current generation of large language and vision models and how we got there. In today’s roundup of news and announcements, I will share some additional information—including an expanded partnership to make generative AI more accessible, a blog post about diffusion models, and our weekly Twitch show on Generative AI. Let’s dive right into it!
Last Week’s Launches Here are some launches that got my attention during the previous week:
AWS Glue Crawlers – Now integrate with Lake Formation. AWS Glue Crawlers are used to discover datasets, extract schema information, and populate the AWS Glue Data Catalog. With this Glue Crawler and Lake Formation integration, you can configure a crawler to use Lake Formation permissions to access an S3 data store or a Data Catalog table with an underlying S3 location within the same AWS account or another AWS account. You can configure an existing Data Catalog table as a crawler’s target if the crawler and the Data Catalog table reside in the same account. To learn more, check out this Big Data Blog post.
Amazon SageMaker Model Monitor – You can now launch and configure Amazon SageMaker Model Monitor from the SageMaker Model Dashboard using a code-free point-and-click setup experience. SageMaker Model Dashboard gives you unified monitoring across all your models by providing insights into deviations from expected behavior, automated alerts, and troubleshooting to improve model performance. Model Monitor can detect drift in data quality, model quality, bias, and feature attribution and alert you to take remedial actions when such changes occur.
Amazon EKS – Now supports Kubernetes version 1.25. Kubernetes 1.25 introduced several new features and bug fixes, and you can now use Amazon EKS and Amazon EKS Distro to run Kubernetes version 1.25. You can create new 1.25 clusters or upgrade your existing clusters to 1.25 using the Amazon EKS console, the eksctl command line interface, or through an infrastructure-as-code tool. To learn more about this release named “Combiner,” check out this Containers Blog post.
Amazon Detective –New self-paced workshop available. You can now learn to use Amazon Detective with a new self-paced workshop in AWS Workshop Studio. AWS Workshop Studio is a collection of self-paced tutorials designed to teach practical skills and techniques to solve business problems. The Amazon Detective workshop is designed to teach you how to use the primary features of Detective through a series of interactive modules that cover topics such as security alert triage, security incident investigation, and threat hunting. Get started with the Amazon Detective Workshop.
Other AWS News Here are some additional news items and blog posts that you may find interesting:
AWS and Hugging Face collaborate to make generative AI more accessible and cost-efficient – This previous week, we announced an expanded collaboration between AWS and Hugging Face to accelerate the training, fine-tuning, and deployment of large language and vision models used to create generative AI applications. Generative AI applications can perform a variety of tasks, including text summarization, answering questions, code generation, image creation, and writing essays and articles. For more details, read this Machine Learning Blog post.
If you are interested in generative AI, I also recommend reading this blog post on how to Fine-tune text-to-image Stable Diffusion models with Amazon SageMaker JumpStart. Stable Diffusion is a deep learning model that allows you to generate realistic, high-quality images and stunning art in just a few seconds. This blog post discusses how to make design choices, including dataset quality, size of training dataset, choice of hyperparameter values, and applicability to multiple datasets.
AWS open-source news and updates – My colleague Ricardo writes this weekly open-source newsletter in which he highlights new open-source projects, tools, and demos from the AWS Community. Read edition #146 here.
Upcoming AWS Events Check your calendars and sign up for these AWS events:
#BuildOn Generative AI – Join our weekly live Build On Generative AI Twitch show. Every Monday morning, 9:00 US PT, my colleagues Emily and Darko take a look at aspects of generative AI. They host developers, scientists, startup founders, and AI leaders and discuss how to build generative AI applications on AWS.
In today’s episode, my colleague Chris walked us through an end-to-end ML pipeline from data ingestion to fine-tuning and deployment of generative AI models. You can watch the video here.
AWS Pi Day – Join me on March 14 for the third annual AWS Pi Day live, virtual event hosted on the AWS On Air channel on Twitch as we celebrate the 17th birthday of Amazon S3 and the cloud.
We will discuss the latest innovations across AWS Data services, from storage to analytics and AI/ML. If you are curious about how AI can transform your business, register here and join my session.
AWS Innovate Data and AI/ML edition – AWS Innovate is a free online event to learn the latest from AWS experts and get step-by-step guidance on using AI/ML to drive fast, efficient, and measurable results. Register now for EMEA (March 9) and the Americas (March 14).
I've known the CrypTool website for many years, I use it occasioanly when I need to do some crypto and I only have a browser at my disposal. Lately, I'm more inclined to use CyberChef, as it provides also many non-crypto features.
The Cybersecurity and Infrastructure Security Agency (CISA) is releasing this Cybersecurity Advisory (CSA) detailing activity and key findings from a recent CISA red team assessment—in coordination with the assessed organization—to provide network defenders recommendations for improving their organization’s cyber posture.
Actions to take today to harden your local environment:
Establish a security baseline of normal network activity; tune network and host-based appliances to detect anomalous behavior.
Conduct regular assessments to ensure appropriate procedures are created and can be followed by security staff and end users.
In 2022, CISA conducted a red team assessment (RTA) at the request of a large critical infrastructure organization with multiple geographically separated sites. The team gained persistent access to the organization’s network, moved laterally across the organization’s multiple geographically separated sites, and eventually gained access to systems adjacent to the organization’s sensitive business systems (SBSs). Multifactor authentication (MFA) prompts prevented the team from achieving access to one SBS, and the team was unable to complete its viable plan to compromise a second SBSs within the assessment period.
Despite having a mature cyber posture, the organization did not detect the red team’s activity throughout the assessment, including when the team attempted to trigger a security response.
CISA is releasing this CSA detailing the red team’s tactics, techniques, and procedures (TTPs) and key findings to provide network defenders of critical infrastructure organizations proactive steps to reduce the threat of similar activity from malicious cyber actors. This CSA highlights the importance of collecting and monitoring logs for unusual activity as well as continuous testing and exercises to ensure your organization’s environment is not vulnerable to compromise, regardless of the maturity of its cyber posture.
CISA encourages critical infrastructure organizations to apply the recommendations in the Mitigations section of this CSA—including conduct regular testing within their security operations center—to ensure security processes and procedures are up to date, effective, and enable timely detection and mitigation of malicious activity.
Note: This advisory uses the MITRE ATT&CK® for Enterprise framework, version 12. See the appendix for a table of the red team’s activity mapped to MITRE ATT&CK tactics and techniques.
CISA has authority to, upon request, provide analyses, expertise, and other technical assistance to critical infrastructure owners and operators and provide operational and timely technical assistance to Federal and non-Federal entities with respect to cybersecurity risks. (See generally 6 U.S.C. §§ 652[c], 659[c].) After receiving a request for a red team assessment (RTA) from an organization and coordinating some high-level details of the engagement with certain personnel at the organization, CISA conducted the RTA over a three-month period in 2022.
During RTAs, a CISA red team emulates cyber threat actors to assess an organization’s cyber detection and response capabilities. During Phase I, the red team attempts to gain and maintain persistent access to an organization’s enterprise network while avoiding detection and evading defenses. During Phase II, the red team attempts to trigger a security response from the organization’s people, processes, or technology.
The “victim” for this assessment was a large organization with multiple geographically separated sites throughout the United States. For this assessment, the red team’s goal during Phase I was to gain access to certain sensitive business systems (SBSs).
Phase I: Red Team Cyber Threat Activity
The organization’s network was segmented with both logical and geographical boundaries. CISA’s red team gained initial access to two organization workstations at separate sites via spearphishing emails. After gaining access and leveraging Active Directory (AD) data, the team gained persistent access to a third host via spearphishing emails. From that host, the team moved laterally to a misconfigured server, from which they compromised the domain controller (DC). They then used forged credentials to move to multiple hosts across different sites in the environment and eventually gained root access to all workstations connected to the organization’s mobile device management (MDM) server. The team used this root access to move laterally to SBS-connected workstations. However, a multifactor authentication (MFA) prompt prevented the team from achieving access to one SBS, and Phase I ended before the team could implement a seemingly viable plan to achieve access to a second SBS.
Initial Access and Active Directory Discovery
The CISA red team gained initial access [TA0001] to two workstations at geographically separated sites (Site 1 and Site 2) via spearphishing emails. The team first conducted open-source research [TA0043] to identify potential targets for spearphishing. Specifically, the team looked for email addresses [T1589.002] as well as names [T1589.003] that could be used to derive email addresses based on the team’s identification of the email naming scheme. The red team sent tailored spearphishing emails to seven targets using commercially available email platforms [T1585.002]. The team used the logging and tracking features of one of the platforms to analyze the organization’s email filtering defenses and confirm the emails had reached the target’s inbox.
The team built a rapport with some targeted individuals through emails, eventually leading these individuals to accept a virtual meeting invite. The meeting invite took them to a red team-controlled domain [T1566.002] with a button, which, when clicked, downloaded a “malicious” ISO file [T1204]. After the download, another button appeared, which, when clicked, executed the file.
Two of the seven targets responded to the phishing attempt, giving the red team access to a workstation at Site 1 (Workstation 1) and a workstation at Site 2. On Workstation 1, the team leveraged a modified SharpHound collector, ldapsearch, and command-line tool, dsquery, to query and scrape AD information, including AD users [T1087.002], computers [T1018], groups [T1069.002], access control lists (ACLs), organizational units (OU), and group policy objects (GPOs) [T1615]. Note: SharpHound is a BloodHound collector, an open-source AD reconnaissance tool. Bloodhound has multiple collectors that assist with information querying.
There were 52 hosts in the AD that had Unconstrained Delegation enabled and a lastlogon timestamp within 30 days of the query. Hosts with Unconstrained Delegation enabled store Kerberos ticket-granting tickets (TGTs) of all users that have authenticated to that host. Many of these hosts, including a Site 1 SharePoint server, were Windows Server 2012R2. The default configuration of Windows Server 2012R2 allows unprivileged users to query group membership of local administrator groups.
The red team queried parsed Bloodhound data for members of the SharePoint admin group and identified several standard user accounts with administrative access. The team initiated a second spearphishing campaign, similar to the first, to target these users. One user triggered the red team’s payload, which led to installation of a persistent beacon on the user’s workstation (Workstation 2), giving the team persistent access to Workstation 2.
Lateral Movement, Credential Access, and Persistence
The red team moved laterally [TA0008] from Workstation 2 to the Site 1 SharePoint server and had SYSTEM level access to the Site 1 SharePoint server, which had Unconstrained Delegation enabled. They used this access to obtain the cached credentials of all logged-in users—including the New Technology Local Area Network Manager (NTLM) hash for the SharePoint server account. To obtain the credentials, the team took a snapshot of lsass.exe [T1003.001] with a tool called nanodump, exported the output, and processed the output offline with Mimikatz.
The team then exploited the Unconstrained Delegation misconfiguration to steal the DC’s TGT. They ran the DFSCoerce python script (DFSCoerce.py), which prompted DC authentication to the SharePoint server using the server’s NTLM hash. The team then deployed Rubeus to capture the incoming DC TGT [T1550.002], [T1557.001]. (DFSCoerce abuses Microsoft’s Distributed File System [MS-DFSNM] protocol to relay authentication against an arbitrary server.)
The team then used the TGT to harvest advanced encryption standard (AES)-256 hashes via DCSync [T1003.006] for the krbtgt account and several privileged accounts—including domain admins, workstation admins, and a system center configuration management (SCCM) service account (SCCM Account 1). The team used the krbtgt account hash throughout the rest of their assessment to perform golden ticket attacks [T1558.001] in which they forged legitimate TGTs. The team also used the asktgt command to impersonate accounts they had credentials for by requesting account TGTs [T1550.003].
The team first impersonated the SCCM Account 1 and moved laterally to a Site 1 SCCM distribution point (DP) server (SCCM Server 1) that had direct network access to Workstation 2. The team then moved from SCCM Server 1 to a central SCCM server (SCCM Server 2) at a third site (Site 3). Specifically, the team:
Queried the AD using Lightweight Directory Access Protocol (LDAP) for information about the network’s sites and subnets [T1016]. This query revealed all organization sites and subnets broken down by classless inter-domain routing (CIDR) subnet and description.
Used LDAP queries and domain name system (DNS) requests to identify recently active hosts.
Listed existing network connections [T1049] on SCCM Server 1, which revealed an active Server Message Block (SMB) connection from SCCM Server 2.
Attempted to move laterally to the SCCM Server 2 via AppDomain hijacking, but the HTTPS beacon failed to call back.
Attempted to move laterally with an SMB beacon [T1021.002], which was successful.
The team also moved from SCCM Server 1 to a Site 1 workstation (Workstation 3) that housed an active server administrator. The team impersonated an administrative service account via a golden ticket attack (from SCCM Server 1); the account had administrative privileges on Workstation 3. The user employed a KeePass password manager that the team was able to use to obtain passwords for other internal websites, a kernel-based virtual machine (KVM) server, virtual private network (VPN) endpoints, firewalls, and another KeePass database with credentials. The server administrator relied on a password manager, which stored credentials in a database file. The red team pulled the decryption key from memory using KeeThief and used it to unlock the database [T1555.005].
At the organization’s request, the red team confirmed that SCCM Server 2 provided access to the organization’s sites because firewall rules allowed SMB traffic to SCCM servers at all other sites.
The team moved laterally from SCCM Server 2 to an SCCM DP server at Site 5 and from the SCCM Server 1 to hosts at two other sites (Sites 4 and 6). The team installed persistent beacons at each of these sites. Site 5 was broken into a private and a public subnet and only DCs were able to cross that boundary. To move between the subnets, the team moved through DCs. Specifically, the team moved from the Site 5 SCCM DP server to a public DC; and then they moved from the public DC to the private DC. The team was then able to move from the private DC to workstations in the private subnet.
The team leveraged access available from SCCM 2 to move around the organization’s network for post-exploitation activities (See Post-Exploitation Activity section).
See Figure 1 for a timeline of the red team’s initial access and lateral movement showing key access points.
While traversing the network, the team varied their lateral movement techniques to evade detection and because the organization had non-uniform firewalls between the sites and within the sites (within the sites, firewalls were configured by subnet). The team’s primary methods to move between sites were AppDomainManager hijacking and dynamic-link library (DLL) hijacking [T1574.001]. In some instances, they used Windows Management Instrumentation (WMI) Event Subscriptions [T1546.003].
The team impersonated several accounts to evade detection while moving. When possible, the team remotely enumerated the local administrators group on target hosts to find a valid user account. This technique relies on anonymous SMB pipe binds [T1071], which are disabled by default starting with Windows Server 2016. In other cases, the team attempted to determine valid accounts based on group name and purpose. If the team had previously acquired the credentials, they used asktgt to impersonate the account. If the team did not have the credentials, they used the golden ticket attack to forge the account.
Post-Exploitation Activity: Gaining Access to SBSs
With persistent, deep access established across the organization’s networks and subnetworks, the red team began post-exploitation activities and attempted to access SBSs. Trusted agents of the organization tasked the team with gaining access to two specialized servers (SBS 1 and SBS 2). The team achieved root access to three SBS-adjacent workstations but was unable to move laterally to the SBS servers:
Phase I ended before the team could implement a plan to move to SBS 1.
An MFA prompt blocked the team from moving to SBS 2, and Phase I ended before they could implement potential workarounds.
However, the team assesses that by using Secure Shell (SSH) session socket files (see below), they could have accessed any hosts available to the users whose workstations were compromised.
Plan for Potential Access to SBS 1
Conducting open-source research [1591.001], the team identified that SBS 1 and 2 assets and associated management/upkeep staff were located at Sites 5 and 6, respectively. Adding previously collected AD data to this discovery, the team was able to identify a specific SBS 1 admin account. The team planned to use the organization’s mobile device management (MDM) software to move laterally to the SBS 1 administrator’s workstation and, from there, pivot to SBS 1 assets.
The team identified the organization’s MDM vendor using open-source and AD information [T1590.006] and moved laterally to an MDM distribution point server at Site 5 (MDM DP 1). This server contained backups of the MDM MySQL database on its D: drive in the Backup directory. The backups included the encryption key needed to decrypt any encrypted values, such as SSH passwords [T1552]. The database backup identified both the user of the SBS 1 administrator account (USER 2) and the user’s workstation (Workstation 4), which the MDM software remotely administered.
The team moved laterally to an MDM server (MDM 1) at Site 3, searched files on the server, and found plaintext credentials [T1552.001] to an application programming interface (API) user account stored in PowerShell scripts. The team attempted to leverage these credentials to browse to the web login page of the MDM vendor but were unable to do so because the website directed to an organization-controlled single-sign on (SSO) authentication page.
The team gained root access to workstations connected to MDM 1—specifically, the team accessed Workstation 4—by:
Selecting an MDM user from the plaintext credentials in PowerShell scripts on MDM 1.
While in the MDM MySQL database,
Elevating the selected MDM user’s account privileges to administrator privileges, and
Modifying the user’s account by adding Create Policy and Delete Policy permissions [T1098], [T1548].
Creating a policy via the MDM API [T1106], which instructed Workstation 4 to download and execute a payload to give the team interactive access as root to the workstation.
Verifying their interactive access.
Resetting permissions back to their original state by removing the policy via the MDM API and removing Create Policy and Delete Policy and administrator permissions and from the MDM user’s account.
While interacting with Workstation 4, the team found an open SSH socket file and a corresponding netstat connection to a host that the team identified as a bastion host from architecture documentation found on Workstation 4. The team planned to move from Workstation 4 to the bastion host to SBS 1. Note: A SSH socket file allows a user to open multiple SSH sessions through a single, already authenticated SSH connection without additional authentication.
The team could not take advantage of the open SSH socket. Instead, they searched through SBS 1 architecture diagrams and documentation on Workstation 4. They found a security operations (SecOps) network diagram detailing the network boundaries between Site 5 SecOps on-premises systems, Site 5 non-SecOps on-premises systems, and Site 5 SecOps cloud infrastructure. The documentation listed the SecOps cloud infrastructure IP ranges [T1580]. These “trusted” IP addresses were a public /16 subnet; the team was able to request a public IP in that range from the same cloud provider, and Workstation 4 made successful outbound SSH connections to this cloud infrastructure. The team intended to use that connection to reverse tunnel traffic back to the workstation and then access the bastion host via the open SSH socket file. However, Phase 1 ended before they were able to implement this plan.
Attempts to Access SBS 2
Conducting open-source research, the team identified an organizational branch [T1591] that likely had access to SBS 2. The team queried the AD to identify the branch’s users and administrators. The team gathered a list of potential accounts, from which they identified administrators, such as SYSTEMS ADMIN or DATA SYSTEMS ADMINISTRATOR, with technical roles. Using their access to the MDM MySQL database, the team queried potential targets to (1) determine the target’s last contact time with the MDM and (2) ensure any policy targeting the target’s workstation would run relatively quickly [T1596.005]. Using the same methodology as described by the steps in the Plan for Potential Access to SBS 1 section above, the team gained interactive root access to two Site 6 SBS 2-connected workstations: a software engineering workstation (Workstation 5) and a user administrator workstation (Workstation 6).
The Workstation 5 user had bash history files with what appeared to be SSH passwords mistyped into the bash prompt and saved in bash history [T1552.003]. The team then attempted to authenticate to SBS 2 using a similar tunnel setup as described in the Access to SBS 1 section above and the potential credentials from the user’s bash history file. However, this attempt was unsuccessful for unknown reasons.
On Workstation 6, the team found a .txt file containing plaintext credentials for the user. Using the pattern discovered in these credentials, the team was able to crack the user’s workstation account password [T1110.002]. The team also discovered potential passwords and SSH connection commands in the user’s bash history. Using a similar tunnel setup described above, the team attempted to log into SBS 2. However, a prompt for an MFA passcode blocked this attempt.
See figure 2 for a timeline of the team’s post exploitation activity that includes key points of access.
Command and Control
The team used third-party owned and operated infrastructure and services [T1583] throughout their assessment, including in certain cases for command and control (C2) [TA0011]. These included:
Cobalt Strike and Merlin payloads for C2 throughout the assessment. Note: Merlin is a post-exploit tool that leverages HTTP protocols for C2 traffic.
The team maintained multiple Cobalt Strike servers hosted by a cloud vendor. They configured each server with a different domain and used the servers for communication with compromised hosts. These servers retained all assessment data.
Two commercially available cloud-computing platforms.
The team used these platforms to create flexible and dynamic redirect servers to send traffic to the team’s Cobalt Strike servers [T1090.002]. Redirecting servers make it difficult for defenders to attribute assessment activities to the backend team servers. The redirectors used HTTPS reverse proxies to redirect C2 traffic between the target organization’s network and the Cobalt Strike team servers [T1071.002]. The team encrypted all data in transit [T1573] using encryption keys stored on team’s Cobalt Strike servers.
A cloud service to rapidly change the IP address of the team’s redirecting servers in the event of detection and eradication.
Content delivery network (CDN) services to further obfuscate some of the team’s C2 traffic.
This technique leverages CDNs associated with high-reputation domains so that the malicious traffic appears to be directed towards a reputation domain but is actually redirected to the red team-controlled Cobalt Strike servers.
The team used domain fronting [T1090.004] to disguise outbound traffic in order to diversify the domains with which the persistent beacons were communicating. This technique, which also leverages CDNs, allows the beacon to appear to connect to third-party domains, such as nytimes.com, when it is actually connecting to the team’s redirect server.
Phase II: Red Team Measurable Events Activity
The red team executed 13 measurable events designed to provoke a response from the people, processes, and technology defending the organization’s network. See Table 1 for a description of the events, the expected network defender activity, and the organization’s actual response.
Table 1: Measurable Events
MITRE ATT&CK Technique(s)
Expected Detection Points
Expected Network Defender Reactions
Internal Port Scan
Launch scan from inside the network from a previously gained workstation to enumerate ports on target workstation, server, and domain controller system(s).
Comprehensive Active Directory and Host Enumeration
Perform AD enumeration by querying all domain objects from the DC; and enumerating trust relationships within the AD Forest, user accounts, and current session information from every domain computer (Workstation and Server).
Detect and identify source IP and source process of malicious traffic
Investigate destination IP address
Triage compromised host
Develop response plan
Malicious file was removed by antivirus
Execute simulated ransomware on multiple Workstation systems to simulate a ransomware attack.
Note: This technique does NOT encrypt files on the target system.
End User Reporting
Investigate end user reported event
Triage compromised host
Develop response Plan
Four users reported event to defensive staff
The red team noted the following key issues relevant to the security of the organization’s network. These findings contributed to the team’s ability to gain persistent, undetected access across the organization’s sites. See the Mitigations section for recommendations on how to mitigate these issues.
Insufficient host and network monitoring. Most of the red team’s Phase II actions failed to provoke a response from the people, processes, and technology defending the organization’s network. The organization failed to detect lateral movement, persistence, and C2 activity via their intrusion detection or prevention systems, endpoint protection platform, web proxy logs, and Windows event logs. Additionally, throughout Phase I, the team received no deconflictions or confirmation that the organization caught their activity. Below is a list of some of the higher risk activities conducted by the team that were opportunities for detection:
Lateral movement reuse
Generation and use of the golden ticket
Anomalous LDAP traffic
Anomalous internal share enumeration
Unconstrained Delegation server compromise
Anomalous account usage during lateral movement
Anomalous outbound network traffic
Anomalous outbound SSH connections to the team’s cloud servers from workstations
Lack of monitoring on endpoint management systems. The team used the organization’s MDM system to gain root access to machines across the organization’s network without being detected. Endpoint management systems provide elevated access to thousands of hosts and should be treated as high value assets (HVAs) with additional restrictions and monitoring.
KRBTGT never changed. The Site 1 krbtgt account password had not been updated for over a decade. The krbtgt account is a domain default account that acts as a service account for the key distribution center (KDC) service used to encrypt and sign all Kerberos tickets for the domain. Compromise of the krbtgt account could provide adversaries with the ability to sign their own TGTs, facilitating domain access years after the date of compromise. The red team was able to use the krbtgt account to forge TGTs for multiple accounts throughout Phase I.
Excessive permissions to standard users. The team discovered several standard user accounts that have local administrator access to critical servers. This misconfiguration allowed the team to use the low-level access of a phished user to move laterally to an Unconstrained Delegation host and compromise the entire domain.
Hosts with Unconstrained Delegation enabled unnecessarily. Hosts with Unconstrained Delegation enabled store the Kerberos TGTs of all users that authenticate to that host, enabling actors to steal service tickets or compromise krbtgt accounts and perform golden ticket or “silver ticket” attacks. The team performed an NTLM-relay attack to obtain the DC’s TGT, followed by a golden ticket attack on a SharePoint server with Unconstrained Delegation to gain the ability to impersonate any Site 1 AD account.
Use of non-secure default configurations. The organization used default configurations for hosts with Windows Server 2012 R2. The default configuration allows unprivileged users to query group membership of local administrator groups. The red team used and identified several standard user accounts with administrative access from a Windows Server 2012 R2 SharePoint server.
The team noted the following additional issues.
Ineffective separation of privileged accounts. Some workstations allowed unprivileged accounts to have local administrator access; for example, the red team discovered an ordinary user account in the local admin group for the SharePoint server. If a user with administrative access is compromised, an actor can access servers without needing to elevate privileges. Administrative and user accounts should be separated, and designated admin accounts should be exclusively used for admin purposes.
Lack of server egress control. Most servers, including domain controllers, allowed unrestricted egress traffic to the internet.
Inconsistent host configuration. The team observed inconsistencies on servers and workstations within the domain, including inconsistent membership in the local administrator group among different servers or workstations. For example, some workstations had “Server Admins” or “Domain Admins” as local administrators, and other workstations had neither.
Potentially unwanted programs. The team noticed potentially unusual software, including music software, installed on both workstations and servers. These extraneous software installations indicate inconsistent host configuration (see above) and increase the attack surfaces for malicious actors to gain initial access or escalate privileges once in the network.
Mandatory password changes enabled. During the assessment, the team keylogged a user during a mandatory password change and noticed that only the final character of their password was modified. This is potentially due to domain passwords being required to be changed every 60 days.
Smart card use was inconsistent across the domain. While the technology was deployed, it was not applied uniformly, and there was a significant portion of users without smartcard protections enabled. The team used these unprotected accounts throughout their assessment to move laterally through the domain and gain persistence.
The red team noted the following technical controls or defensive measures that prevented or hampered offensive actions:
The organization conducts regular, proactive penetration tests and adversarial assessments and invests in hardening their network based on findings.
The team was unable to discover any easily exploitable services, ports, or web interfaces from more than three million external in-scope IPs. This forced the team to resort to phishing to gain initial access to the environment.
Service account passwords were strong. The team was unable to crack any of the hashes obtained from the 610 service accounts pulled. This is a critical strength because it slowed the team from moving around the network in the initial parts of the Phase I.
The team did not discover any useful credentials on open file shares or file servers. This slowed the progress of the team from moving around the network.
MFA was used for some SBSs. The team was blocked from moving to SBS 2 by an MFA prompt.
There were strong security controls and segmentation for SBS systems. Direct access to SBS were located in separate networks, and admins of SBS used workstations protected by local firewalls.
CISA recommends organizations implement the recommendations in Table 2 to mitigate the issues listed in the Findings section of this advisory. These mitigations align with the Cross-Sector Cybersecurity Performance Goals (CPGs) developed by CISA and the National Institute of Standards and Technology (NIST). The CPGs provide a minimum set of practices and protections that CISA and NIST recommend all organizations implement. CISA and NIST based the CPGs on existing cybersecurity frameworks and guidance to protect against the most common and impactful threats, tactics, techniques, and procedures. See CISA’s Cross-Sector Cybersecurity Performance Goals for more information on the CPGs, including additional recommended baseline protections.
Table 2: Recommendations to Mitigate Identified Issues
Insufficient host and network monitoring
Establish a security baseline of normal network traffic and tune network appliances to detect anomalous behavior [CPG 3.1]. Tune host-based products to detect anomalous binaries, lateral movement, and persistence techniques.
Create alerts for Windows event log authentication codes, especially for the domain controllers. This could help detect some of the pass-the-ticket, DCSync, and other techniques described in this report.
From a detection standpoint, focus on identity and access management (IAM) rather than just network traffic or static host alerts.
Consider who is accessing what (what resource), from where (what internal host or external location), and when (what day and time the access occurs).
Look for access behavior that deviates from expected or is indicative of AD abuse.
Reduce the attack surface by limiting the use of legitimate administrative pathways and tools such as PowerShell, PSExec, and WMI, which are often used by malicious actors. CISA recommends selecting one tool to administer the network, ensuring logging is turned on [CPG 3.1], and disabling the others.
Consider using “honeypot” service principal names (SPNs) to detect attempts to crack account hashes [CPG 1.1].
Conduct regular assessments to ensure processes and procedures are up to date and can be followed by security staff and end users.
Consider using red team tools, such as SharpHound, for AD enumeration to identify users with excessive privileges and misconfigured hosts (e.g., with Unconstrained Delegation enabled).
Ensure all commercial tools deployed in your environment are regularly tuned to pick up on relevant activity in your environment.
Lack of monitoring on endpoint management systems
Treat endpoint management systems as HVAs with additional restrictions and monitoring because they provide elevated access to thousands of hosts.
KRBTGT never changed
Change the krbtgt account password on a regular schedule such as every 6 to 12 months or if it becomes compromised. Note that this password change must be carefully performed to effectively change the credential without breaking AD functionality. The password must be changed twice to effectively invalidate the old credentials. However, the required waiting period between resets must be greater than the maximum lifetime period of Kerberos tickets, which is 10 hours by default. See Microsoft’s KRBTGT account maintenance considerations guidance for more information.
Excessive permissions to standard users and ineffective separation of privileged accounts
Implement the principle of least privilege:
Grant standard user rights for standard user tasks such as email, web browsing, and using line-of-business (LOB) applications.
Periodically audit standard accounts and minimize where they have privileged access.
Periodically Audit AD permissions to ensure users do not have excessive permissions and have not been added to admin groups.
Evaluate which administrative groups should administer which servers/workstations. Ensure group members administrative accounts instead of standard accounts.
Separate administrator accounts from user accounts [CPG 1.5]. Only allow designated admin accounts to be used for admin purposes. If an individual user needs administrative rights over their workstation, use a separate account that does not have administrative access to other hosts, such as servers.
Consider using a privileged access management (PAM) solution to manage access to privileged accounts and resources [CPG 3.4]. PAM solutions can also log and alert usage to detect any unusual activity and may have helped stop the red team from accessing resources with admin accounts. Note: password vaults associated with PAM solutions should be treated as HVAs with additional restrictions and monitoring (see below).
Configure time-based access for accounts set at the admin level and higher. For example, the just-in-time (JIT) access method provisions privileged access when needed and can support enforcement of the principle of least privilege, as well as the Zero Trust model. This is a process in which a network-wide policy is set in place to automatically disable administrator accounts at the AD level when the account is not in direct need. When individual users need the account, they submit their requests through an automated process that enables access to a system but only for a set timeframe to support task completion.
Hosts with Unconstrained Delegation enabled
Remove Unconstrained Delegation from all servers. If Unconstrained Delegation functionality is required, upgrade operating systems and applications to leverage other approaches (e.g., constrained delegation) or explore whether systems can be retired or further isolated from the enterprise. CISA recommends Windows Server 2019 or greater.
Consider disabling or limiting NTLM and WDigest Authentication if possible, including using their use as criteria for prioritizing updates to legacy systems or for segmenting the network. Instead use more modern federation protocols (SAML, OIDC) or Kerberos for authentication with AES-256 bit encryption [CPG 3.4].
If on-premise, require MFA for admin and apply network segmentation [CPG 1.3]. Use solutions with end-to-end encryption where applicable [CPG 3.3].
If cloud-based, evaluate the provider to ensure use of strong security controls such as MFA and end-to-end encryption [CPG 1.3, 3.3].
Inconsistent host configuration
Establish a baseline/gold-image for workstations and servers and deploy from that image [CPG 2.5]. Use standardized groups to administer hosts in the network.
Potentially unwanted programs
Implement software allowlisting to ensure users can only install software from an approved list [CPG 2.1].
Remove unnecessary, extraneous software from servers and workstations.
Mandatory password changes enabled
Consider only requiring changes for memorized passwords in the event of compromise. Regular changing of memorized passwords can lead to predictable patterns, and both CISA and the National Institute of Standards and Technology (NIST) recommend against changing passwords on regular intervals.
Additionally, CISA recommends organizations implement the mitigations below to improve their cybersecurity posture:
Provide users with regular training and exercises, specifically related to phishing emails [CPG 4.3]. Phishing accounts for majority of initial access intrusion events.
Refrain from storing plaintext credentials in scripts [CPG 3.4]. The red team discovered a PowerShell script containing plaintext credentials that allowed them to escalate to admin.
Upgrade to Windows Server 2019 or greater and Windows 10 or greater. These versions have security features not included in older operating systems.
As a long-term effort, CISA recommends organizations prioritize implementing a more modern, Zero Trust network architecture that:
Leverages secure cloud services for key enterprise security capabilities (e.g., identity and access management, endpoint detection and response, policy enforcement).
Upgrades applications and infrastructure to leverage modern identity management and network access practices.
Centralizes and streamlines access to cybersecurity data to drive analytics for identifying and managing cybersecurity risks.
Invests in technology and personnel to achieve these goals.
CISA encourages organizational IT leadership to ask their executive leadership the question: Can the organization accept the business risk of NOT implementing critical security controls such as MFA? Risks of that nature should typically be acknowledged and prioritized at the most senior levels of an organization.
VALIDATE SECURITY CONTROLS
In addition to applying mitigations, CISA recommends exercising, testing, and validating your organization’s security program against the threat behaviors mapped to the MITRE ATT&CK for Enterprise framework in this advisory. CISA recommends testing your existing security controls inventory to assess how they perform against the ATT&CK techniques described in this advisory.
To get started:
Select an ATT&CK technique described in this advisory (see Table 3).
Align your security technologies against the technique.
Test your technologies against the technique.
Analyze your detection and prevention technologies’ performance.
Repeat the process for all security technologies to obtain a set of comprehensive performance data.
Tune your security program, including people, processes, and technologies, based on the data generated by this process.
CISA recommends continually testing your security program, at scale, in a production environment to ensure optimal performance against the MITRE ATT&CK techniques identified in this advisory.
The team obtained the cached credentials from a SharePoint server account by taking a snapshot of lsass.exe with a tool called nanodump, exporting the output and processing the output offline with Mimikatz.
The team remotely enumerated the local administrators group on target hosts to find valid user accounts. This technique relies on anonymous SMB pipe binds, which are disabled by default starting with Server 2016.
During Phase II, the team established sessions that originated from a target Workstation and from the DC directly to an external host over a clear text protocol.
Note: This joint Cybersecurity Advisory (CSA) is part of an ongoing #StopRansomware effort to publish advisories for network defenders that detail various ransomware variants and ransomware threat actors. These #StopRansomware advisories include recently and historically observed tactics, techniques, and procedures (TTPs) and indicators of compromise (IOCs) to help organizations protect against ransomware. Visit stopransomware.gov to see all #StopRansomware advisories and to learn more about other ransomware threats and no-cost resources.
Actions to take today to mitigate cyber threats from ransomware:
The Federal Bureau of Investigation (FBI) and the Cybersecurity and Infrastructure Security Agency (CISA) are releasing this joint CSA to disseminate known Royal ransomware IOCs and TTPs identified through FBI threat response activities as recently as January 2023.
Since approximately September 2022, cyber criminals have compromised U.S. and international organizations with a Royal ransomware variant. FBI and CISA believe this variant, which uses its own custom-made file encryption program, evolved from earlier iterations that used “Zeon” as a loader. After gaining access to victims’ networks, Royal actors disable antivirus software and exfiltrate large amounts of data before ultimately deploying the ransomware and encrypting the systems. Royal actors have made ransom demands ranging from approximately $1 million to $11 million USD in Bitcoin. In observed incidents, Royal actors do not include ransom amounts and payment instructions as part of the initial ransom note. Instead, the note, which appears after encryption, requires victims to directly interact with the threat actor via a .onion URL (reachable through the Tor browser). Royal actors have targeted numerous critical infrastructure sectors including, but not limited to, Manufacturing, Communications, Healthcare and Public Healthcare (HPH), and Education.
FBI and CISA encourage organizations to implement the recommendations in the Mitigations section of this CSA to reduce the likelihood and impact of ransomware incidents.
Note: This advisory uses the MITRE ATT&CK® for Enterprise framework, version 12. See MITRE ATT&CK for Enterprise for all referenced tactics and techniques.
Royal ransomware uses a unique partial encryption approach that allows the threat actor to choose a specific percentage of data in a file to encrypt. This approach allows the actor to lower the encryption percentage for larger files, which helps evade detection. In addition to encrypting files, Royal actors also engage in double extortion tactics in which they threaten to publicly release the encrypted data if the victim does not pay the ransom.
Royal actors gain initial access to victim networks in a number of ways including:
Phishing. According to third-party reporting, Royal actors most commonly (in 66.7% of incidents) gain initial access to victim networks via successful phishing emails [T1566].
According to open-source reporting, victims have unknowingly installed malware that delivers Royal ransomware after receiving phishing emails containing malicious PDF documents [T1566.001], and malvertising [T1566.002].
Remote Desktop Protocol (RDP). The second most common vector Royal actors use (in 13.3% of incidents) for initial access is RDP compromise.
Public-facing applications. FBI has also observed Royal actors gain initial access through exploiting public-facing applications [T1190].
Brokers. Reports from trusted third-party sources indicate that Royal actors may leverage brokers to gain initial access and source traffic by harvesting virtual private network (VPN) credentials from stealer logs.
Command and Control
Once Royal actors gain access to the network, they communicate with command and control (C2) infrastructure and download multiple tools [T1105]. Legitimate Windows software is repurposed by Royal operators to strengthen their foothold in the victim’s network. Ransomware operators often use open-source projects to aid their intrusion activities; Royal operators have recently been observed using Chisel, a tunneling tool transported over HTTP and secured via SSH [T1572], to communicate with their C2 infrastructure. FBI has observed multiple Qakbot C2s used in Royal ransomware attacks, but has not yet determined if Royal ransomware exclusively uses Qakbot C2s.
Lateral Movement and Persistence
Royal actors often use RDP to move laterally across the network [T1021.001]. Microsoft Sysinternals tool PsExec has also been used to aid lateral movement. FBI has observed Royal actors using remote monitoring and management (RMM) software, such as AnyDesk, LogMeIn, and Atera, for persistence in the victim’s network [T1133]. In some instances, the actors moved laterally to the domain controller. In one confirmed case, the actors used a legitimate admin account to remotely log on to the domain controller [T1078]. Once on the domain controller, the threat actor deactivated antivirus protocols [T1562.001] by modifying Group Policy Objects [T1484.001].
Royal actors exfiltrate data from victim networks by repurposing legitimate cyber pentesting tools, such as Cobalt Strike, and malware tools and derivatives, such as Ursnif/Gozi, for data aggregation and exfiltration. According to third-party reporting, Royal actors’ first hop in exfiltration and other operations is usually a U.S. IP address.
Note: In reference to Cobalt Strike and other tools mentioned above, a tool repository used by Royal was identified at IP: 94.232.41[.]105 in December 2022.
Before starting the encryption process, Royal actors:
Use Windows Restart Manager to determine whether targeted files are currently in use or blocked by other applications [T1486].
Use Windows Volume Shadow Copy service (vssadmin.exe) to delete shadow copies to prevent system recovery.
FBI has found numerous batch (.bat) files on impacted systems which are typically transferred as an encrypted 7zip file. Batch files create a new admin user [T1078.002], force a group policy update, set pertinent registry keys to auto-extract [T1119] and execute the ransomware, monitor the encryption process, and delete files upon completion—including Application, System, and Security event logs [T1070.001].
Malicious files have been found in victim networks in the following directories:
Indicators of Compromise (IOC)
See table 1 and 2 for Royal ransomware IOCs that FBI obtained during threat response activities as of January 2023. Note: Some of the observed IP addresses are several months old. FBI and CISA recommend vetting or investigating these IP addresses prior to taking forward-looking action, such as blocking.
Table 1: Royal Ransomware Associated Files, Hashes, and IP addresses as of January 2023
The actors encrypted data to determine which files were being used or blocked by other applications.
FBI and CISA recommend network defenders apply the following mitigations to limit potential adversarial use of common system and network discovery techniques and to reduce the risk of compromise by Royal ransomware. These mitigations follow CISA’s Cybersecurity Performance Goals (CPGs), which provide a minimum set of practices and protections that are informed by the most common and impactful threats, tactics, techniques, and procedures, and which yield goals that all organizations across critical infrastructure sectors should implement:
Implement a recovery plan to maintain and retain multiple copies of sensitive or proprietary data and servers [CPG 7.3] in a physically separate, segmented, and secure location (i.e., hard drive, storage device, the cloud).
Refrain from requiring password changes more frequently than once per year. Note: NIST guidance suggests favoring longer passwords instead of requiring regular and frequent password resets. Frequent password resets are more likely to result in users developing password patterns cyber criminals can easily decipher.
Require administrator credentials to install software.
Require multifactor authentication [CPG 1.3] for all services to the extent possible, particularly for webmail, virtual private networks, and accounts that access critical systems.
Keep all operating systems, software, and firmware up to date. Timely patching is one of the most efficient and cost-effective steps an organization can take to minimize its exposure to cybersecurity threats.
Segment networks [CPG 8.1]. Network segmentation can help prevent the spread of ransomware by controlling traffic flows between—and access to—various subnetworks and by restricting adversary lateral movement.
Identify, detect, and investigate abnormal activity and potential traversal of the indicated ransomware with a networking monitoring tool. To aid in detecting ransomware, implement a tool that logs and reports all network traffic [CPG 5.1], including lateral movement activity on a network. Endpoint detection and response (EDR) tools are useful for detecting lateral connections as they have insight into common and uncommon network connections for each host.
Install, regularly update, and enable real time detection for antivirus software on all hosts.
Review domain controllers, servers, workstations, and active directories for new and/or unrecognized accounts.
Audit user accounts with administrative privileges and configure access controls according to the principle of least privilege [CPG 1.5].
Disable unused ports.
Consider adding an email banner to emails [CPG 8.3] received from outside your organization.
Implement time-based access for accounts set at the admin level and higher. For example, the Just-in-Time (JIT) access method provisions privileged access when needed and can support enforcement of the principle of least privilege (as well as the Zero Trust model). This is a process where a network-wide policy is set in place to automatically disable admin accounts at the Active Directory level when the account is not in direct need. Individual users may submit their requests through an automated process that grants them access to a specified system for a set timeframe when they need to support the completion of a certain task.
Disable command-line and scripting activities and permissions. Privilege escalation and lateral movement often depend on software utilities running from the command line. If threat actors are not able to run these tools, they will have difficulty escalating privileges and/or moving laterally.
Maintain offline backups of data, and regularly maintain backup and restoration [CPG 7.3]. By instituting this practice, the organization ensures they will not be severely interrupted, and/or only have irretrievable data.
Ensure all backup data is encrypted, immutable (i.e., cannot be altered or deleted), and covers the entire organization’s data infrastructure [CPG 3.3].
Stopransomware.gov is a whole-of-government approach that gives one central location for ransomware resources and alerts.
Resource to mitigate a ransomware attack: CISA-Multi-State Information Sharing and Analysis Center (MS-ISAC) Joint Ransomware Guide.
FBI is seeking any information that can be shared, to include boundary logs showing communication to and from foreign IP addresses, a sample ransom note, communications with Royal actors, Bitcoin wallet information, decryptor files, and/or a benign sample of an encrypted file.
Additional details requested include: a targeted company Point of Contact, status and scope of infection, estimated loss, operational impact, transaction IDs, date of infection, date detected, initial attack vector, host and network based indicators.
FBI and CISA do not encourage paying ransom as payment does not guarantee victim files will be recovered. Furthermore, payment may also embolden adversaries to target additional organizations, encourage other criminal actors to engage in the distribution of ransomware, and/or fund illicit activities. Regardless of whether you or your organization have decided to pay the ransom, FBI and CISA urge you to promptly report ransomware incidents to a local FBI Field Office, or CISA at https://www.cisa.gov/report.
The information in this report is being provided “as is” for informational purposes only. CISA and FBI do not endorse any commercial product or service, including any subjects of analysis. Any reference to specific commercial products, processes, or services by service mark, trademark, manufacturer, or otherwise, does not constitute or imply endorsement, recommendation, or favoring by CISA or the FBI.
In this update we rewrote all the symbol logic. Classes (and their properties and methods) are now proper symbols. We now have a single visitor that builds a cached dictionary of symbols for each file instead of a dozen similar-yet-different Abstract Symbol Tree (AST) PowerShell script visitors handling different parts of each symbol-related request. This was a massive simplification of the code that also leads to huge performance improvements across all the symbol related features.
Over the course of more than one hundred years, the telecom industry has become standardized and regulated, and has developed methods, technologies, and an entire vocabulary (chock full of interesting acronyms) along the way. As an industry, they need to honor this tremendous legacy while also taking advantage of new technology, all in the name of delivering the best possible voice and data services to their customers.
Today I would like to tell you about AWS Telco Network Builder (TNB). This new service is designed to help Communications Service Providers (CSPs) deploy and manage public and private telco networks on AWS. It uses existing standards, practices, and data formats, and makes it easier for CSPs to take advantage of the power, scale, and flexibility of AWS.
Today, CSPs often deploy their code to virtual machines. However, as they look to the future they are looking for additional flexibility and are increasingly making use of containers. AWS TNB is intended to be a part of this transition, and makes use of Kubernetes and Amazon Elastic Kubernetes Service (EKS) for packaging and deployment.
Concepts and Vocabulary Before we dive in to the service, let’s take a look some concepts and vocabulary that are unique to this industry, and are relevant to AWS TNB:
European Telecommunications Standards Institute (ETSI) – A European organization that defines specifications suitable for global use. AWS TNB supports multiple ETSI specifications including ETSI SOL001 through ETSI SOL005, and ETSI SOL007.
Communications Service Provider (CSP) – An organization that offers telecommunications services.
Topology and Orchestration Specification for Cloud Applications (TOSCA) – A standardized grammar that is used to describe service templates for telecommunications applications.
Network Function (NF) – A software component that performs a specific core or value-added function within a telco network.
Virtual Network Function Descriptor (VNFD) – A specification of the metadata needed to onboard and manage a Network Function.
Cloud Service Archive (CSAR) – A ZIP file that contains a VNFD, references to container images that hold Network Functions, and any additional files needed to support and manage the Network Function.
Network Service Descriptor (NSD) – A specification of the compute, storage, networking, and location requirements for a set of Network Functions along with the information needed to assemble them to form a telco network.
Network Core – The heart of a network. It uses control plane and data plane operations to manage authentication, authorization, data, and policies.
Service Orchestrator (SO) – An external, high-level network management tool.
Radio Access Network (RAN) – The components (base stations, antennas, and so forth) that provide wireless coverage over a specific geographic area.
Using AWS Telco Network Builder (TNB) I don’t happen to be a CSP, but I will do my best to walk you through the getting-started experience anyway! The primary steps are:
Creating a function package for each Network Function by uploading a CSAR.
Creating a network package for the network by uploading a Network Service Descriptor (NSD).
Creating a network by selecting and instantiating an NSD.
To begin, I open the AWS TNB Console and click Get started:
Initially, I have no networks, no function packages, and no network packages:
My colleagues supplied me with sample CSARs and an NSD for use in this blog post (the network functions are from Free 5G Core):
Each CSAR is a fairly simple ZIP file with a VNFD and other items inside. For example, the VNFD for the Free 5G Core Session Management Function (smf) looks like this:
The final section (HelmImage) of the VNFD points to the Kubernetes Helm Chart that defines the implementation.
I click Function packages in the console, then click Create function package. Then I upload the first CSAR and click Next:
I review the details and click Create function package (each VNFD can include a set of parameters that have default values which can be overwritten with values that are specific to a particular deployment):
I repeat this process for the nine remaining CSARs, and all ten function packages are ready to use:
Now I am ready to create a Network Package. The Network Service Descriptor is also fairly simple, and I will show you several excerpts. First, the NSD establishes a mapping from descriptor_id to namespace for each Network Function so that the functions can be referenced by name:
I click Create network package, select the NSD, and click Next to proceed. AWS TNB asks me to review the list of function packages and the NSD parameters. I do so, and click Create network package:
My network package is created and ready to use within seconds:
Now I am ready to create my network instance! I select the network package and choose Create network instance from the Actions menu:
I give my network a name and a description, then click Next:
I make sure that I have selected the desired network package, review the list of functions packages that will be deployed, and click Next:
Then I do one final review, and click Create network instance:
I select the new network instance and choose Instantiate from the Actions menu:
I review the parameters, and enter any desired overrides, then click Instantiate network:
AWS Telco Network Builder (TNB) begins to instantiate my network (behind the scenes, the service creates a AWS CloudFormation template, uses the template to create a stack, and executes other tasks including Helm charts and custom scripts). When the instantiation step is complete, my network is ready to go. Instantiating a network creates a deployment, and the same network (perhaps with some parameters overridden) can be deployed more than once. I can see all of the deployments at a glance:
I can return to the dashboard to see my networks, function packages, network packages, and recent deployments:
Inside an AWS TNB Deployment Let’s take a quick look inside my deployment. Here’s what AWS TNB set up for me:
Deployment Options – We are launching with the ability to create a network that spans multiple Availability Zones in a single AWS Region. Over time we expect to add additional deployment options such as Local Zones and Outposts.
Pricing – Pricing is based on the number of Network Functions that are managed by AWS TNB and on calls to the AWS TNB APIs, but the first 45,000 API requests per month in each AWS Region are not charged. There are also additional charges for the AWS resources that are created as part of the deployment. To learn more, read the TNB Pricing page.
Reviewing my ISC mail inbox, I noticed that I had been receiving multiple phishing email that were very similar. Putting my cursor over each embedded pictures, I noticed the domain involved was the same for all of them. I copied the URL and started checking around for known threat intel on ipfs[.]io against various sites and found on urlscan.io , there was over 10000+ samples listed.
Iron Castle Systems
Manage Cookie Consent
To provide the best experiences, we use technologies like cookies to store and/or access device information. Consenting to these technologies will allow us to process data such as browsing behavior or unique IDs on this site. Not consenting or withdrawing consent, may adversely affect certain features and functions.
The technical storage or access is strictly necessary for the legitimate purpose of enabling the use of a specific service explicitly requested by the subscriber or user, or for the sole purpose of carrying out the transmission of a communication over an electronic communications network.
The technical storage or access is necessary for the legitimate purpose of storing preferences that are not requested by the subscriber or user.
The technical storage or access that is used exclusively for statistical purposes.The technical storage or access that is used exclusively for anonymous statistical purposes. Without a subpoena, voluntary compliance on the part of your Internet Service Provider, or additional records from a third party, information stored or retrieved for this purpose alone cannot usually be used to identify you.
The technical storage or access is required to create user profiles to send advertising, or to track the user on a website or across several websites for similar marketing purposes.