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Come Antigena Email ha intercettato un attacco fearware che ha aggirato il gateway

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11
Mar 2020
11
Mar 2020

The cyber-criminals behind email attacks are well-researched and highly responsive to human behaviors and emotions, often seeking to evoke a specific reaction by leveraging topical information and current news. It’s therefore no surprise that attackers have attempted to latch onto COVID-19 in their latest effort to convince users to open their emails and click on seemingly benign links.

The latest email trend involves attackers who claim to be from the Center for Disease Control and Prevention, purporting to have emergency information about COVID-19. This is typical of a recent trend we’re calling ‘fearware’: cyber-criminals exploit a collective sense of fear and urgency, and coax users into clicking a malicious attachment or link. While the tactic is common, the actual campaigns contain terms and content that’s unique. There are a few patterns in the emails we’ve seen, but none reliably predictable enough to create hard and fast rules that will stop emails with new wording without causing false positives.

For example, looking for the presence of “CDC” in the email sender would easily fail when the emails begin to use new wording, like “WHO”. We’ve also seen a mismatch of links and their display text – with display text that reads “https://cdc.gov/[random-path]” while the actual link is a completely arbitrary URL. Looking for a pattern match on this would likely lead to false positives and would serve as a weak indicator at best.

The majority of these emails, especially the early ones, passed most of our customers’ existing defenses including Mimecast, Proofpoint, and Microsoft’s ATP, and were approved to be delivered directly to the end user’s inbox. Fortunately, these emails were immediately identified and actioned by Antigena Email, Darktrace’s Autonomous Response technology for the inbox.

Gateways: The Current Approach

Most organizations employ Secure Email Gateways (SEGs), like Mimecast or Proofpoint, which serve as an inline middleman between the email sender and the recipient’s email provider. SEGs have largely just become spam-detection engines, as these emails are obvious to spot when seen at scale. They can identify low-hanging fruit (i.e. emails easily detectable as malicious), but they fail to detect and respond when attacks become personalized or deviate even slightly from previously-seen attacks.

Figure 1: A high-level diagram depicting an Email Secure Gateway’s inline position.

SEGs tend to use lists of ‘known-bad’ IPs, domains, and file hashes to determine an email’s threat level – inherently failing to stop novel attacks when they use IPs, domains, or files which are new and have not yet been triaged or reported as malicious.

When advanced detection methods are used in gateway technologies, such as anomaly detection or machine learning, these are performed after the emails have been delivered, and require significant volumes of near-identical emails to trigger. The end result is very often to take an element from one of these emails and simply deny-list it.

When a SEG can’t make the determination on these factors, they may resort to a technique known as sandboxing, which creates an isolated environment for testing links and attachments seen in emails. Alternatively, they may turn to basic levels of anomaly detection that are inadequate due to their lack of context of data outside of emails. For sandboxing, most advanced threats now typically employ evasion techniques like an activation time that waits until a certain date before executing. When deployed, the sandboxing attempts see a harmless file, not recognizing the sleeping attack waiting within.

Figure 2: This email was registered only 2 hours prior to an email we processed.

Taking a sample COVID-19 email seen in a Darktrace customer’s environment, we saw a mix of domains used in what appears to be an attempt to avoid pattern detection. It would be improbable to have the domains used on a list of ‘known-bad’ domains anywhere at the time of the first email, as it was received a mere two hours after the domain was registered.

Figure 3: While other defenses failed to block these emails, Antigena Email immediately marked them as 100% unusual and held them back from delivery.

Antigena Email sits behind all other defenses, meaning we only see emails when those defenses fail to block a malicious email or deem an email is safe for delivery. In the above COVID-19 case, the first 5 emails were marked by MS ATP with a spam confidence score of 1, indicating Microsoft scanned the email and it was determined to be clean – so Microsoft took no action whatsoever.

The Cat and Mouse Game

Cyber-criminals are permanently in flux, quickly moving to outsmart security teams and bypass current defenses. Recognizing email as the easiest entry point into an organization, they are capitalizing on the inadequate detection of existing tools by mass-producing personalized emails through factory-style systems that machine-research, draft, and send with minimal human interaction.

Domains are cheap, proxies are cheap, and morphing files slightly to change the entire fingerprint of a file is easy – rendering any list of ‘known-bads’ as outdated within seconds.

Cyber AI: The New Approach

A new approach is required that relies on business context and an inside-out understanding of a corporation, rather than analyzing emails in isolation.

An Immune System Approach

Darktrace’s core technology uses AI to detect unusual patterns of behavior in the enterprise. The AI is able to do this successfully by following the human immune system’s core principles: develop an innate sense of ‘self’, and use that understanding to detect abnormal activity indicative of a threat.

In order to identify threats across the entire enterprise, the AI is able to understand normal patterns of behavior beyond just the network. This is crucial when working towards a goal of full business understanding. There’s a clear connection between activity in, for example, a SaaS application and a corresponding network event, or an event in the cloud and a corresponding event elsewhere within the business.

There’s an explicit relationship between what people do on their computers and the emails they send and receive. Having the context that a user has just visited a website before they receive an email from the same domain lends credibility to that email: it’s very common to visit a website, subscribe to a mailing list, and then receive an email within a few minutes. On the contrary, receiving an email from a brand-new sender, containing a link that nobody in the organization has ever been to, lends support to the fact that the link is likely no good and that perhaps the email should be removed from the user’s inbox.

Enterprise-Wide Context

Darktrace’s Antigena Email extends this interplay of data sources to the inbox, providing unique detection capabilities by leveraging full business context to inform email decisions.

The design of Antigena Email provides a fundamental shift in email security – from where the tool sits to how it understands and processes data. Unlike SEGs, which sit inline and process emails only as they first pass through and never again, Antigena Email sits passively, ingesting data that is journaled to it. The technology doesn’t need to wait until a domain is fingerprinted or sandboxed, or until it is associated with a campaign that has a famous name and all the buzz.

Antigena Email extends its unique position of not sitting inline to email re-assessment, processing emails millions of times instead of just once, enabling actions to be taken well after delivery. A seemingly benign email with popular links may become more interesting over time if there’s an event within the enterprise that was determined to have originated via an email, perhaps when a trusted site becomes compromised. While Antigena Network will mitigate the new threat on the network, Antigena Email will neutralize the emails that contain links associated with those found in the original email.

Figure 4: Antigena Email sits passively off email providers, continuously re-assessing and issuing updated actions as new data is introduced.

When an email first arrives, Antigena Email extracts its raw metadata, processes it multiple times at machine speed, and then many millions of times subsequently as new evidence is introduced (typically based on events seen throughout the business). The system corroborates what it is seeing with what it has previously understood to be normal throughout the corporate environment. For example, when domains are extracted from envelope information or links in the email body, they’re compared against the popularity of the domain on the company’s network.

Figure 5: The link above was determined to be 100% rare for the enterprise.

Dissecting the above COVID-19 linked email, we can extract some of the data made available in the Antigena Email user interface to see why Darktrace thought the email was so unusual. The domain in the ‘From’ address is rare, which is supplemental contextual information derived from data across the customer’s entire digital environment, not limited to just email but including network data as well. The emails’ KCE, KCD, and RCE indicate that it was the first time the sender had been seen in any email: there had been no correspondence with the sender in any way, and the email address had never been seen in the body of any email.

Figure 6: KCE, KCD, and RCE scores indicate no sender history with the organization.

Correlating the above, Antigena Email deemed these emails 100% anomalous to the business and immediately removed them from the recipients’ inboxes. The platform did this for the very first email, and every email thereafter – not a single COVID-19-based email got by Antigena Email.

Conclusion

Cyber AI does not distinguish ‘good’ from ‘bad’; rather whether an event is likely to belong or not. The technology looks only to compare data with the learnt patterns of activity in the environment, incorporating the new email (alongside its own scoring of the email) into its understanding of day-to-day context for the organization.

By asking questions like “Does this email appear to belong?” or “Is there an existing relationship between the sender and recipient?”, the AI can accurately discern the threat posed by a given email, and incorporate these findings into future modelling. A model cannot be trained to think just because the corporation received a higher volume of emails from a specific sender, these emails are all of a sudden considered normal for the environment. By weighing human interaction with the emails or domains to make decisions on math-modeling reincorporation, Cyber AI avoids this assumption, unless there’s legitimate correspondence from within the corporation back out to the sender.

The inbox has traditionally been the easiest point of entry into an organization. But the fundamental differences in approach offered by Cyber AI drastically increase Antigena Email’s detection capability when compared with gateway tools. Customers with and without email gateways in place have therefore seen a noticeable curbing of their email problem. In the continuous cat-and-mouse game with their adversaries, security teams augmenting their defenses with Cyber AI are finally regaining the advantage.

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INSIDE THE SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
AUTHOR
ABOUT ThE AUTHOR
Dan Fein
Vicepresidente, Prodotto

Based in New York, Dan joined Darktrace’s technical team in 2015, helping customers quickly achieve a complete and granular understanding of Darktrace’s product suite. Dan has a particular focus on Darktrace/Email, ensuring that it is effectively deployed in complex digital environments, and works closely with the development, marketing, sales, and technical teams. Dan holds a Bachelor’s degree in Computer Science from New York University.

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Inside the SOC

How Abuse of ‘PerfectData Software’ May Create a Perfect Storm: An Emerging Trend in Account Takeovers

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05
Jun 2023

Amidst the ever-changing threat landscape, new tactics, techniques, and procedures (TTPs) seem to emerge daily, creating extreme challenges for security teams. The broad range of attack methods utilized by attackers seems to present an insurmountable problem: how do you defend against a playbook that does not yet exist?

Faced with the growing number of novel and uncommon attack methods, it is essential for organizations to adopt a security solution able to detect threats based on their anomalies, rather than relying on threat intelligence alone.   

In March 2023, Darktrace observed an emerging trend in the use of an application known as ‘PerfectData Software’ for probable malicious purposes in several Microsoft 365 account takeovers.

Using its anomaly-based detection, Darktrace DETECT™ was able to identify the activity chain surrounding the use of this application, potentially uncovering a novel piece of threat actor tradecraft in the process.

Microsoft 365 Intrusions

In recent years, Microsoft’s Software-as-a-Service (SaaS) suite, Microsoft 365, along with its built-in identity and access management (IAM) service, Azure Active Directory (Azure AD), have been heavily targeted by threat actors due to their near-ubiquitous usage across industries. Four out of every five Fortune 500 companies, for example, use Microsoft 365 services [1].  

Malicious actors typically gain entry to organizations’ Microsoft 365 environments by abusing either stolen account credentials or stolen session cookies [2]. Once inside, actors can access sensitive data within mailboxes or SharePoint repositories, and send out emails or Teams messages. This activity can often result in serious financial harm, especially in cases where the malicious actor’s end-goal is to elicit fraudulent transactions.  

Darktrace regularly observes malicious actors behaving in predictable ways once they gain access to customer Microsoft 365 environment. One typical example is the creation of new inbox rules and sending deceitful emails intended to convince recipients to carry out subsequent actions, such as following a malicious link or providing sensitive information. It is also common for actors to register new applications in Azure AD so that they can be used to conduct follow-up activities, like mass-mailing or data theft. The registration of applications in Azure AD therefore seems to be a relatively predictable threat actor behavior [3][4]. Darktrace DETECT understands that unusual application registrations in Azure AD may constitute a deviation in expected behavior, and therefore a possible indicator of account compromise.

These registrations of applications in Azure AD are evidenced by creations of, as well as assignments of permissions to, Service Principals in Azure AD. Darktrace has detected a growing trend in actors creating and assigning permissions to a Service Principal named ‘PerfectData Software’. Further investigation of this Azure AD activity revealed it to be part of an ongoing account takeover. 

 ‘PerfectData Software’ Activity 

Darktrace observed variations of the following pattern of activity relating to an application named ‘PerfectData Software’ within its customer base:

  1. Actor signs in to a Microsoft 365 account from an endpoint associated with a Virtual Private Server (VPS) or Virtual Private Network (VPN) service
  2. Actor registers an application called 'PerfectData Software' with Azure AD, and then grants permissions to the application
  3. Actor accesses mailbox data and creates inbox rule 

In two separate incidents, malicious actors were observed conducting their activities from endpoints associated with VPN services (HideMyAss (HMA) VPN and Surfshark VPN, respectively) and from endpoints within the Autonomous System AS396073 MAJESTIC-HOSTING-01. 

In March 2023, Darktrace observed a malicious actor signing in to a Microsoft 365 account from a Kuwait-based IP address within the Autonomous System, AS198605 AVAST Software s.r.o. This IP address is associated with the VPN service, HMA VPN. Over the next couple of days, an actor (likely the same malicious actor) signed in to the account several more times from two different Nigeria-based endpoints, as well as a VPS-related endpoint and a HMA VPN endpoint. 

During their login sessions, the actor performed a variety of actions. First, they created and assigned permissions to a Service Principal named ‘PerfectData Software’. This Service Principal creation represents the registration of an application called ‘PerfectData Software’ in Azure AD.  Although the reason for registering this application is unclear, within a few days the actor registered and granted permission to another application, ‘Newsletter Software Supermailer’, and created a new inbox rule names ‘s’ on the mailbox of the hijacked account. This inbox rule moved emails meeting certain conditions to a folder named ‘RSS Subscription. The ‘Newsletter Software Supermailer’ application was likely registered by the actor to facilitate mass-mailing activity.

Immediately after these actions, Darktrace detected the actor sending out thousands of malicious emails from the account. The emails included an attachment named ‘Credit Transfer Copy.html’, which contained a suspicious link. Further investigation revealed that the customer’s network had received several fake invoice emails prior to this initial intrusion activity. Additionally, there was an unusually high volume of failed logins to the compromised account around the time of the initial access. 

Figure 1: Advanced Search logs depicting the steps which the actor took after logging in to a user’s Microsoft 365 account.
Figure 1: Advanced Search logs depicting the steps which the actor took after logging in to a user’s Microsoft 365 account.

In a separate case also observed by Darktrace in March 2023, a malicious actor was observed signing in to a Microsoft 365 account from an endpoint within the Autonomous System, AS397086 LAYER-HOST-HOUSTON. The endpoint appears to be related to the VPN service, Surfshark VPN. This login was followed by several failed and successful logins from a VPS-related within the Autonomous System, AS396073 MAJESTIC-HOSTING-01. The actor was then seen registering and assigning permissions to an application called ‘PerfectData Software’. As with the previous example, the motives for this registration are unclear. The actor proceeded to log in several more times from a Surfshark VPN endpoint, however, they were not observed carrying out any further suspicious activity. 

Advanced Search logs depicting the steps which the actor took after logging in to a user’s Microsoft 365 account.
Figure 2: Advanced Search logs depicting the steps which the actor took after logging in to a user’s Microsoft 365 account.

It was not clear in either of these examples, nor in fact any of cases observed by Darktrace, why actors had registered and assigned permissions to an application called ‘PerfectData Software’, and there do not appear to be any open-source intelligence (OSINT) resources or online literature related to the malicious usage of an application by that name. That said, there are several websites which appear to provide email migration and data recovery/backup tools under the moniker ‘PerfectData Software’. 

It is unclear whether the use of ‘PerfectData Software’ by malicious actors observed on the networks of Darktrace customers was one of these tools. However, given the nature of the tools, it is possible that the actors intended to use them to facilitate the exfiltration of email data from compromises mailboxes.

If the legitimate software ‘PerfectData’ is the application in question in these incidents, it is likely being purchased and misused by attackers for malicious purposes. It is also possible the application referenced in the incidents is a spoof of the legitimate ‘PerfectData’ software designed to masquerade a malicious application as legitimate.

Darktrace Coverage

Cases of ‘PerfectData Software’ activity chains detected by Darktrace typically began with an actor signing into an internal user’s Microsoft 365 account from a VPN or VPS-related endpoint. These login events, along with the suspicious email and/or brute-force activity which preceded them, caused the following DETECT models to breach:

  • SaaS / Access / Unusual External Source for SaaS Credential Use
  • SaaS / Access / Suspicious Login Attempt
  • SaaS / Compromise / Login From Rare Following Suspicious Login Attempt(s)
  • SaaS / Email Nexus / Unusual Location for SaaS and Email Activity

Subsequent activities, including inbox rule creations, registration of applications in Azure AD, and mass-mailing activity, resulted in breaches of the following DETECT models.

  • SaaS / Admin / OAuth Permission Grant 
  • SaaS / Compromise / Unusual Logic Following OAuth Grant 
  • SaaS / Admin / New Application Service Principal
  • IaaS / Admin / Azure Application Administration Activities
  • SaaS / Compliance / New Email Rule
  • SaaS / Compromise / Unusual Login and New Email Rule
  • SaaS / Email Nexus / Suspicious Internal Exchange Activity
  • SaaS / Email Nexus / Possible Outbound Email Spam
  • SaaS / Compromise / Unusual Login and Outbound Email Spam
  • SaaS / Compromise / Suspicious Login and Suspicious Outbound Email(s)
DETECT Model Breaches highlighting unusual login and 'PerfectData Software' registration activity from a malicious actor
Figure 3: DETECT Model Breaches highlighting unusual login and 'PerfectData Software' registration activity from a malicious actor.

In cases where Darktrace RESPOND™ was enabled in autonomous response mode, ‘PerfectData Software’ activity chains resulted in breaches of the following RESPOND models:

• Antigena / SaaS / Antigena Suspicious SaaS Activity Block

• Antigena / SaaS / Antigena Significant Compliance Activity Block

In response to these model breaches, Darktrace RESPOND took immediate action, performing aggressive, inhibitive actions, such as forcing the actor to log out of the SaaS platform, and disabling the user entirely. When applied autonomously, these RESPOND actions would seriously impede an attacker’s progress and minimize network disruption.

Figure 4: A RESPOND model breach created in response to a malicious actor's registration of 'PerfectData Software'

In addition, Darktrace Cyber AI Analyst was able to autonomously investigate registrations of the ‘PerfectData Software’ application and summarized its findings into digestible reports. 

A Cyber AI Analyst Incident Event log
Figure 5: A Cyber AI Analyst Incident Event log showing AI Analyst autonomously pivoting off a breach of 'SaaS / Admin / OAuth Permission Grant' to uncover details of an account hijacking.

Conclusion 

Due to the widespread adoption of Microsoft 365 services in the workplace and continued emphasis on a remote workforce, account hijackings now pose a more serious threat to organizations around the world than ever before. The cases discussed here illustrate the tendency of malicious actors to conduct their activities from endpoints associated with VPN services, while also registering new applications, like PerfectData Software, with malicious intent. 

While it was unclear exactly why the malicious actors were using ‘PerfectData Software’ as part of their account hijacking, it is clear that either the legitimate or spoofed version of the application is becoming an very likely emergent piece of threat actor tradecraft.

Darktrace DETECT’s anomaly-based approach to threat detection allowed it to recognize that the use of ‘PerfectData Software’ represented a deviation in the SaaS user’s expected behavior. While Darktrace RESPOND, when enabled in autonomous response mode, was able to quickly take preventative action against threat actors, blocking the potential use of the application for data exfiltration or other nefarious purposes.

Appendices

MITRE ATT&CK Mapping

Reconnaissance:

T1598 ­– Phishing for Information

Credential Access:

T1110 – Brute Force

Initial Access:

T1078.004 – Valid Accounts: Cloud Accounts

Command and Control:

T1105 ­– Ingress Tool Transfer

Persistence:

T1098.003 – Account Manipulation: Additional Cloud Roles 

Collection:

• T1114 – Email Collection 

Defense Evasion:

• T1564.008 ­– Hide Artifacts: Email Hiding Rules­

Lateral Movement:

T1534 – Internal Spearphishing

Unusual Source IPs

• 5.62.60[.]202  (AS198605 AVAST Software s.r.o.) 

• 160.152.10[.]215 (AS37637 Smile-Nigeria-AS)

• 197.244.250[.]155 (AS37705 TOPNET)

• 169.159.92[.]36  (AS37122 SMILE)

• 45.62.170[.]237 (AS396073 MAJESTIC-HOSTING-01)

• 92.38.180[.]49 (AS202422 G-Core Labs S.A)

• 129.56.36[.]26 (AS327952 AS-NATCOM)

• 92.38.180[.]47 (AS202422 G-Core Labs S.A.)

• 107.179.20[.]214 (AS397086 LAYER-HOST-HOUSTON)

• 45.62.170[.]31 (AS396073 MAJESTIC-HOSTING-01)

References

[1] https://www.investing.com/academy/statistics/microsoft-facts/

[2] https://intel471.com/blog/countering-the-problem-of-credential-theft

[3] https://darktrace.com/blog/business-email-compromise-to-mass-phishing-campaign-attack-analysis

[4] https://darktrace.com/blog/breakdown-of-a-multi-account-compromise-within-office-365

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About the author
Sam Lister
SOC Analyst

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Darktrace Integrates Self-Learning AI with Amazon Security Lake to Support Security Investigations

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31
May 2023

Darktrace has deepened its relationship with AWS by integrating its detection and response capabilities with Amazon Security Lake

This development will allow mutual customers to seamlessly combine Darktrace AI’s bespoke understanding of their organization with the Threat Intelligence offered by other security tools, and investigate all of their alerts in one central location. 

This integration will improve the value security teams get from both products, streamlining analyst workflows and improving their ability to detect and respond to the full spectrum of known and unknown cyber-threats. 

How Darktrace and Amazon Security Lake augment security teams

Amazon Security Lake is a newly-released service that automatically centralizes an organization’s security data from cloud, on-premises, and custom sources into a customer owned purpose-built data lake. Both Darktrace and Amazon Security Lake support the Open Cybersecurity Schema Framework (OCSF), an open standard to simplify, combine, and analyze security logs.  

Customers can store security logs, events, alerts, and other relevant data generated by various AWS services and security tools. By consolidating security data in a central lake, organizations can gain a holistic view of their security posture, perform advanced analytics, detect anomalies and open investigations to improve their security practices.

With Darktrace DETECT and RESPOND AI engines covering all assets across IT, OT, network, endpoint, IoT, email and cloud, organizations can augment the value of their security data lakes by feeding Darktrace’s rich and context-aware datapoints to Amazon Security Lake. 

Amazon Security Lake empowers security teams to improve the protection of your digital estate:

  • Quick and painless data normalization 
  • Fast-tracks ability to investigate, triage and respond to security events
  • Broader visibility aids more effective decision-making
  • Surfaces and prioritizes anomalies for further investigation
  • Single interface for seamless data management

How will Darktrace customers benefit?

Across the Cyber AI Loop, all Darktrace solutions have been architected with AWS best practices in mind. With this integration, Darktrace is bringing together its understanding of ‘self’ for every organization with the centralized data visibility of the Amazon Security Lake. Darktrace’s unique approach to cyber security, powered by groundbreaking AI research, delivers a superior dataset based on a deep and interconnected understanding of the enterprise. 

Where other cyber security solutions are trained to identify threats based on historical attack data and techniques, Darktrace DETECT gains a bespoke understanding of every digital environment, continuously analyzing users, assets, devices and the complex relationships between them. Our AI analyzes thousands of metrics to reveal subtle deviations that may signal an evolving issue – even unknown techniques and novel malware. It distinguishes between malicious and benign behavior, identifying harmful activity that typically goes unnoticed. This rich dataset is fed into RESPOND, which takes precise action to neutralize threats against any and every asset, no matter where data resides.

Both DETECT and RESPOND are supported by Darktrace Self-Learning AI, which provides full, real-time visibility into an organization’s systems and data. This always-on threat analysis already makes humans better at cyber security, improving decisions and outcomes based on total visibility of the digital ecosystem, supporting human performance with AI coverage and empowering security teams to proactively protect critical assets.  

Converting Darktrace alerts to the Amazon Security Lake Open Cybersecurity Schema Framework (OCSF) supplies the Security Operations Center (SOC) and incident response team with contextualized data, empowering them to accelerate their investigation, triage and response to potential cyber threats. 

Darktrace is available for purchase on the AWS Marketplace.

Learn more about how Darktrace provides full-coverage, AI-powered cloud security for AWS, or see how our customers use Darktrace in their AWS cloud environments.

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About the author
Nabil Zoldjalali
Vicepresidente, Innovazione tecnologica

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