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Darktrace의 사이버 AI 분석가가 미국 연방 정부의 사건 보고를 가속화하는 방법
On March 15, 2022, President Biden signed the Cyber Incident Reporting for Critical Infrastructure Act into law, included as part of the Congressional Omnibus Appropriations bill. The law requires critical infrastructure owners and operators to quickly notify the Cyber and Infrastructure Security Agency (CISA) of ransomware payments and significant cyber-attacks.
The Cyber Incident Reporting for Critical Infrastructure Act creates two new reporting requirements:
- an obligation to report certain cyber incidents to DHS CISA within 72 hours
- an obligation to report ransomware payments within 24 hours
Supporting the new law, Darktrace AI accelerates the cyber incident reporting process. Specifically, Darktrace’s Cyber AI Analyst understands the connections among disparate security incidents with supervised machine learning and autonomously writes incident reports in human-readable language using natural language processing (NLP). These Darktrace incident reports allow human analysts to send reports to CISA quickly and efficiently.
In the below real-world attack case study, we demonstrate how Cyber AI Analyst facilitates seamless reporting for critical infrastructure organizations that fall victim to ransomware and malicious data exfiltration. The AI technology, trained on human analyst behavior, replicates investigations at machine speed and scale, surfacing relevant details in minutes and allowing security teams to understand what happened precisely and share this information with the relevant authorities.
The below threat investigation details a significant threat find on a step by step level in technical detail to demonstrate the power and speed of Cyber AI Analyst.
Cyber AI Analyst’s incident report
When ransomware struck this organization, Cyber AI Analyst was invaluable, autonomously investigating the full scope of the incident and generating a natural language summary that clearly showed the progression of the attack.
In the aftermath of this attack, Darktrace’s technology also offered analyst assistance in mapping out the timeline of the attack and identifying what files were compromised, helping the security team identify anomalous activity related to the ransomware attack.
With Darktrace AI’s insights, the team easily identified the timeline of the attack, affected devices, credentials used, file shares accessed, files exfiltrated, and malicious endpoints contacted, enabling the customer to disclose the scale of the attack and notify necessary parties.
This example demonstrates how Cyber AI Analyst empowers critical infrastructure owners and operators to swiftly report major cyber-attacks to the federal government. Considering that 72 hours is the reporting period is for significant incidents — and 24 hours for ransomware payments — Cyber AI Analyst is no longer a nice-to-have but a must-have for critical infrastructure.
Attack breakdown: Ransomware and data exfiltration
Cyber AI Analyst delivered the most critical information in an easy-to-read report — with no human touch involved — as shown in the incident report above. We will now break down the attack further to demonstrate how Darktrace’s Self-Learning AI understood the unusual activity throughout the attack lifecycle.
In this double extortion ransomware, attackers exfiltrated data over 22 days. The detections made by Darktrace’s Self-Learning AI, and the parallel investigation by Cyber AI Analyst, were used to map the attack chain and identify how and what data had been exfiltrated and encrypted.
The attack consisted of three general groups of events:
- Unencrypted FTP (File Transfer Protocol) data exfiltration to rare malicious external endpoint in Bulgaria (May 9 07:23:46 UTC – May 21 03:06:46 UTC)
- Ransomware encryption of files in network file shares (May 25 01:00:27 UTC – May 30 07:09:53 UTC)
- Encrypted SSH (Secure Shell) data exfiltration to rare malicious external endpoint (May 29 16:43:37 UTC – May 30 13:23:59 UTC)
First, uploads of internal data to a rare external endpoint in Bulgaria were observed within the networks. The exfiltration was preceded by SMB reads of internal file shares before approximately 450GB of data was exfiltrated via FTP.
Darktrace’s AI identified this threatening activity on its own, and the organization was quickly able to pinpoint what data had been exfiltrated, including files camouflaged by markings such as ‘Talent Acquisition’ and ‘Engineering and Construction,’ and legal and financial documents — suggesting that these were documents of an extremely sensitive nature.
Model breaches:
- Anomalous Connection / Unusual Incoming Data Volume
- Anomalous File / Internal / Additional Extension Appended to SMB File
- Compromise / Ransomware / Suspicious SMB Activity
- Compromise / Ransomware / SMB Reads then Writes with Additional Extensions
- Unusual Activity / Anomalous SMB Move & Write
- Unusual Activity / High Volume Server Data Transfer
- Unusual Activity / Sustained Anomalous SMB Activity
- Device / SMB Lateral Movement
Four days following this observed activity, Darktrace’s AI detected the deployment of ransomware when multiple compromised devices began making anomalous SMB connections to file shares that they do not typically access, reading and writing similar volumes to the SMB file shares, as well as writing additional extensions to files over SMB. The file extension comprised a random string of letters and was likely to be unique to this target.
Using Darktrace, the customer obtained a full list of files that had been encrypted. The list included apparent financial records in an ‘Accounts’ file share.
Model breaches:
- Anomalous Connection / Unusual Incoming Data Volume
- Anomalous File / Internal / Additional Extension Appended to SMB File
- Compromise / Ransomware / Suspicious SMB Activity
- Compromise / Ransomware / SMB Reads then Writes with Additional Extensions
- Unusual Activity / Anomalous SMB Move & Write
- Unusual Activity / High Volume Server Data Transfer
- Unusual Activity / Sustained Anomalous SMB Activity
- Device / SMB Lateral Movement
Simultaneously, uploads of internal data to a rare external endpoint were observed within the network. The uploads were all performed using encrypted SSH/SFTP. In total, approximately 3.5GB of data was exfiltrated this way.
Despite the attacker using an encrypted channel to exfiltrate this data, Darktrace detected anomalous SMB file transfers prior to the external upload, indicating which files were exfiltrated. Here, Darktrace’s ability to go ‘back in time’ proved invaluable in helping analysts determine which files had been exfiltrated, although they were exfiltrated via an encrypted means.
Model breaches:
- Anomalous Server Activity / Outgoing from Server
- Compliance / SSH to Rare External Destination
- Unusual Activity / Enhanced Unusual External Data Transfer
- Device / Anomalous SMB Followed By Multiple Model Breaches
- Device / Large Number of Model Breaches
- Anomalous Connection / Uncommon 1 GiB Outbound
- Anomalous Connection / Data Sent to Rare Domain
- Anomalous Connection / Data Sent To New External Device
How did the attack bypass the rest of the security stack?
Existing administrative credentials were used to escalate privileges within the network and perform malicious activity.
Had Darktrace Antigena been active, it would have actioned a targeted, autonomous response to contain the activity in its early stages. Antigena would have enforced the ‘pattern of life’ on the devices involved in anomalous SMB activity — containing activity such as reading from file shares that are not normally connected, appending extensions to files and blocking outgoing connections to rare external endpoints.
However, in this case, Antigena was not set up to take action – it was configured in Human Confirmation mode. The incident was clearly alerted on by Darktrace, and appeared as a top priority item in the security team’s workflow. However, the security team was not monitoring Darktrace’s user interface, and in the absence of any action taken by other tools, the attack was allowed to progress, and the organization was obligated to disclose the details of the incident.
Streamlining the reporting process
In the modern threat landscape, leaning on AI to stop fast-moving and sophisticated attacks at machine speed and scale is critical. As this attack shows, the technology also helps organizations fulfill reporting requirements in the aftermath of an attack.
New legislation requires timely disclosure; with many traditional approaches to security, organizations do not have the capacity to surface the full details after an attack. On top of this, collating these details can take days or weeks. This is why Darktrace is no longer a nice-to-have but a must-have for critical infrastructure organizations, which are now required to report significant incidents swiftly.
Darktrace’s AI detects malicious activity as it happens and empowers customers to quickly understand the timeline of a compromise, as well as files accessed and exfiltrated by an attacker. This not only prepares organizations to resist the most sophisticated attacks, but also accelerates and radically simplifies the process of reporting the data breach.
Security teams should not have to confront disclosure processes on their own. Attacks happen fast, and their aftermaths are messy – retrospective investigation of lost data can be a futile effort with traditional approaches. With Darktrace, security teams can meet disruptive and sudden attacks with precise and nimble means of uncovering data, as well as detection and mitigation of risk. And, should the need arise, rapid and accurate reporting of events is laid out on a silver platter by the AI.
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Inside the SOC
How Abuse of ‘PerfectData Software’ May Create a Perfect Storm: An Emerging Trend in Account Takeovers
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:
- Actor signs in to a Microsoft 365 account from an endpoint associated with a Virtual Private Server (VPS) or Virtual Private Network (VPN) service
- Actor registers an application called 'PerfectData Software' with Azure AD, and then grants permissions to the application
- 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.
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.
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)
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.
In addition, Darktrace Cyber AI Analyst was able to autonomously investigate registrations of the ‘PerfectData Software’ application and summarized its findings into digestible reports.
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
Blog
클라우드
Darktrace Integrates Self-Learning AI with Amazon Security Lake to Support Security Investigations
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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.
