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Threat Finds
The anatomy of a SaaS attack: Two threats caught and investigated by AI
Executive summary
- Darktrace has observed a significant increase in attacks against SaaS platforms, including file storage, collaborative work, and email solutions.
- This blog post details two example threats that are representative of the current threat landscape: an Office 365 business email compromise and a Box.com file sharing account compromise.
- Organizations are recommended to enable multi-factor authentication to combat credential stuffing attacks and the re-use of stolen credentials from data dumps. It is further advised to actively monitor SaaS environments for in-progress cyber-attacks.
- SaaS exacerbates the skill gap in security – identifying and investigating threats in SaaS environments is a different skill to traditional security operations skill-sets.
Introduction
The digital transformation – whether planned naturally or forced by the global pandemic – has increased the use of Software-as-a-Service (SaaS) solutions in modern organizations. The annual growth rate of the SaaS market is currently 18%, and as the workforce becomes increasingly remote throughout 2020, this is set to skyrocket.
Attackers have been targeting SaaS solutions for a long time – but almost nobody talks about how the Techniques, Tools & Procedures (TTPs) in SaaS attacks differ significantly from traditional TTPs seen in networks and endpoint attacks.
How do you create meaningful detections in SaaS environments that don’t have endpoint or network data? How can you investigate threats in a SaaS environment as an analyst? What does a ‘good’ SaaS event look like, and what does a threat look like? Finding skilled security analysts that can work in traditional IT environments is already hard – it gets even harder when trying to hire security people with SaaS domain knowledge.
SaaS consumers are left with only a few choices: either use the native SaaS security controls provided in each SaaS solution – and rely on the (non-)maturity of the SaaS provider – or go with a third party SaaS security solution, often in the form of Cloud Access Security Brokers (CASBs). Both cases are often not ideal.
This blog outlines two attacks we have recently observed in SaaS environments that are representative for the broader SaaS threat landscape: a Microsoft (Office) 365 business email compromise (BEC) and the compromise of a corporate Box.com account. The analysis serves to illuminate the sharp distinction between a traditional network attack and a SaaS compromise – demonstrating how using machine learning to detect anomalies in behavior offers crucial hope for defenders as SaaS applications define this new era of work.
Anonymized SaaS Threat 1: Office 365 Business Email Compromise
Figure 1: The timeline of attack for the Microsoft 365 Compromise
In this case of a classic BEC attack, a threat-actor infiltrated an employee’s Microsoft 365 account to access sensitive financial documents hosted in SharePoint, including pay slip and banking details. The attacker went on to make configuration changes to the hacked inbox, deleting items and making updates that may have allowed them to cover their tracks.
Darktrace first observed the employee’s account log in from unusual IP ranges. The particular account had never logged in from Bulgaria before, and the peer accounts belonging to those from the same department had not exhibited similar behavioral traits. This in itself was a low-level anomaly and not necessarily indicative of malicious activity – employees might change locations after all.
The unusual login location was then accompanied by an unusual login time and a new user-agent. All of these anomalies triggered Cyber AI Analyst – Darktrace’s automated threat investigation technology – to launch a deeper analysis.
Darktrace then identified that the account was starting to access highly sensitive information, including payroll information on a Sharepoint. Two examples that were highlighted by AI Analyst are shown below:
- hxxps://anonymised[.]sharepoint[.]com/anonymised/pages/Understanding-my-payslip[.]aspx
- hxxps:// anonymised [.]sharepoint[.]com/anonymised /pages/Changing-my-bank-details[.]aspx
The attacker tried to gain insights about payment information and credit card details, with the likely intention of changing the payroll details to an attacker-controlled bank account. But with its ability to automatically analyze events to piece together attack narratives, Cyber AI Analyst was able to put together these weak signals of a threat and illuminate the likely account compromise. The security team was then able to lock the account and alert the user, who subsequently changed their credentials.
Anonymized SaaS Threat 2: Box.com Compromise
Figure 2: The timeline of attack for the Box.com Compromise
Darktrace observed a case of unauthorized access to a corporate Box.com file storage account belonging to an employee of a global supply company. The Box.com account login took place in the US – the same country that this organization operates in – but from an unusual IP space and ASN. Made suspicious by this low-level anomaly, Cyber AI Analyst did further, ongoing investigations into the user’s activity.
The actor behind the account logged in to Box.com successfully, and then proceeded to download expense reports, invoices, and other financial documents. It became evident that the account started accessing files that were highly unusual for the account to access. Darktrace recognized that neither the account itself, nor its peer group were usually accessing the file called ‘PASSWORD SHEET.xlsx’.
With Cyber AI’s bespoke knowledge of ‘self’ for every member of the organization’s workforce, the technology was able to identify the threat immediately. The Darktrace Cyber AI Platform detected that the activity occurred at a highly unusual time for the legitimate user, and that the location of the actor’s IP address was also anomalous compared to the employee’s previous access locations for this particular SaaS service.
While accessing these documents may have been normal for the employee in another context, Darktrace Cyber AI’s deep understanding of user behavior and granular visibility within the Box.com application allowed it to spot the subtle signs of account compromise. Moreover, when Darktrace’s Cyber AI Analyst automatically investigated the threat, it was able to illuminate the wider narrative, understanding that each unauthorized file exposure was part of a connected incident and highlighted the breach as a key concern for the security team.
Conclusion
Traditional detection approaches like ‘more than X failed logins from Y’ are not enough to ensure sufficient security across SaaS applications. Keeping threat intelligence lists up to date is even more difficult, as most SaaS attacks don’t involve any Command & Control – just indiscriminate logins from remote devices. Attackers may use VPN, Tor, other compromised devices, dynamic DNS, or virtual private servers to further mask their tracks.
A more intricate and effective approach to SaaS security requires understanding the dynamic individual behind the account. SaaS applications are fundamentally platforms for humans to communicate – allowing them to exchange and store ideas and information. Abnormal, threatening behavior is therefore impossible to detect without a nuanced understanding of those unique individuals: where and when do they typically access a SaaS account, which files are they like to access, who do they typically connect with?
Cyber AI asks these questions, continuously analyzing data not only across SaaS platforms, but from the unique ‘patterns of life’ of every user and device in the organization as a whole. With this context, it can chain together seemingly disparate anomalies – unusual login times, login locations, access of new or unusual files, and hundreds of other indicators of threat. These anomalies then act as a trigger for more in-depth investigations via Cyber AI Analyst that can link the anomalies together and create a coherent attack narrative.
Both of the above SaaS attacks were comprehensively but succinctly investigated and fully reported on by the Darktrace’s Cyber AI Analyst, which then surfaced an easy-to-understand incident report, ready for executive review. For a more in-depth look at how Cyber AI Analyst investigated an emerging APT threat in the wild, read: Catching APT41 exploiting a zero-day vulnerability.
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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
Cloud
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.
