5 Security Risks Companies Face Transitioning to Remote Work
Discover 5 security risks companies face with remote work employees. Protect against email scams, weakened security controls, errors, and insider threats.
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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.
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18
Mar 2020
As we all adjust to working remotely, security teams across the world are grappling with a very serious challenge. Almost overnight our companies have changed. Well established procedures are being rewritten, best practices quickly rethought, and policies stretched to breaking point.
Business transformation is always a security risk. New technology and working practices need new security measures; but normally this risk is managed carefully, and over time. COVID-19 has not afforded us that luxury. For some businesses the scale and speed of this change will be unprecedented. It is also very public; attackers are aware of the situation and already exploiting it. Below are some of the most serious threats that security teams will face over the coming weeks.
1. Email scams
Change brings novelty, and novelty brings opportunity for scammers. In the last 48 hours, internal security teams will have been racing to roll out essential remote working tools. Links to download new software, changes to how we authenticate services. When you do not know what to expect, employee training on spotting social engineering goes out the window. Both employees and IT departments should be wary of unexpected calls and requests:
“Hi, I’m calling from IT, can you please read out your 2FA code to me to confirm that you have been transitioned to the new Duo system?”
“Hi, I’ve forgotten my O365 password, can you please email a reset code to my personal Gmail?”
Such requests may be legitimate and may need to be resolved outside normal channels. The onus will be on individuals to be cautious, apply common sense and validate as appropriate.
There will also be ample opportunity for spear phishers to impersonate third-parties and clients:
“Hi John, I need to reschedule our meeting next week to be remote. Please see the link below for an invite to the Zoom call.”
These risks will be exacerbated by the simultaneous relaxing of security controls in order to facilitate the use of non-standard web conferencing software and the sharing of files by email. Attackers will have both the opportunity and the means.
2. Weakened security controls
The weakening of security controls goes far beyond relaxing firewall rules and email policy. Many existing layers of security will not apply to remote workers. Employees suddenly taking their work computer home with them will find themselves stripped of protection as they trade the office network for their home Wi-Fi. Without internet proxy, NAC, IDS and NGFW, client devices will now be sitting exposed on potentially unsecured networks amongst potentially compromised devices. Endpoint security will have to bear the full brunt of protection.
Internal network security may be compromised as well; employees might need access to resources previously only accessible on a wired network in one location. To make it reachable over VPN, internal segmentation might need to be flattened. This will open the door to malware spread and lateral movement. Client certificate authentication protecting web services might need to be turned off to enable BYOD working for employees that don’t have a company laptop.
These changes must be scrupulously logged, and dependencies understood. The extra weight will have to be carried elsewhere: perhaps host AV policies can be tightened to compensate for lack of network protection, perhaps employee devices can be reconfigured to use a secure external DNS provider instead of the on-prem DNS server.
3. Attacks on remote-working infrastructure
Beyond the weakening of existing controls, spinning up new infrastructure will bring fresh risks. In January we saw a spate of attacks on web-facing Citrix infrastructure. Companies will be rapidly deploying VPN gateways, transitioning to Sharepoint and expanding their internet-facing perimeter. This rapidly increased attack surface will need monitoring and protecting. Security teams should be on heightened alert for brute force and server-side attacks. DDoS protection will also become more important than ever; for many companies this will be the first time that a DDoS attack could cripple their business by preventing remote workers from accessing services over the internet. We should expect to see a sharp rise in both of these forms of attack immediately.
4. Errors and creative solutions
“Put it in an S3 bucket.”
“Let’s use join.me instead.”
“I’ll send it to you over WeTransfer.”
Both IT, and individual employees, will face blockers. There won’t be an authorized solution for their needs, and those needs may well be extremely urgent. At a time when businesses are extremely worried about their financial position and ability to operate, there will be pressure to throw caution to the wind and protect ‘business as usual’. This pressure may even come from the top. Security leadership must do the best they can to both push back against rash decisions and provide creative solutions.
Well-meaning employees will get creative, and responsibility will be delegated to team leaders to “do what it takes”. It may be impossible for security to police this centrally but monitoring vigilance will be required to spot risky behavior and non-compliance. This is easier said than done; the SOC will be asked to monitor for incidents in a sea of change. Existing use-cases and rules will not apply, and companies will need a more proactive and dynamic approach to detection and response.
5. Malicious insiders and malicious housemates
Unfortunately, there will be some within our companies that want to kick us while we are down. Sudden remote working is a godsend to malicious insiders. Data can now be easily taken from a company device over USB within the privacy of their own home. Security monitoring may be crippled or disabled entirely. This risk is harder to address. It may not be eliminable, but it can be balanced against the need for productivity and access to data.
We should also be wary of those around us. We all hope we can trust the people we live with. But from a company perspective, employee homes are zero-trust environments. Confidential conversations will now be conducted within range of eavesdroppers. Intellectual property will be visible on screens and monitors in living rooms around the world. This risk is greater for younger demographics likely to be house-sharing, but it remains for all workers; delivery personnel, visitors to the house – they could all potentially steal a company laptop from the kitchen room table. Education of employees in particular risk groups will be key.
Finding direction in a sea of digital change
All of the above changes and risks create a monitoring nightmare for SOCs. We are entering into a period of digital unknown, where change will be the new normal. Data flows and topology will change. New technology and services will be deployed. Logging formats will be different. The SIEM use-cases that took 12 months to develop will need to be scrapped overnight. For the next few weeks, business practice will shift rapidly.
Static defenses and rules will not be able to keep up, no matter how diligently and rapidly we rewrite them. How will you spot a malicious login attempt to O365 in your audit logs now that connections are coming from thousands of different locations around the world? Companies need to leverage technology that can allow them to continue to operate amidst uncertainty without choking productivity at this critical time. More critical still, containing those threats is of paramount importance – it won’t be feasible to entirely quarantine an infected machine if it cannot be re-imaged or replaced for days.
AI systems that can continuously evolve and adapt to change will provide the best chance of detecting misconfigurations, attacks, and risky behavior – when you don’t know what to look for, you need technology that is able to identify patterns and quantify risks for you. Autonomous Response technology can also surgically intervene to halt malicious activity when teams can’t be there to stop it, protecting devices and systems whilst allowing essential operations to continue unaffected.
Evolutions: Meeting the challenge head-on
Confronting these threats will not be easy. It will require a mixture of hard work, creativity, and new technology, alongside an openness to new ways of working and a willingness to embrace dynamic, proactive defense, instead of traditional rigid policies. However, placing trust in defensive systems to autonomously protect employees will be the single most effective way of maintaining resilience and security when our static defenses have failed us.
At Darktrace we are working hard to help our customers get even more value from their Cyber AI platform throughout this difficult time, and ease workloads of busy security teams. We know that with the right tools and technologies – from Autonomous Response and Cyber AI Analyst, through to the Darktrace Mobile App – these teams will be able to navigate these stormy waters. In this unprecedented period of uncertainty, the need for security that evolves in step with your changing digital business has never been greater.
No items found.
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.
Defending the Cloud: Stopping Cyber Threats in Azure and AWS with Darktrace
Real-world intrusions across Azure and AWS
As organizations pursue greater scalability and flexibility, cloud platforms like Microsoft Azure and Amazon Web Services (AWS) have become essential for enabling remote operations and digitalizing corporate environments. However, this shift introduces a new set of security risks, including expanding attack surfaces, misconfigurations, and compromised credentials frequently exploited by threat actors.
This blog dives into three instances of compromise within a Darktrace customer’s Azure and AWS environment which Darktrace.
The first incident took place in early 2024 and involved an attacker compromising a legitimate user account to gain unauthorized access to a customer’s Azure environment.
The other two incidents, taking place in February and March 2025, targeted AWS environments. In these cases, threat actors exfiltrated corporate data, and in one instance, was able to detonate ransomware in a customer’s environment.
Case 1 - Microsoft Azure
Figure 1: Simplified timeline of the attack on a customer’s Azure environment.
In early 2024, Darktrace identified a cloud compromise on the Azure cloud environment of a customer in the Europe, the Middle East and Africa (EMEA) region.
Initial access
In this case, a threat actor gained access to the customer’s cloud environment after stealing access tokens and creating a rogue virtual machine (VM). The malicious actor was found to have stolen access tokens belonging to a third-party external consultant’s account after downloading cracked software.
With these stolen tokens, the attacker was able to authenticate to the customer’s Azure environment and successfully modified a security rule to allow inbound SSH traffic from a specific IP range (i.e., securityRules/AllowCidrBlockSSHInbound). This was likely performed to ensure persistent access to internal cloud resources.
Detection and investigation of the threat
Darktrace / IDENTITY recognized that this activity was highly unusual, triggering the “Repeated Unusual SaaS Resource Creation” alert.
Cyber AI Analyst launched an autonomous investigation into additional suspicious cloud activities occurring around the same time from the same unusual location, correlating the individual events into a broader account hijack incident.
Figure 2: Cyber AI Analyst’s investigation into unusual cloud activity performed by the compromised account.
Figure 3: Surrounding resource creation events highlighted by Cyber AI Analyst.
Figure 4: Surrounding resource creation events highlighted by Cyber AI Analyst.
“Create resource service limit” events typically indicate the creation or modification of service limits (i.e., quotas) for a specific Azure resource type within a region. Meanwhile, “Registers the Capacity Resource Provider” events refer to the registration of the Microsoft Capacity resource provider within an Azure subscription, responsible for managing capacity-related resources, particularly those related to reservations and service limits. These events suggest that the threat actor was looking to create new cloud resources within the environment.
Around ten minutes later, Darktrace detected the threat actor creating or modifying an Azure disk associated with a virtual machine (VM), suggesting an attempt to create a rogue VM within the environment.
Threat actors can leverage such rogue VMs to hijack computing resources (e.g., by running cryptomining malware), maintain persistent access, move laterally within the cloud environment, communicate with command-and-control (C2) infrastructure, and stealthily deliver and deploy malware.
Persistence
Several weeks later, the compromised account was observed sending an invitation to collaborate to an external free mail (Google Mail) address.
Darktrace deemed this activity as highly anomalous, triggering a compliance alert for the customer to review and investigate further.
The next day, the threat actor further registered new multi-factor authentication (MFA) information. These actions were likely intended to maintain access to the compromised user account. The customer later confirmed this activity by reviewing the corresponding event logs within Darktrace.
Case 2 – Amazon Web Services
Figure 5: Simplified timeline of the attack on a customer’s AWS environment
In February 2025, another cloud-based compromised was observed on a UK-based customer subscribed to Darktrace’s Managed Detection and Response (MDR) service.
How the attacker gained access
The threat actor was observed leveraging likely previously compromised credential to access several AWS instances within customer’s Private Cloud environment and collecting and exfiltrating data, likely with the intention of deploying ransomware and holding the data for ransom.
Darktrace alerting to malicious activity
This observed activity triggered a number of alerts in Darktrace, including several high-priority Enhanced Monitoring alerts, which were promptly investigated by Darktrace’s Security Operations Centre (SOC) and raised to the customer’s security team.
The earliest signs of attack observed by Darktrace involved the use of two likely compromised credentials to connect to the customer’s Virtual Private Network (VPN) environment.
Internal reconnaissance
Once inside, the threat actor performed internal reconnaissance activities and staged the Rclone tool “ProgramData\rclone-v1.69.0-windows-amd64.zip”, a command-line program to sync files and directories to and from different cloud storage providers, to an AWS instance whose hostname is associated with a public key infrastructure (PKI) service.
The threat actor was further observed accessing and downloading multiple files hosted on an AWS file server instance, notably finance and investment-related files. This likely represented data gathering prior to exfiltration.
Shortly after, the PKI-related EC2 instance started making SSH connections with the Rclone SSH client “SSH-2.0-rclone/v1.69.0” to a RockHoster Virtual Private Server (VPS) endpoint (193.242.184[.]178), suggesting the threat actor was exfiltrating the gathered data using the Rclone utility they had previously installed. The PKI instance continued to make repeated SSH connections attempts to transfer data to this external destination.
Darktrace’s Autonomous Response
In response to this activity, Darktrace’s Autonomous Response capability intervened, blocking unusual external connectivity to the C2 server via SSH, effectively stopping the exfiltration of data.
This activity was further investigated by Darktrace’s SOC analysts as part of the MDR service. The team elected to extend the autonomously applied actions to ensure the compromise remained contained until the customer could fully remediate the incident.
Continued reconissance
Around the same time, the threat actor continued to conduct network scans using the Nmap tool, operating from both a separate AWS domain controller instance and a newly joined device on the network. These actions were accompanied by further internal data gathering activities, with around 5 GB of data downloaded from an AWS file server.
The two devices involved in reconnaissance activities were investigated and actioned by Darktrace SOC analysts after additional Enhanced Monitoring alerts had triggered.
Lateral movement attempts via RDP connections
Unusual internal RDP connections to a likely AWS printer instance indicated that the threat actor was looking to strengthen their foothold within the environment and/or attempting to pivot to other devices, likely in response to being hindered by Autonomous Response actions.
This triggered multiple scanning, internal data transfer and unusual RDP alerts in Darktrace, as well as additional Autonomous Response actions to block the suspicious activity.
Suspicious outbound SSH communication to known threat infrastructure
Darktrace subsequently observed the AWS printer instance initiating SSH communication with a rare external endpoint associated with the web hosting and VPS provider Host Department (67.217.57[.]252), suggesting that the threat actor was attempting to exfiltrate data to an alternative endpoint after connections to the original destination had been blocked.
Further investigation using open-source intelligence (OSINT) revealed that this IP address had previously been observed in connection with SSH-based data exfiltration activity during an Akira ransomware intrusion [1].
Once again, connections to this IP were blocked by Darktrace’s Autonomous Response and subsequently these blocks were extended by Darktrace’s SOC team.
The above behavior generated multiple Enhanced Monitoring alerts that were investigated by Darktrace SOC analysts as part of the Managed Threat Detection service.
Figure 5: Enhanced Monitoring alerts investigated by SOC analysts as part of the Managed Detection and Response service.
Final containment and collaborative response
Upon investigating the unusual scanning activity, outbound SSH connections, and internal data transfers, Darktrace analysts extended the Autonomous Response actions previously triggered on the compromised devices.
As the threat actor was leveraging these systems for data exfiltration, all outgoing traffic from the affected devices was blocked for an additional 24 hours to provide the customer’s security team with time to investigate and remediate the compromise.
Additional investigative support was provided by Darktrace analysts through the Security Operations Service, after the customer's opened of a ticket related to the unfolding incident.
Figure 8: Simplified timeline of the attack
Around the same time of the compromise in Case 2, Darktrace observed a similar incident on the cloud environment of a different customer.
Initial access
On this occasion, the threat actor appeared to have gained entry into the AWS-based Virtual Private Cloud (VPC) networkvia a SonicWall SMA 500v EC2 instance allowing inbound traffic on any port.
The instance received HTTPS connections from three rare Vultr VPS endpoints (i.e., 45.32.205[.]52, 207.246.74[.]166, 45.32.90[.]176).
Lateral movement and exfiltration
Around the same time, the EC2 instance started scanning the environment and attempted to pivot to other internal systems via RDP, notably a DC EC2 instance, which also started scanning the network, and another EC2 instance.
The latter then proceeded to transfer more than 230 GB of data to the rare external GTHost VPS endpoint 23.150.248[.]189, while downloading hundreds of GBs of data over SMB from another EC2 instance.
Figure 7: Cyber AI Analyst incident generated following the unusual scanning and RDP connections from the initial compromised device.
The same behavior was replicated across multiple EC2 instances, whereby compromised instances uploaded data over internal RDP connections to other instances, which then started transferring data to the same GTHost VPS endpoint over port 5000, which is typically used for Universal Plug and Play (UPnP).
What Darktrace detected
Darktrace observed the threat actor uploading a total of 718 GB to the external endpoint, after which they detonated ransomware within the compromised VPC networks.
This activity generated nine Enhanced Monitoring alerts in Darktrace, focusing on the scanning and external data activity, with the earliest of those alerts triggering around one hour after the initial intrusion.
Darktrace’s Autonomous Response capability was not configured to act on these devices. Therefore, the malicious activity was not autonomously blocked and escalated to the point of ransomware detonation.
Conclusion
This blog examined three real-world compromises in customer cloud environments each illustrating different stages in the attack lifecycle.
The first case showcased a notable progression from a SaaS compromise to a full cloud intrusion, emphasizing the critical role of anomaly detection when legitimate credentials are abused.
The latter two incidents demonstrated that while early detection is vital, the ability to autonomously block malicious activity at machine speed is often the most effective way to contain threats before they escalate.
Together, these incidents underscore the need for continuous visibility, behavioral analysis, and machine-speed intervention across hybrid environments. Darktrace's AI-driven detection and Autonomous Response capabilities, combined with expert oversight from its Security Operations Center, give defenders the speed and clarity they need to contain threats and reduce operational disruption, before the situation spirals.
Credit to Alexandra Sentenac (Senior Cyber Analyst) and Dylan Evans (Security Research Lead)
Top Eight Threats to SaaS Security and How to Combat Them
The latest on the identity security landscape
Following the mass adoption of remote and hybrid working patterns, more critical data than ever resides in cloud applications – from Salesforce and Google Workspace, to Box, Dropbox, and Microsoft 365.
As SaaS applications look set to remain an integral part of the digital estate, organizations are being forced to rethink how they protect their users and data in this area.
What is SaaS security?
SaaS security is the protection of cloud applications. It includes securing the apps themselves as well as the user identities that engage with them.
Below are the top eight threats that target SaaS security and user identities.
1. Account Takeover (ATO)
Attackers gain unauthorized access to a user’s SaaS or cloud account by stealing credentials through phishing, brute-force attacks, or credential stuffing. Once inside, they can exfiltrate data, send malicious emails, or escalate privileges to maintain persistent access.
2. Privilege escalation
Cybercriminals exploit misconfigurations, weak access controls, or vulnerabilities to increase their access privileges within a SaaS or cloud environment. Gaining admin or superuser rights allows attackers to disable security settings, create new accounts, or move laterally across the organization.
3. Lateral movement
Once inside a network or SaaS platform, attackers move between accounts, applications, and cloud workloads to expand their foot- hold. Compromised OAuth tokens, session hijacking, or exploited API connections can enable adversaries to escalate access and exfiltrate sensitive data.
4. Multi-Factor Authentication (MFA) bypass and session hijacking
Threat actors bypass MFA through SIM swapping, push bombing, or exploiting session cookies. By stealing an active authentication session, they can access SaaS environments without needing the original credentials or MFA approval.
5. OAuth token abuse
Attackers exploit OAuth authentication mechanisms by stealing or abusing tokens that grant persistent access to SaaS applications. This allows them to maintain access even if the original user resets their password, making detection and mitigation difficult.
6. Insider threats
Malicious or negligent insiders misuse their legitimate access to SaaS applications or cloud platforms to leak data, alter configurations, or assist external attackers. Over-provisioned accounts and poor access control policies make it easier for insiders to exploit SaaS environments.
SaaS applications rely on APIs for integration and automation, but attackers exploit insecure endpoints, excessive permissions, and unmonitored API calls to gain unauthorized access. API abuse can lead to data exfiltration, privilege escalation, and service disruption.
8. Business Email Compromise (BEC) via SaaS
Adversaries compromise SaaS-based email platforms (e.g., Microsoft 365 and Google Workspace) to send phishing emails, conduct invoice fraud, or steal sensitive communications. BEC attacks often involve financial fraud or data theft by impersonating executives or suppliers.
BEC heavily uses social engineering techniques, tailoring messages for a specific audience and context. And with the growing use of generative AI by threat actors, BEC is becoming even harder to detect. By adding ingenuity and machine speed, generative AI tools give threat actors the ability to create more personalized, targeted, and convincing attacks at scale.
Protecting against these SaaS threats
Traditionally, security leaders relied on tools that were focused on the attack, reliant on threat intelligence, and confined to a single area of the digital estate.
However, these tools have limitations, and often prove inadequate for contemporary situations, environments, and threats. For example, they may lack advanced threat detection, have limited visibility and scope, and struggle to integrate with other tools and infrastructure, especially cloud platforms.
AI-powered SaaS security stays ahead of the threat landscape
New, more effective approaches involve AI-powered defense solutions that understand the digital business, reveal subtle deviations that indicate cyber-threats, and action autonomous, targeted responses.
