Since first being discovered in May 2020, WastedLocker has made quite a name for itself, quickly becoming an issue for businesses and cyber security firms around the world. WastedLocker is known for its sophisticated methods of obfuscation and steep ransom demands.
Its use of ‘Living off the Land’ techniques makes a WastedLocker attack extremely difficult for legacy security tools to detect. An ever-decreasing dwell time – the time between initial intrusion and final execution – means human responders alone struggle to contain the ransomware variant before damage is done.
This blog examines the anatomy of a WastedLocker intrusion that targeted a US agricultural organization in December. Darktrace’s AI detected and investigated the incident in real time, and we can see how Darktrace RESPOND would have autonomously taken action to stop the attack before encryption had begun.
As ransomware dwell time shrinks to hours rather than days, security teams are increasingly relying on artificial intelligence to stop threats from escalating at the earliest signs of compromise – containing attacks even when they strike at night or on the weekend.
How the WastedLocker attack unfolded
The initial infection appears to have taken place when an employee was deceived into downloading a fake browser update. Darktrace AI was monitoring the behavior of around 5,000 devices at the organization, continuously adapting its understanding of the evolving ‘pattern of life’. It detected the first signs of a threat when a virtual desktop device started making HTTP and HTTPS connections to external destinations that were deemed unusual for the organization. The graph below depicts how the patient zero device exhibited a spike in internal connections around December 4.
Attempted reconnaissance began just 11 minutes after the initial intrusion. Again, Darktrace immediately picked up on the activity, detecting unusual ICMP ping scans and targeted address scans on ports 135, 139 and 445; presumably as the attacker looked for potential further Windows targets. The below demonstrates the scanning detections based on the unusual number of new failed connections.
The attacker used an existing administrative credential to authenticate against a Domain Controller, initiating new service control over SMB. Darktrace picked this up immediately, identifying it as unusual behavior.
Several hours later – and in the early hours of the morning – the attacker used a temporary admin account ‘tempadmin’ to move to another Domain Controller over SMB. Darktrace instantly detected this as it was highly unusual to use a temporary admin account to connect from a virtual desktop to a Domain Controller.
Lock and load: WastedLocker prepares to strike
During the beaconing activity, the attacker also conducted internal reconnaissance and managed to establish successful administrative and remote connections to other internal devices by using tools already present. Soon after, a transfer of suspicious .csproj files was detected by Darktrace, and at least four other devices began exhibiting similar command and control (C2) communications.
However, with Darktrace’s real-time detections – and Cyber AI Analyst investigating and reporting on the incident in a number of minutes, the security team were able to contain the attack, taking the infected devices offline.
Automated investigations with Cyber AI Analyst
Darktrace’s Cyber AI Analyst launched an automatic investigation around every anomaly detection, forming hypotheses, asking questions about its own findings, and forming accurate answers at machine speed. It then generated high-level, intuitive incident summaries for the security team. Over the 48 hour period, the AI Analyst surfaced just six security incidents in total, with three of these directly relating to the WastedLocker intrusion.
The snapshot below shows a VMWare device (patient zero) making repeated external connections to rare destinations, scanning the network and using new admin credentials.
Darktrace RESPOND: AI that responds when the security team cannot
Darktrace RESPOND – the world’s first and only Autonomous Response technology – was configured in passive mode, meaning it did not actively interfere with the attack, but if we dive back into the Threat Visualizer we can see that Antigena in fully autonomous mode would have responded to the attack at this early stage, buying the security team valuable time.
In this case, after the initial unusual SSL C2 detection (based on a combination of destination rarity, JA3 unusualness and frequency analysis), RESPOND (formerly known as 'Antigena', as shown in the screenshots below) suggested instantly blocking the C2 traffic on port 443 and parallel internal scanning on port 135.
When beaconing was later observed to bywce.payment.refinedwebs[.]com, this time over HTTP to /updateSoftwareVersion, RESPOND escalated its response by blocking the further C2 channels.
The vast majority of response tools rely on hard-coded, pre-defined rules, formulated as ‘If X, do Y’. This can lead to false positives that unnecessarily take devices offline and hamper productivity. Darktrace RESPOND's actions are proportionate, bespoke to the organization, and not created in advance. Darktrace Antigena autonomously chose what to block and the severity of the blocks based on the context of the intrusion, without a human pre-eminently hard-coding any commands or set responses.
Every response over the 48 hours was related to the incident – RESPOND did not try to take action on anything else during the intrusion period. It simply would have actioned a surgical response to contain the threat, while allowing the rest of the business to carry on as usual. There were a total of 59 actions throughout the incident time period – excluding the ‘Watched Domain Block’ actions shown below – which are used during incident response to proactively shut down C2 communication.
RESPOND would have delivered those blocks via whatever integration is most suitable for the organization – whether that be Firewall integrations, NACL integrations or other native integrations. The technology would have blocked the malicious activity on the relevant ports and protocols for several hours – surgically interrupting the threat actors’ intrusion activity, thus preventing further escalation and giving the security team air cover.
Stopping WastedLocker ransomware before encryption ensues
This attack used many notable Tools, Techniques and Procedures (TTPs) to bypass signature-based tools. It took advantage of ‘Living off the Land’ techniques, including Windows Management Instrumentation (WMI), Powershell, and default admin credential use. Only one of the involved C2 domains had a single hit on Open Source Intelligence Lists (OSINT); the others were unknown at the time. The C2 was also encrypted with legitimate Thawte SSL Certificates.
For these reasons, it is plausible that without Darktrace in place, the ransomware would have been successful in encrypting files, preventing business operations at a critical time and possibly inflicting huge financial and reputational losses to the organization in question.
Darktrace’s AI detects and stops ransomware in its tracks without relying on threat intelligence. Ransomware has thrived this year, with attackers constantly coming up with new attack TTPs. However, the above threat find demonstrates that even targeted, sophisticated strains of ransomware can be stopped with AI technology.
Thanks to Darktrace analyst Signe Zaharka for her insights on the above threat find.
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.
ABOUT ThE AUTHOR
Chief Product Officer
Max is a cyber security expert with over a decade of experience in the field, specializing in a wide range of areas such as Penetration Testing, Red-Teaming, SIEM and SOC consulting and hunting Advanced Persistent Threat (APT) groups. At Darktrace, Max is closely involved with Darktrace’s strategic customers & prospects. He works closely with the R&D team at Darktrace’s Cambridge UK headquarters, leading research into new AI innovations and their various defensive and offensive applications. Max’s insights are regularly featured in international media outlets such as the BBC, Forbes and WIRED. When living in Germany, he was an active member of the Chaos Computer Club. Max holds an MSc from the University of Duisburg-Essen and a BSc from the Cooperative State University Stuttgart in International Business Information Systems.
share this article
Stay up to date on the latest industry news and insights.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
Darktrace/Email in Action: Why AI-Driven Email Security is the Best Defense Against Sustained Phishing Campaigns
Stopping the bad while allowing the good
Since its inception, email has been regarded as one of the most important tools for businesses, revolutionizing communication and allowing global teams to become even more connected. But besides organizations heavily relying on email for their daily operations, threat actors have also recognized that the inbox is one of the easiest ways to establish an initial foothold on the network.
Today, not only are phishing campaigns and social engineering attacks becoming more prevalent, but the level of sophistication of these attacks are also increasing with the help of generative AI tools that allow for the creation of hyper-realistic emails with minimal errors, effectively lowering the barrier to entry for threat actors. These diverse and stealthy types of attacks evade traditional email security tools based on rules and signatures, because they are less likely to contain the low-sophistication markers of a typical phishing attack.
In a situation where the sky is the limit for attackers and security teams are lean, how can teams equip themselves to tackle these threats? How can they accurately detect increasingly realistic malicious emails and neutralize these threats before it is too late? And importantly, how can email security block these threats while allowing legitimate emails to flow freely?
Instead of relying on past attack data, Darktrace’s Self-Learning AI detects the slightest deviation from a user’s pattern of life and responds autonomously to contain potential threats, stopping novel attacks in their tracks before damage is caused. It doesn’t define ‘good’ and ‘bad’ like traditional email tools, rather it understands each user and what is normal for them – and what’s not.
This blog outlines how Darktrace/Email™ used its understanding of ‘normal’ to accurately detect and respond to a sustained phishing campaign targeting a real-life company.
Responding to a sustained phishing attack
Over the course of 24 hours, Darktrace detected multiple emails containing different subjects, all from different senders to different recipients in one organization. These emails were sent from different IP addresses, but all came from the same autonomous system number (ASN).
The emails themselves had many suspicious indicators. All senders had no prior association with the recipient, and the emails generated a high general inducement score. This score is generated by structural and non-specific content analysis of the email – a high score indicates that the email is trying to induce the recipient into taking a particular action, which may lead to account compromise.
Additionally, each email contained a visually prominent link to a file storage service, hidden behind a shortened bit.ly link. The similarities across all these emails pointed to a sustained campaign targeting the organization by a single threat actor.
With all these suspicious indicators, many models were breached. This drove up the anomaly score, causing Darktrace/Email to hold all suspicious emails from the recipients’ inboxes, safeguarding the recipients from potential account compromise and disallowing the threats from taking hold in the network.
Imagining a phishing attack without Darktrace/Email
So what could have happened if Darktrace had not withheld these emails, and the recipients had clicked on the links? File storage sites have a wide variety of uses that allow attackers to be creative in their attack strategy. If the user had clicked on the shortened link, the possible consequences are numerous. The link could have led to a login page for unsuspecting victims to input their credentials, or it could have hosted malware that would automatically download if the link was clicked. With the compromised credentials, threat actors could even bypass MFA, change email rules, or gain privileged access to a network. The downloaded malware might also be a keylogger, leading to cryptojacking, or could open a back door for threat actors to return to at a later time.
The limits of traditional email security tools
Secure email gateways (SEGs) and static AI security tools may have found it challenging to detect this phishing campaign as malicious. While Darktrace was able to correlate these emails to determine that a sustained phishing campaign was taking place, the pattern among these emails is far too generic for specific rules as set in traditional security tools. If we take the characteristic of the freemail account sender as an example, setting a rule to block all emails from freemail accounts may lead to more legitimate emails being withheld, since these addresses have a variety of uses.
With these factors in mind, these emails could have easily slipped through traditional security filters and led to a devastating impact on the organization.
As threat actors step up their attacks in sophistication, prioritizing email security is more crucial than ever to preserving a safe digital environment. In response to these challenges, Darktrace/Email offers a set-and-forget solution that continuously learns and adapts to changes in the organization.
Through an evolving understanding of every environment in which it is deployed, its threat response becomes increasingly precise in neutralizing only the bad, while allowing the good – delivering email security that doesn’t come at the expense of business growth.
Over the past year, security researchers have been tracking a new ransomware group, known as Black Basta, that has been observed targeted organizations worldwide to deploy double extortion ransomware attacks since early 2022. While the strain and group are purportedly new, evidence seen suggests they are an offshoot of the Conti ransomware group .
The group behind Black Basta run a Ransomware as a Service (RaaS) model. They work with initial access brokers who will typically already have a foothold in company infrastructure to begin their attacks. Once inside a network, they then pivot internally using numerous tools to further their attack.
Black Basta Ransomware
Like many other ransomware actors, Black Basta uses double extortion as part of its modus operandi, exfiltrating sensitive company data and using the publication of this as a second threat to affected companies. This is also advertised on a dark web site, setup by the group to apply further pressure for affected companies to make ransom payments and avoid reputational damage.
The group also seems to regularly take advantage of existing tools to undertake the earlier stages of their attacks. Notably, the Qakbot banking trojan, seems to be the malware often used to gain an initial foothold within compromised environments.
Analysis of the tools, procedures and infrastructure used by Black Basta belies a maturity to the actors behind the ransomware. Their models and practices suggest those involved are experienced individuals, and security researchers have drawn possible links to the Conti ransomware group.
As such, Black Basta is a particular concern for security teams as attacks will likely be more sophisticated, with attackers more patient and able to lie low on digital estates for longer, waiting for the opportune moment to strike.
Cyber security is an infinite game where defender and attacker are stuck as cat and mouse; as new attacks evolve, security vendors and teams respond to the new indicators of compromise (IoCs), and update their existing rulesets and lists. As a result, attackers are forced to change their stripes to evade detection or sometimes even readjust their targets and end goals.
Anomaly Based Detection
By using the power of Darktrace’s Self-Learning AI, security teams are able to detect deviations in behavior. Threat actors need to move through the kill chain to achieve their aims, and in doing so will cause affected devices within networks to deviate from their expected pattern of life. Darktrace’s anomaly-based approach to threat detection allows it recognize these subtle deviations that indicate the presence of an attacker, and stop them in their tracks.
Additionally, the ecosystem of cyber criminals has matured in the last few decades. It is well documented how many groups now operate akin to legitimate companies, with structure, departments and governance. As such, while new attack methods and tactics do appear in the wild, the maturity in their business models belie the experience of those behind the attack.
As attackers grow their business models and develop their arsenal of attack vectors, it becomes even more critical for security teams to remain vigilant to anomalies within networks, and remain agnostic to underlying IoCs and instead adopt anomaly detection tools able to identify tactics, techniques, and procedures (TTPs) that indicate attackers may be moving through a network, ahead of deployment of ransomware and data encryption.
Darktrace’s Coverage of Black Basta
In April 2023, the Darktrace Security Operations Center (SOC) assisted a customer in triaging and responding to an ongoing ransomware infection on their network. On a Saturday, the customer reached out directly to the Darktrace analyst team via the Ask the Expert service for support after they observed encrypted files and locked administrative accounts on their network. The analyst team were able to investigate and clarify the attack path, identifying affected devices and assisting the customer with their remediation. Darktrace DETECT™ observed varying IoCs and TTPs throughout the course of this attack’s kill chain; subsequent analysis into these indicators revealed this had likely been a case of Black Basta seen in the wild.
The methods used by the group to gain an initial foothold in environments varies – sometimes using phishing, sometimes gaining access through a common vulnerability exposed to the internet. Black Basta actors appear to target specific organizations, as opposed to some groups who aim to hit multiple at once in a more opportunistic fashion.
In the case of the Darktrace customer likely affected by Black Basta, it is probable that the initial intrusion was out of scope. It may be that the path was via a phishing email containing an Microsoft Excel spreadsheet that launches malicious powershell commands; a noted technique for Black Basta.  Alternatively, the group may have worked with access brokers who already had a foothold within the customer’s network.
One particular device on the network was observed acting anomalously and was possibly the first to be infected. The device attempted to connect to multiple internal devices over SMB, and connected to a server that was later found to be compromised and is described throughout the course of this blog. During this connection, it wrote a file over SMB, “syncro.exe”, which is possibly a legitimate Remote Management software but could in theory be used to spread an infection laterally. Use of this tool otherwise appears sporadic for the network, and was notably unusual for the environment.
Given these timings, it is possible this activity is related to the likely Black Basta compromise. However, there is some evidence online that use of Syncro has been seen installed as part of the execution of loaders such as Batloader, potentially indicating a separate or concurrent attack .
Internal Reconnaissance + Lateral Movement
However the attackers gained access in this instance, the first suspicious activity observed by Darktrace originated from an infected server. The attacker used their foothold in the device to perform internal reconnaissance, enumerating large portions of the network. Darktrace DETECT’s anomaly detection noted a distinct rise in connections to a large number of subnets, particularly to closed ports associated with native Windows services, including:
During the enumeration, SMB connections were observed during which suspiciously named executable files were written:
Data Staging and Exfiltration
Around 4 hours after the scanning activity, the attackers used their knowledge gained during enumeration about the environment to begin gathering and staging data for their double extortion attempts. Darktrace observed the same infected server connecting to a file storage server, and downloading over 300 GiB of data. Darktrace DETECT identified that the connections had been made via SMB and was able to present a list of filenames to the customer, allowing their security team to determine the data that had likely been exposed to the attackers.
The SMB paths detected by Darktrace showed a range of departments’ file areas being accessed by threat actors. This suggests they were interested in getting as much varied data as possible, presumably in an attempt to ensure a large amount of valuable information was at their disposal to make any threats of releasing them more credible, and more damaging to the company.
Shortly after the download, the device made an external connection over SSH to a rare domain, dataspt[.]com, hosted in the United States. The connection itself was made over an unusual port, 2022, and Darktrace recognized that the domain was new for the network.
During this upload, the threat actors uploaded a similar volume of data to the 300GiB that had been downloaded internally earlier. Darktrace flagged the usual elements of this external upload, making the identification and triage of this exfiltration attempt easier for the customer.
On top of this, Darktrace’s autonomous investigation tool Cyber AI Analyst™ launched an investigation into this on-going activity and was able to link the external upload events to the internal download, identifying them as one exfiltration incident rather than two isolated events. AI Analyst then provided a detailed summary of the activity detected, further speeding up the identification of affected files.
Preparing for Exploitation
All the activity documented so far had occurred on a Wednesday evening. It was at this point that the burst of activity calmed, and the ransomware lay in wait within the environment. Other devices around the network, particularly those connected to by the original infected server and a domain controller, were observed performing some elements of anomalous activity, but the attack seemed to largely take a pause.
However, on the Saturday morning, 3 days later, the compromised server began to change the way it communicated with attackers by reaching out to a new command and control (C2) endpoint. It seemed that attackers were gearing up for their attack, taking advantage of the weekend to strike while security teams often run with a reduced staffing.
Darktrace identified connections to a new endpoint within 4 minutes of it first being seen on the customer’s environment. The server had begun making repeated SSL connections to the new external endpoint, faceappinc[.]com, which has been flagged as malicious by various open-source intelligence (OSINT) sources.
The observed JA3 hash (d0ec4b50a944b182fc10ff51f883ccf7) suggests that the command-line tool BITS Admin was being used to launch these connections, another suggestion of the use of mature tooling.
In addition to this, Darktrace also detected the server using an administrative credential it had never previously been associated with. Darktrace recognized that the use of this credential represented a deviation from the device’s usual activity and thus could be indicative of compromise.
The server then proceeded to use the new credential to authenticate over Keberos before writing a malicious file (“management.exe”) to the Temp directory on a number of internal devices.
At this point, the number of anomalous activities detected from the server increased massively as the attacker seems to connect networkwide in an attempt to cause as quick and destructive an encryption effort as possible. Darktrace observed numerous files that had been encrypted by a local process. The compromised server began to write ransom notes, named “instructions_read_me.txt” to other file servers, which presumably also had successfully deployed payloads. While Black Basta actors had initially been observed dropping ransom notes named “readme.txt”, security researchers have since observed and reported an updated variant of the ransomware that drops “instructions_read_me_.txt”, the name of the file detected by Darktrace, instead .
Another server was also observed making repeated SSL connections to the same rare external endpoint, faceappinc[.]com. Shortly after beginning these connections, the device made an HTTP connection to a rare IP address with no hostname, 212.118.55[.]211. During this connection, the device also downloaded a suspicious executable file, cal[.]linux. OSINT research linked the hash of this file to a Black Basta Executable and Linkable File (ELF) variant, indicating that the group was highly likely behind this ransomware attack.
Of particular interest again, is how the attacker lives off the land, utilizing pre-installed Windows services. Darktrace flagged that the server was observed using PsExec, a remote management executable, on multiple devices.
Darktrace DETECT was able to clearly detect and provide visibility over all stages of the ransomware attack, alerting the customer with multiple model breaches and AI Analyst investigation(s) and highlighting suspicious activity throughout the course of the attack.
For example, the exfiltration of sensitive data was flagged for a number of anomalous features of the meta-data: volume; rarity of the endpoint; port and protocol used.
In total, the portion of the attack observed by Darktrace lasted about 4 days from the first model breach until the ransomware was deployed. In particular, the encryption itself was initiated on a Saturday.
The encryption event itself was initiated on a Saturday, which is not uncommon as threat actors tend to launch their destructive attacks when they expect security teams will be at their lowest capacity. The Darktrace SOC team regularly observes and assists in customer’s in the face of ransomware actors who patiently lie in wait. Attackers often choose to strike as security teams run on reduced hours of manpower, sometimes even choosing to deploy ahead of longer breaks for national or public holidays, for example.
In this case, the customer contacted Darktrace directly through the Ask the Expert (ATE) service. ATE offers customers around the clock access to Darktrace’s team of expert analysts. Customers who subscribe to ATE are able to send queries directly to the analyst team if they are in need of assistance in the face of suspicious network activity or emerging attacks.
In this example, Darktrace’s team of expert analysts worked in tandem with Cyber AI Analyst to investigate the ongoing compromise, ensuring that the investigation and response process were completed as quickly and efficiently as possible.
Thanks to Darktrace’s Self-Learning AI, the analyst team were able to quickly produce a detailed report enumerating the timeline of events. By combining the human expertise of the analyst team and the machine learning capabilities of AI Analyst, Darktrace was able to quickly identify anomalous activity being performed and the affected devices. AI Analyst was then able to collate and present this information into a comprehensive and digestible report for the customer to consult.
It is likely that this ransomware attack was undertaken by the Black Basta group, or at least using tools related to their method. Although Black Basta itself is a relatively novel ransomware strain, there is a maturity and sophistication to its tactics. This indicates that this new group are actually experienced threat actors, with evidence pointing towards it being an offshoot of Conti.
The Pyramid of Pain is a well trodden model in cyber security, but it can help us understand the various features of an attack. Indicators like static C2 destinations or file hashes can easily be changed, but it’s the underlying TTPs that remain the same between attacks.
In this case, the attackers used living off the land techniques, making use of tools such as BITSAdmin, as well as using tried and tested malware such as Qakbot. While the domains and IPs involved will change, the way these malware interact and move about systems remains the same. Their fingerprint therefore causes very similar anomalies in network traffic, and this is where the strength of Darktrace lies.
Darktrace’s anomaly-based approach to threat detection means that these new attack types are quickly drawn out of the noise of everyday traffic within an environment. Once attackers have gained a foothold in a network, they will have to cause deviation from the usual pattern of a life on a network to proceed; Darktrace is uniquely placed to detect even the most subtle changes in a device’s behavior that could be indicative of an emerging threat.
Machine learning can act as a force multiplier for security teams. Working hand in hand with the Darktrace SOC, the customer was able to generate cohesive and comprehensive reporting on the attack path within days. This would be a feat for humans alone, requiring significant resources and time, but with the power of Darktrace’s Self-Learning AI, these deep and complex analyses become as easy as the click of a button.
Credit to: Matthew John, Director of Operations, SOC, Paul Jennings, Principal Analyst Consultant
Darktrace DETECT Model Breaches
Device / Multiple Lateral Movement Model Breaches
Device / Large Number of Model Breaches
Device / Network Scan
Device / Anomalous RDP Followed by Multiple Model Breaches
Device / Possible SMB/NTLM Reconnaissance
Device / SMB Lateral Movement
Anomalous Connection / SMB Enumeration
Anomalous Connection / Possible Share Enumeration Activity
Device / Suspicious SMB Scanning Activity
Device / RDP Scan
Anomalous Connection / Active Remote Desktop Tunnel
Device / Increase in New RPC Services
Device / ICMP Address Scan
Download and Upload
Unusual Activity / Enhanced Unusual External Data Transfer
Unusual Activity / Unusual External Data Transfer
Anomalous Connection / Uncommon 1 GiB Outbound
Anomalous Connection / Data Sent to Rare Domain
Anomalous Connection / Download and Upload
Compliance / SSH to Rare External Destination
Anomalous Server Activity / Rare External from Server
Anomalous Server Activity / Outgoing from Server
Anomalous Connection / Application Protocol on Uncommon Port
Anomalous Connection / Multiple Connections to New External TCP Port
Device / Anomalous SMB Followed By Multiple Model Breaches
Unusual Activity / SMB Access Failures
Lateral Movement and Encryption
User / New Admin Credentials on Server
Compliance / SMB Drive Write
Device / Anomalous RDP Followed By Multiple Model Breaches
Anomalous Connection / High Volume of New or Uncommon Service Control
Anomalous Connection / New or Uncommon Service Control
Device / New or Unusual Remote Command Execution
Anomalous Connection / SMB Enumeration
Additional Beaconing and Tooling
Device / Initial Breach Chain Compromise
Device / Multiple C2 Model Breaches
Compromise / Large Number of Suspicious Failed Connections
Compromise / Sustained SSL or HTTP Increase
Compromise / SSL or HTTP Beacon
Compromise / Suspicious Beaconing Behavior
Compromise / Large Number of Suspicious Successful Connections
Compromise / High Volume of Connections with Beacon Score
Compromise / Slow Beaconing Activity To External Rare
Compromise / SSL Beaconing to Rare Destination
Compromise / Beaconing Activity To External Rare
Compromise / Beacon to Young Endpoint
Compromise / Agent Beacon to New Endpoint
Anomalous Server Activity / Rare External from Server
Anomalous Connection / Multiple Failed Connections to Rare Endpoint
Anomalous File / EXE from Rare External Location
IoC - Type - Description + Confidence
dataspt[.]com - Hostname - Highly Likely Exfiltration Server
46.22.211[.]151:2022 - IP Address and Unusual Port - Highly Likely Exfiltration Server