This blog discusses the consequences and challenges associated with compliance, and how Darktrace’s AI not only defends against double extortion ransomware, but also builds internal mechanisms that help enforce compliance across the workforce.
Compliance regulations like CCPA and GDPR are created with good intentions. They aim to secure user data, ensure privacy, and build trust between the companies and consumers. However, these regulations have become a double-edged sword for many organizations.
One reason for this is the rise of double extortion ransomware, where data is exfiltrated before files are encrypted. In this scenario, threat actors threaten to release sensitive company information online if the ransom is not paid. Companies can face hefty fines if they fail to comply with regulation, and thus they are pressured into paying the ransom just to keep the breach quiet.
Consequences of non-compliance
Today’s businesses face a range of demanding privacy regulations that are frequently being updated. This includes General Data Protection Regulation, or GDPR, the California Consumer Privacy Act, or CCPA, and regulations from the New York State Department Of Financial Services, or NYDFS.
With the shift to remote and dynamic working, and the ever-increasing complexity of business operations, there has been great pressure for companies to upgrade infrastructure and ensure that they are meeting all regulations.
Non-compliance can lead to significant financial penalties and drawn-out legal actions. If organizations fail to protect their data, the fees can be disastrous. GDPR can fine companies up to €20 million, or 4% of a company’s annual global turnover. For example, since 2017, Google has been fined a combined total of $9.5 billion by EU regulators.
Weaponization of compliance
Ultimately, compliance serves the important purpose of giving citizens more control and rights over their data. However, cyber-criminals have realized that they can use the threat of non-compliance as a pressure point against organizations. Stolen data, if released to the public, can lead to huge regulatory fines.
We have seen this phenomenon in double extortion ransomware attacks, where threat actors steal sensitive data before they encrypt the files. Moreover, several ransomware actors, such as the Babuk gang, now have begun to forsake encryption in favor of extortion. This is because threat actors realize that exfiltration is more effective when many organizations continually back up files as a precaution against the threat of ransomware locking down files.
Ransomware actors often auction intellectual property, customer data, and company secrets on the Dark Web. The Maze ransomware group established this trend back when it created a website in late 2019 to publicly ‘name and shame’ organizations that had been compromised. These attacks included theft of information such as stolen PDF files, in addition to IP addresses and device names which were then uploaded and made publicly available on its website.
Over 70% of ransomware attacks now involve exfiltration.
The tactic was made infamous by the cyber-criminal group REvil, who publicly announced their intentions on a Russian hacker forum in December 2019:
“Each attack is accompanied by a copy of commercial information. In case of refusal of payment, the data will either be sold to competitors or laid out in open sources. GDPR. Do not want to pay us – pay x10 more to the government. No problems.”
In these cases, threat actors are essentially saying, ‘if you pay us this small ransom, we will keep your data safe. If you don’t pay us, we have the power to release your data, and then you can take your chances with a huge compliance fine.’
Organizations may prefer to negotiate with cyber-criminals and keep the breach – or threat of breach – quiet. This is what the ransomware attackers are banking on.
How AI can help: Stopping ransomware and strengthening compliance
Compliance fines are not cheap. It took over three years of legal proceedings for Equifax to settle their 2017 data breach. They finally settled with paying $700 million to regulators, including the Federal Trade Commission and the Consumer Financial Protection Bureau (CFPB). Home Depot and Uber have also famously faced financial penalties of hundreds of millions of dollars.
These regulatory fines are compounding the potential consequences of ransomware. The continued ability of attackers to adapt and find new weaknesses means that it is crucial for companies to identify and contain ransomware in its earliest stages, with machine speed and precision.
Darktrace’s AI has achieved this repeatedly, such as when a WastedLocker intrusion was stopped before the ransomware was deployed. By constantly evolving its understanding of the organization, Cyber AI detects and automatically investigates all unusual activity across the enterprise and can respond autonomously in real time to stop threats in their tracks.
Figure 1: Darktrace’s customizable CCPA tags allow for specialized alerting on activity related to personal data as defined by CCPA
Furthermore, Darktrace’s technology can be used to action specific types of alerts based on different compliance threat models. For instance, businesses seeking to ensure compliance with CCPA requirements can use a specific ‘CCPA Tag’ for certain devices which have, or are likely to have, consumer data subject to the CCPA. When relevant data from the tagged devices leaves the environment or is involved in any abnormal activity, Darktrace’s AI detects this immediately and automatically launches an investigation into the incident.
With a proven ability to protect against machine-speed threats, and the ability to strengthen compliance with customizable alerts, the Darktrace Immune System platform provides a powerful defense against double extortion ransomware.
Under pressure
Compliance is just one of the many strategic concerns facing ransomware victims. In addition to customer trust, valuable IP, and long-term reputation, attackers and defenders are in a constant ‘cat and mouse’ game, such that threat actors will continue to seek out new pressure points to extort their targets.
Figure 2: Current varieties of double extortion ransomware
Organizations accordingly will benefit from using sophisticated technologies that neutralize ransomware before it has encrypted or exfiltrated files, stopping advanced threats in their earliest stages.
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Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
AUTHOR
ABOUT ThE AUTHOR
Mariana Pereira
VP, Cyber Innovation
Mariana is the VP of Cyber Innovation at Darktrace, and works closely with the development, analyst, and marketing teams to advise technical and non-technical audiences on how best to augment cyber resilience, and how to implement AI technology as a means of defense. She speaks regularly at international events, with a specialism in presenting on sophisticated, AI-powered email attacks. She holds an MBA from the University of Chicago, and speaks several languages including French, Italian, and Portuguese.
Darktrace has been named as Microsoft UK Partner of the Year for 2024! The Microsoft Partner Awards recognize winners for their commitment to customers, impact of solutions, and exemplary use of Microsoft technologies.
Whilst the award was granted based on our innovations combining Darktrace/Email and Microsoft Defender for Office 365, our shared values go beyond technology. Darktrace stood out for the integration of our products to deliver exceptional security value to customers, as well as our investment in partnerships, marketplace and go to market. Microsoft was also impressed with our strong commitment to diversity and inclusion and our broader contribution to both the UK economy and the UK tech sector.
Microsoft Defender for Office 365 + Darktrace/Email leave attackers nowhere to hide
The email threat landscape is constantly evolving. Attacks are becoming more sophisticated, more targeted and increasing in multi-stage payload attacks. Across the Darktrace customer base in 2023 alone, we have seen a 135% increase in ‘novel social engineering attacks’, corresponding with the rise of ChatGPT, 45% of phishing emails were identified as spear phishing attempts and a 59% increase in multi-stage payload attacks.
Legacy defenses were built to address a high volume of unsophisticated attacks, but generative AI has shifted the threats towards lower quantity yet very sophisticated, high impact targeted attacks. Microsoft Defender for Office 365’s rapid innovation has outpaced the Secure Email Gateway’s rule and signature based historical data approach. Customers no longer need email gateways which duplicate workflows and add expense native to their Defender for O365 solution.
Point email solutions overlap with Microsoft in 3 key areas: detection approach, workflows, capabilities
Detection - Microsoft receives trillions threat signals daily, giving customers the broadest scope of the attack landscape. Darktrace combined with Microsoft unites business and attack centric approaches
Workflows – any Microsoft configurations are reflected automatically in Darktrace/Email. Users can keep daily workflow in Microsoft, while a traditional SEG requires duplicated workflows
Capabilities – Microsoft handles foundational elements like archiving/encryption/signature matching while Darktrace handles advanced threat security
Darktrace/Email is built to elevate, not duplicate, Microsoft email security – removing the burden of operating legacy point solutions and blocking 25% more threats. Robust account takeover protections to stop the 38% of sophisticated threats other tools miss. Customers can seamlessly correlate activity and insights across Microsoft email, DMARC and Teams to stop threats on average 13 days earlier.
Azure Marketplace
Microsoft Azure customers can access Darktrace in the Azure Marketplace to take advantage of the scalability, reliability, and agility of Azure to drive rapid IT operations and security integrations across the enterprise. Customers can leverage their Microsoft Azure Consumption Commitments (MACC), making procurement simple. As UK Partner of the Year winner, customers know they have a trusted partner with Darktrace and a proven solution to work seamlessly with Azure.
Following up on our Conversation: Detecting & Containing a LinkedIn Phishing Attack with Darktrace
25
Jun 2024
Note: Real organization, domain and user names have been modified and replaced with fictitious names to maintain anonymity.
Social media cyber-attacks
Social media is a known breeding ground for cyber criminals to easily connect with a near limitless number of people and leverage the wealth of personal information shared on these platforms to defraud the general public. Analysis suggests even the most tech savvy ‘digital natives’ are vulnerable to impersonation scams over social media, as criminals weaponize brands and trends, using the promise of greater returns to induce sensitive information sharing or fraudulent payments [1].
LinkedIn phishing
As the usage of a particular social media platform increases, cyber criminals will find ways to exploit the increasing user base, and this trend has been observed with the rise in LinkedIn scams in recent years [2]. LinkedIn is the dominant professional networking site, with a forecasted 84.1million users by 2027 [3]. This platform is data-driven, so users are encouraged to share information publicly, including personal life updates, to boost visibility and increase job prospects [4] [5]. While this helps legitimate recruiters to gain a good understanding of the user, an attacker could also leverage the same personal content to increase the sophistication and success of their social engineering attempts.
Darktrace detection of LinkedIn phishing
Darktrace detected a Software-as-a-Service (SaaS) compromise affecting a construction company, where the attack vector originated from LinkedIn (outside the monitoring of corporate security tools), but then pivoted to corporate email where a credential harvesting payload was delivered, providing the attacker with credentials to access a corporate file storage platform.
Because LinkedIn accounts are typically linked to an individual’s personal email and are most commonly accessed via the mobile application [6] on personal devices that are not monitored by security teams, it can represent an effective initial access point for attackers looking to establish an initial relationship with their target. Moreover, user behaviors to ignore unsolicited emails from new or unknown contacts are less frequently carried over to platforms like LinkedIn, where interactions with ‘weak ties’ as opposed to ‘strong ties’ are a better predictor of job mobility [7]. Had this attack been allowed to continue, the threat actor could have leveraged access to further information from the compromised business cloud account to compromise other high value accounts, exfiltrate sensitive data, or defraud the organization.
LinkedIn phishing attack details
Reconnaissance
The initial reconnaissance and social engineering occurred on LinkedIn and was thus outside the purview of corporate security tools, Darktrace included.
However, the email domain “hausconstruction[.]com” used by the attacker in subsequent communications appears to be a spoofed domain impersonating a legitimate construction company “haus[.]com”, suggesting the attacker may have also impersonated an employee of this construction company on LinkedIn. In addition to spoofing the domain, the attacker seemingly went further to register “hausconstruction.com” on a commercial web hosting platform. This is a technique used frequently not just to increase apparent legitimacy, but also to bypass traditional security tools since newly registered domains will have no prior threat intelligence, making them more likely to evade signature and rules-based detections [8]. In this instance, open-source intelligence (OSINT) sources report that the domain was created several months earlier, suggesting this may have been part of a targeted attack on construction companies.
Initial Intrusion
It was likely that during the correspondence over LinkedIn, the target user was solicited into following up over email regarding a prospective construction project, using their corporate email account. In a probable attempt to establish a precedent of bi-directional correspondence so that subsequent malicious emails would not be flagged by traditional security tools, the attacker did not initially include suspicious links, attachments or use solicitous or inducive language within their initial emails.
Figure 1: Example of bi-directional email correspondence between the target and the attacker impersonating a legitimate employee of the construction company haus.com.
Figure 2: Cyber AI Analyst investigation into one of the initial emails the target received from the attacker.
To accomplish the next stage of their attack, the attacker shared a link, hidden behind the inducing text “VIEW ALL FILES”, to a malicious file using the Hightail cloud storage service. This is also a common method employed by attackers to evade detection, as this method of file sharing does not involve attachments that can be scanned by traditional security tools, and legitimate cloud storage services are less likely to be blocked.
OSINT analysis on the malicious link link shows the file hosted on Hightail was a HTML file with the associated message “Following up on our LinkedIn conversation”. Further analysis suggests the file contained obfuscated Javascript that, once opened, would automatically redirect the user to a malicious domain impersonating a legitimate Microsoft login page for credential harvesting purposes.
Figure 3: The malicious HTML file containing obfuscated Javascript, where the highlighted string references the malicious credential harvesting domain.
Figure 4: Screenshot of fraudulent Microsoft Sign In page hosted on the malicious credential harvesting domain.
Although there was prior email correspondence with the attacker, this email was not automatically deemed safe by Darktrace and was further analyzed for unusual properties and unusual communications for the recipient and the recipient’s peer group.
Darktrace determined that:
It was unusual for this file storage solution to be referenced in communications to the user and the wider network
Textual properties of the email body suggested a high level of inducement from the sender, with a high level of focus on the phishing link.
The full link contained suspicious properties suggesting it is high risk.
Figure 5: Darktrace’s analysis of the phishing email, presenting key information about the unusual characteristics of this email, information on highlighted content, and an overview of actions that were initially applied.
Based on these anomalies, Darktrace initially moved the phishing email to the junk folder and locked the link, preventing the user from directly accessing the malicious file hosted on Hightail. However, the customer’s security team released the email, likely upon end-user request, allowing the target user to access the file and ultimately enter their credentials into that credential harvesting domain.
Figure 6: Darktrace alerts triggered by the malicious phishing email and the corresponding Autonomous Response actions.
Lateral Movement
Correspondence between the attacker and target continued for two days after the credential harvesting payload was delivered. Five days later, Darktrace detected an unusual login using multi-factor authentication (MFA) from a rare external IP and ASN that coincided with Darktrace/Email logs showing access to the credential harvesting link.
This attempt to bypass MFA, known as an Office365 Shell WCSS attack, was likely achieved by inducing the target to enter their credentials and legitimate MFA token into the fake Microsoft login page. This was then relayed to Microsoft by the attacker and used to obtain a legitimate session. The attacker then reused the legitimate token to log into Exchange Online from a different IP and registered the compromised device for MFA.
Figure 7: Screenshot within Darktrace/Email of the phishing email that was released by the security team, showing the recipient clicked the link to file storage where the malicious payload was stored.
Figure 8: Event Log showing a malicious login and MFA bypass at 17:57:16, shortly after the link was clicked. Highlighted in green is activity from the legitimate user prior to the malicious login, using Edge. Highlighted in orange and red is the malicious activity using Chrome.
The IP addresses used by the attacker appear to be part of anonymization infrastructure, but are not associated with any known indicators of compromise (IoCs) that signature-based detections would identify [9] [10].
In addition to logins being observed within half an hour of each other from multiple geographically impossible locations (San Francisco and Phoenix), the unexpected usage of Chrome browser, compared to Edge browser previously used, provided Darktrace with further evidence that this activity was unlikely to originate from the legitimate user. Although the user was a salesperson who frequently travelled for their role, Darktrace’s Self-Learning AI understood that the multiple logins from these locations was highly unusual at the user and group level, and coupled with the subsequent unexpected account modification, was a likely indicator of account compromise.
Accomplish mission
Although the email had been manually released by the security team, allowing the attack to propagate, additional layers of defense were triggered as Darktrace's Autonomous Response initiated “Disable User” actions upon detection of the multiple unusual logins and the unauthorized registration of security information.
However, the customer had configured Autonomous Response to require human confirmation, therefore no actions were taken until the security team manually approved them over two hours later. In that time, access to mail items and other SharePoint files from the unusual IP address was detected, suggesting a potential loss of confidentiality to business data.
Figure 9: Advanced Search query showing several FilePreviewed and MailItemsAccessed events from either the IPs used by the attacker, or using the software Chrome. Note some of the activity originated from Microsoft IPs which may be whitelisted by traditional security tools.
However, it appears that the attacker was able to maintain access to the compromised account, as login and mail access events from 199.231.85[.]153 continued to be observed until the afternoon of the next day.
Conclusion
This incident demonstrates the necessity of AI to security teams, with Darktrace’s ActiveAI Security Platform detecting a sophisticated phishing attack where human judgement fell short and initiated a real-time response when security teams could not physically respond as fast.
Security teams are very familiar with social engineering and impersonation attempts, but these attacks remain highly prevalent due to the widespread adoption of technologies that enable these techniques to be deployed with great sophistication and ease. In particular, the popularity of information-rich platforms like LinkedIn that are geared towards connecting with unknown people make it an attractive initial access point for malicious attackers.
In the second half of 2023 alone, over 200 thousand fake profiles were reported by members on LinkedIn [11]. Fake profiles can be highly sophisticated, use professional images, contain compelling descriptions, reference legitimate company listings and present believable credentials.
It is unrealistic to expect end users to defend themselves against such sophisticated impersonation attempts. Moreover, it is extremely difficult for human defenders to recognize every fraudulent interaction amidst a sea of fake profiles. Instead, defenders should leverage AI, which can conduct autonomous investigations without human biases and limitations. AI-driven security can ensure successful detection of fraudulent or malicious activity by learning what real users and devices look like and identifying deviations from their learned behaviors that may indicate an emerging threat.
Appendices
Darktrace Model Detections
DETECT/ Apps
SaaS / Compromise / SaaS Anomaly Following Anomalous Login
SaaS / Compromise / Unusual Login and Account Update
