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October 30, 2019
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Previewing the 2020 Data Protection Landscape

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30
Oct 2019
To achieve compliance in 2020, human teams need artificial intelligence to make sense of their dynamic digital estates.

From credit card details and medical records, through to private conversations and even dating preferences, the modern consumer entrusts an unprecedented number of organizations with their most sensitive information, hoping against hope that it will be stored on the digital equivalent of Fort Knox.

The reality, however, is that robust data privacy has thus far proven elusive. Almost 13 billion records were breached over the last two years — including from Facebook, Google, and the US Postal Service — demonstrating once again that no network perimeter can keep motivated attackers at bay.

For governments whose principal responsibility is to safeguard their citizens, implementing a strong data protection regime is therefore as challenging as it is critical. At a time when cyber-criminals find vulnerabilities in the most ostensibly airtight systems, these regulators have tended to shy away from mandating concrete security practices, since no one can anticipate which measures will repel the next unpredictable attack. Instead, most data protection laws default to ambiguous calls for “reasonable,” “adequate,” or “appropriate” cyber defenses — language that arguably renders any breached company noncompliant by definition.

While such ambiguity makes prediction pieces like this one speculative to some extent, the coming year will almost certainly witness both an increase in data protection laws around the world as well as a less forgiving interpretation of their requirements. Ultimately, as governments attempt to address growing public concern over data privacy, the mere fact of having suffered a breach could be seen as grounds for significant fines. Avoiding these fines — and doing right by one’s customers — entails assuming that the bad guys will inevitably get past the perimeter.

Figure 1: Noncompliance penalties are only getting larger as the 2020s near. Data source: CSO.

GDPR goes global

The EU’s adoption of the General Data Protection Regulation (GDPR) in April 2016 was the watershed moment in the history of data protection legislation. Its enumeration of individual privacy rights, its 72-hour breach notification requirement, and its broad data protection directives continue to serve as a blueprint for countless others, such as Brazil’s General Data Protection Law (LGPD), Thailand’s Personal Data Protection Act (PDPA), and the California Consumer Privacy Act (CCPA). All three of these regulations become enforceable in 2020, with major ramifications for companies worldwide.

Brazil’s law, which will go into effect on August 15, 2020, is modeled closely after GDPR. Like GDPR, the law applies to all companies that handle the personal data of any of Brazil’s 210 million residents — regardless of where these companies themselves are headquartered. Also like GDPR, of course, the LGPD’s security clauses are open to interpretation. The law compels data handlers to “adopt security, technical, and administrative measures able to protect personal data from unauthorized access,” taking into account “the current state of technology.”

The PDPA in Thailand — effective starting on May 27, 2020 — is similarly vague in mandating unspecified security measures. It parts company, however, in that violators face the possibility of criminal prosecution and even imprisonment for up to one year, in addition to civil damages. Organizations classified as Critical Information Infrastructure (CII), including banks, telecoms, utilities, and hospitals, are regulated under Thailand’s separate Cybersecurity Act and its slightly more detailed obligations.

Figure 2: New GDPR-inspired laws like Brazil’s will turn this map increasingly blue. Image source: DLA Piper.

In California, meanwhile, the CCPA will enforce noncompliance penalties of up to $750 per consumer per incident beginning on the first day of 2020, which could result in multibillion-dollar fines in the case of large-scale breaches. Such precise provisions indicate that GDPR-style legislation is more than a symbolic step toward data protection. And yet, as of August 2019, only 2% of companies reported that they were fully compliant with CCPA, perhaps because, according to a state-commissioned study, California firms will be forced to shell out $55 billion on just their initial compliance efforts.

Checkmate for checkbox compliance

Between the hundreds of data protection fines levied under GDPR and analogous laws, the common thread is that penalized companies are deemed to have suffered a preventable breach. For instance, in the aftermath of the 2017 Equifax compromise that exposed the personal information of more than 140 million consumers, the company was found to have been in violation of the FTC Safeguards Rule, which compelled it to adopt security measures “appropriate to [the] size and complexity” of its digital infrastructure. The US government concluded that the incident was “entirely preventable” had Equifax performed a “routine” security update on the impacted database — an oversight that precipitated at least $1.4 billion in total damages.

However, a closer inspection reveals challenges far deeper than just a simple oversight. Equifax did indeed scan its network for vulnerabilities, but the automated scanner it used was not properly configured to search all of its assets. The truth is that these kinds of misconfigurations and blind spots are a symptom of the conventional approach to cyber security itself, an approach reliant on humans to adjust and monitor a vast array of siloed security tools. In the context of cloud environments designed to be dynamic and IoT devices that are often unbeknownst to the security team, there is nothing routine about defending the “size and complexity” of the modern enterprise.

The upshot of all these new laws, requirements, and fines is that the days of mere checkbox compliance are over. Breached companies can no longer throw up their hands and point to the list of perimeter security tools they had in place, particularly because attackers largely exploit user errors and misconfigurations that — while inevitable — also appear preventable in a vacuum. Rather, to achieve compliance in 2020, human teams need artificial intelligence to make sense of their dynamic digital estates. By learning how each unique user and device normally functions while ‘on the job’, such Cyber AI detects threats that are already inside the perimeter — before they cost the company in court.

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.
Author
Justin Fier
SVP, Red Team Operations

Justin is one of the US’s leading cyber intelligence experts, and holds the position of SVP, Red Team Operations at Darktrace. His insights on cyber security and artificial intelligence have been widely reported in leading media outlets, including the Wall Street Journal, CNN, The Washington Post, and VICELAND. With over 10 years’ experience in cyber defense, Justin has supported various elements in the US intelligence community, holding mission-critical security roles with Lockheed Martin, Northrop Grumman Mission Systems and Abraxas. Justin is also a highly-skilled technical specialist, and works with Darktrace’s strategic global customers on threat analysis, defensive cyber operations, protecting IoT, and machine learning.

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September 26, 2024

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Inside the SOC

Thread Hijacking: How Attackers Exploit Trusted Conversations to Infiltrate Networks

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What is Thread Hijacking?

Cyberattacks are becoming increasingly stealthy and targeted, with malicious actors focusing on high-value individuals to gain privileged access to their organizations’ digital environments. One technique that has gained prominence in recent years is thread hijacking. This method allows attackers to infiltrate ongoing conversations, exploiting the trust within these threads to access sensitive systems.

Thread hijacking typically involves attackers gaining access to a user’s email account, monitoring ongoing conversations, and then inserting themselves into these threads. By replying to existing emails, they can send malicious links, request sensitive information, or manipulate the conversation to achieve their goals, such as redirecting payments or stealing credentials. Because such emails appear to come from a trusted source, they often bypass human security teams and traditional security filters.

How does threat hijacking work?

  1. Initial Compromise: Attackers first gain access to a user’s email account, often through phishing, malware, or exploiting weak passwords.
  2. Monitoring: Once inside, they monitor the user’s email threads, looking for ongoing conversations that can be exploited.
  3. Infiltration: The attacker then inserts themselves into these conversations, often replying to existing emails. Because the email appears to come from a trusted source within an ongoing thread, it bypasses many traditional security filters and raises less suspicion.
  4. Exploitation: Using the trust established in the conversation, attackers can send malicious links, request sensitive information, or manipulate the conversation to achieve their goals, such as redirecting payments or stealing credentials.

A recent incident involving a Darktrace customer saw a malicious actor attempt to manipulate trusted email communications, potentially exposing critical data. The attacker created a new mailbox rule to forward specific emails to an archive folder, making it harder for the customer to notice the malicious activity. This highlights the need for advanced detection and robust preventive tools.

Darktrace’s Self-Learning AI is able to recognize subtle deviations in normal behavior, whether in a device or a Software-as-a-Service (SaaS) user. This capability enables it to detect emerging attacks in their early stages. In this post, we’ll delve into the attacker’s tactics and illustrate how Darktrace / IDENTITY™ successfully identified and mitigated a thread hijacking attempt, preventing escalation and potential disruption to the customer’s network.

Threat hijacking attack overview & Darktrace coverage

On August 8, 2024, Darktrace detected an unusual email received by a SaaS account on a customer’s network. The email appeared to be a reply to a previous chain discussing tax and payment details, likely related to a transaction between the customer and one of their business partners.

Headers of the suspicious email received.
Figure 1: Headers of the suspicious email received.

A few hours later, Darktrace detected the same SaaS account creating a new mailbox rule named “.”, a tactic commonly used by malicious actors to evade detection when setting up new email rules [2]. This rule was designed to forward all emails containing a specific word to the user’s “Archives” folder. This evasion technique is typically used to move any malicious emails or responses to a rarely opened folder, ensuring that the genuine account holder does not see replies to phishing emails or other malicious messages sent by attackers [3].

Darktrace recognized the newly created email rule as suspicious after identifying the following parameters:

  • AlwaysDeleteOutlookRulesBlob: False
  • Force: False
  • MoveToFolder: Archive
  • Name: “.”
  • FromAddressContainsWords: [Redacted]
  • MarkAsRead: True
  • StopProcessingRules: True

Darktrace also noted that the user attempting to create this new email rule had logged into the SaaS environment from an unusual IP address. Although the IP was located in the same country as the customer and the ASN used by the malicious actor was typical for the customer’s network, the rare IP, coupled with the anomalous behavior, raised suspicions.

Figure 2: Hijacked SaaS account creating the new mailbox rule.

Given the suspicious nature of this activity, Darktrace’s Security Operations Centre (SOC) investigated the incident and alerted the customer’s security team of this incident.

Due to a public holiday in the customer's location (likely an intentional choice by the threat actor), their security team did not immediately notice or respond to the notification. Fortunately, the customer had Darktrace's Autonomous Response capability enabled, which allowed it to take action against the suspicious SaaS activity without human intervention.

In this instance, Darktrace swiftly disabled the seemingly compromised SaaS user for 24 hours. This action halted the spread of the compromise to other accounts on the customer’s SaaS platform and prevented any sensitive data exfiltration. Additionally, it provided the security team with ample time to investigate the threat and remove the user from their environment. The customer also received detailed incident reports and support through Darktrace’s Security Operations Support service, enabling direct communication with Darktrace’s expert Analyst team.

Conclusion

Ultimately, Darktrace’s anomaly-based detection allowed it to identify the subtle deviations from the user’s expected behavior, indicating a potential compromise on the customer’s SaaS platform. In this case, Darktrace detected a login to a SaaS platform from an unusual IP address, despite the attacker’s efforts to conceal their activity by using a known ASN and logging in from the expected country.

Despite the attempted SaaS hijack occurring on a public holiday when the customer’s security team was likely off-duty, Darktrace autonomously detected the suspicious login and the creation of a new email rule. It swiftly blocked the compromised SaaS account, preventing further malicious activity and safeguarding the organization from data exfiltration or escalation of the compromise.

This highlights the growing need for AI-driven security capable of responding to malicious activity in the absence of human security teams and detect subtle behavioral changes that traditional security tools.

Credit to: Ryan Traill, Threat Content Lead for his contribution to this blog

Appendices

Darktrace Model Detections

SaaS / Compliance / Anomalous New Email Rule

Experimental / Antigena Enhanced Monitoring from SaaS Client Block

Antigena / SaaS / Antigena Suspicious SaaS Activity Block

Antigena / SaaS / Antigena Email Rule Block

References

[1] https://blog.knowbe4.com/whats-the-best-name-threadjacking-or-man-in-the-inbox-attacks

[2] https://darktrace.com/blog/detecting-attacks-across-email-saas-and-network-environments-with-darktraces-combined-ai-approach

[3] https://learn.microsoft.com/en-us/defender-xdr/alert-grading-playbook-inbox-manipulation-rules

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About the author
Maria Geronikolou
Cyber Analyst

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September 26, 2024

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How AI can help CISOs navigate the global cyber talent shortage

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The global picture

4 million cybersecurity professionals are needed worldwide to protect and defend the digital world – twice the number currently in the workforce.1

Innovative technologies are transforming business operations, enabling access to new markets, personalized customer experiences, and increased efficiency. However, this digital transformation also challenges Security Operations Centers (SOCs) with managing and protecting a complex digital environment without additional resources or advanced skills.

At the same time, the cybersecurity industry is suffering a severe global skills shortage, leaving many SOCs understaffed and under-skilled. With a 72% increase in data breaches from 2021-20232, SOCs are dealing with overwhelming alert volumes from diverse security tools. Nearly 60% of cybersecurity professionals report burnout3, leading to high turnover rates. Consequently, only a fraction of alerts are thoroughly investigated, increasing the risk of undetected breaches. More than half of organizations that experienced breaches in 2024 admitted to having short-staffed SOCs.4

How AI can help organizations do more with less

Cyber defense needs to evolve at the same pace as cyber-attacks, but the global skills shortage is making that difficult. As threat actors increasingly abuse AI for malicious purposes, using defensive AI to enable innovation and optimization at scale is reshaping how organizations approach cybersecurity.

The value of AI isn’t in replacing humans, but in augmenting their efforts and enabling them to scale their defense capabilities and their value to the organization. With AI, cybersecurity professionals can operate at digital speed, analyzing vast data sets, identifying more vulnerabilities with higher accuracy, responding and triaging faster, reducing risks, and implementing proactive measures—all without additional staff.

Research indicates that organizations leveraging AI and automation extensively in security functions—such as prevention, detection, investigation, or response—reduced their average mean time to identify (MTTI) and mean time to contain (MTTC) data breaches by 33% and 43%, respectively. These organizations also managed to contain breaches nearly 100 days faster on average compared to those not using AI and automation.5

First, you've got to apply the right AI to the right security challenge. We dig into how different AI technologies can bridge specific skills gaps in the CISO’s Guide to Navigating the Cybersecurity Skills Shortage.

Cases in point: AI as a human force multiplier

Let’s take a look at just some of the cybersecurity challenges to which AI can be applied to scale defense efforts and relieve the burden on the SOC. We go further into real-life examples in our white paper.

Automated threat detection and response

AI enables 24/7 autonomous response, eliminating the need for after-hours SOC shifts and providing security leaders with peace of mind. AI can scale response efforts by analyzing vast amounts of data in real time, identifying anomalies, and initiating precise autonomous actions to contain incidents, which buys teams time for investigation and remediation.  

Triage and investigation

AI enhances the triage process by automatically categorizing and prioritizing security alerts, allowing cybersecurity professionals to focus on the most critical threats. It creates a comprehensive picture of an attack, helps identify its root cause, and generates detailed reports with key findings and recommended actions.  

Automation also significantly reduces overwhelming alert volumes and high false positive rates, enabling analysts to concentrate on high-priority threats and engage in more proactive and strategic initiatives.

Eliminating silos and improving visibility across the enterprise

Security and IT teams are overwhelmed by the technological complexity of operating multiple tools, resulting in manual work and excessive alerts. AI can correlate threats across the entire organization, enhancing visibility and eliminating silos, thereby saving resources and reducing complexity.

With 88% of organizations favoring a platform approach over standalone solutions, many are consolidating their tech stacks in this direction. This consolidation provides native visibility across clouds, devices, communications, locations, applications, people, and third-party security tools and intelligence.

Upskilling your existing talent in AI

As revealed in the State of AI Cybersecurity Survey 2024, only 26% of cybersecurity professionals say they have a full understanding of the different types of AI in use within security products.6

Understanding AI can upskill your existing staff, enhancing their expertise and optimizing business outcomes. Human expertise is crucial for the effective and ethical integration of AI. To enable true AI-human collaboration, cybersecurity professionals need specific training on using, understanding, and managing AI systems. To make this easier, the Darktrace ActiveAI Security Platform is designed to enable collaboration and reduce the learning curve – lowering the barrier to entry for junior or less skilled analysts.  

However, to bridge the immediate expertise gap in managing AI tools, organizations can consider expert managed services that take the day-to-day management out of the SOC’s hands, allowing them to focus on training and proactive initiatives.

Conclusion

Experts predict the cybersecurity skills gap will continue to grow, increasing operational and financial risks for organizations. AI for cybersecurity is crucial for CISOs to augment their teams and scale defense capabilities with speed, scalability, and predictive insights, while human expertise remains vital for providing the intuition and problem-solving needed for responsible and efficient AI integration.

If you’re thinking about implementing AI to solve your own cyber skills gap, consider the following:

  • Select an AI cybersecurity solution tailored to your specific business needs
  • Review and streamline existing workflows and tools – consider a platform-based approach to eliminate inefficiencies
  • Make use of managed services to outsource AI expertise
  • Upskill and reskill existing talent through training and education
  • Foster a knowledge-sharing culture with access to knowledge bases and collaboration tools

Interested in how AI could augment your SOC to increase efficiency and save resources? Read our longer CISO’s Guide to Navigating the Cybersecurity Skills Shortage.

And to better understand cybersecurity practitioners' attitudes towards AI, check out Darktrace’s State of AI Cybersecurity 2024 report.

References

  1. https://www.isc2.org/research  
  2. https://www.forbes.com/advisor/education/it-and-tech/cybersecurity-statistics/  
  3. https://www.informationweek.com/cyber-resilience/the-psychology-of-cybersecurity-burnout  
  4. https://www.ibm.com/downloads/cas/1KZ3XE9D  
  5. https://www.ibm.com/downloads/cas/1KZ3XE9D  
  6. https://darktrace.com/resources/state-of-ai-cyber-security-2024
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