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Machine Learning Is Helping To Stop Security Breaches With Threat Analytics

Bottom Line: Machine learning is enabling threat analytics to deliver greater precision regarding the risk context of privileged users’ behavior, creating notifications of risky activity in real time, while also being able to actively respond to incidents by cutting off sessions, adding additional monitoring, or flagging for forensic follow-up.

Separating Security Hacks Fact from Fiction

It’s time to demystify the scale and severity of breaches happening globally today. A commonly-held misconception or fiction is that millions of hackers have gone to the dark side and are orchestrating massive attacks on any and every business that is vulnerable. The facts are far different and reflect a much more brutal truth, which is that businesses make themselves easy to hack into by not protecting their privileged access credentials. Cybercriminals aren’t expending the time and effort to hack into systems; they’re looking for ingenious ways to steal privileged access credentials and walk in the front door. According to Verizon’s 2019 Data Breach Investigations Report, ‘Phishing’ (as a pre-cursor to credential misuse), ‘Stolen Credentials’, and ‘Privilege Abuse’ account for the majority of threat actions in breaches (see page 9 of the report).

It only really takes one compromised credential to potentially impact millions — whether it’s millions of individuals or millions of dollars. Undeniably, identities and the trust we place in them are being used against us. They have become the Achilles heel of our cybersecurity practices. According to a recent study by Centrify among 1,000 IT decision makers, 74% of respondents whose organizations have been breached acknowledged that it involved access to a privileged account. This number closely aligns with Forrester Research’s estimate “that at least 80% of data breaches . . . [involved] compromised privileged credentials, such as passwords, tokens, keys, and certificates.”

While the threat actors might vary according to Verizon’s 2019 Data Breach Investigations Report, the cyber adversaries’ tactics, techniques, and procedures are the same across the board. Verizon found that the fastest growing source of threats are from internal actors, as the graphic from the study illustrates below:


Internal actors are the fastest growing source of breaches because they’re able to obtain privileged access credentials with minimal effort, often obtaining them through legitimate access requests to internal systems or harvesting their co-workers’ credentials by going through the sticky notes in their cubicles. Privileged credential abuse is a challenge to detect as legacy approaches to cybersecurity trust the identity of the person using the privileged credentials. In effect, the hacker is camouflaged by the trust assigned to the privileged credentials they have and can roam internal systems undetected, exfiltrating sensitive data in the process.

The reality is that many breaches can be prevented by some of the most basic Privileged Access Management (PAM) tactics and solutions, coupled with a Zero Trust approach. Most organizations are investing the largest chunk of their security budget on protecting their network perimeter rather than focusing on security controls, which can affect positive change to protect against the leading attack vector: privileged access abuse.

The bottom line is that investing in securing perimeters leaves the most popular attack vector of all unprotected, which are privileged credentials. Making PAM a top priority is crucial to protect any business’ most valuable asset; it’s systems, data, and the intelligence they provide. Gartner has listed PAM on its Top 10 Security Projects for the past two years for a good reason.

Part of a cohesive PAM strategy should include machine learning-based threat analytics to provide an extra layer of security that goes beyond a password vault, multi-factor authentication (MFA), or privilege elevation.

How Machine Learning and Threat Analytics Stop Privileged Credential Abuse 

Machine learning algorithms enable threat analytics to immediately detect anomalies and non-normal behavior by tracking login behavioral patterns, geolocation, and time of login, and many more variables to calculate a risk score. Risk scores are calculated in real-time and define if access is approved, if additional authentication is needed, or if the request is blocked entirely.

Machine learning-based threat analytics also provide the following benefits:

  • New insights into privileged user access activity based on real-time data related to unusual recent privilege change, the command runs, target accessed, and privilege elevation.
  • Gain greater understanding and insights into the specific risk nature of specific events, computing a risk score in real time for every event expressed as high, medium, or low level for any anomalous activity.
  •  Isolate, identify, and track which security factors triggered an anomaly alert.
  • Capture, play, and analyze video sessions of anomalous events within the same dashboard used for tracking overall security activity.
  • Create customizable alerts that provide context-relevant visibility and session recording and can also deliver notifications of anomalies, all leading to quicker, more informed investigative action.

What to Look for In Threat Analytics 
Threat analytics providers are capitalizing on machine learning to improve the predictive accuracy and usability of their applications continually. What’s most important is for any threat analytics application or solution you’re considering to provide context-aware access decisions in real time. The best threat analytics applications on the market today are using machine learning as the foundation of their threat analytics engine. These machine learning-based engines are very effective at profiling the normal behavior pattern for any user on any login attempt, or any privileged activity including commands, identifying anomalies in real time to enable risk-based access control. High-risk events are immediately flagged, alerted, notified, and elevated to IT’s attention, speeding analysis, and greatly minimizing the effort required to assess risk across today’s hybrid IT environments.

The following is the minimum set of features to look for in any privilege threat analytics solution:

  • Immediate visibility with a flexible, holistic view of access activity across an enterprise-wide IT network and extended partner ecosystem. Look for threat analytics applications that provide dashboards and interactive widgets to better understand the context of IT risk and access patterns across your IT infrastructure. Threat analytics applications that give you the flexibility of tailoring security policies to every user’s behavior and automatically flagging risky actions or access attempts, so that you’ll gain immediate visibility into account risk, eliminating the overhead of sifting through millions of log files and massive amounts of historical data.
  • They have intuitively designed and customizable threat monitoring and investigation screens, workflows, and modules. Machine learning is enabling threat analytics applications to deliver more contextually-relevant and data-rich insights than has ever been possible in the past. Look for threat analytics vendors who offer intuitively designed and customizable threat monitoring features that provide insights into anomalous activity with a detailed timeline view. The best threat analytics vendors can identify the specific factors contributing to an anomaly for a comprehensive understanding of a potential threat, all from a single console. Security teams can then view system access, anomaly detection in high resolutions with analytics tools such as dashboards, explorer views, and investigation tools.
  • Must provide support for easy integration to Security Information and Event Management (SIEM) tools. Privileged access data is captured and stored to enable querying by log management and SIEM reporting tools. Make sure any threat analytics application you’re considering has installed, and working integrations with SIEM tools and platforms such as Micro Focus® ArcSight™, IBM® QRadar™, and Splunk® to identify risks or suspicious activity quickly.
  • Must Support Alert Notification by Integration with Webhook-Enabled Endpoints. Businesses getting the most value out of their threat analytics applications are integrating with Slack or existing onboard incident response systems such as PagerDuty to enable real-time alert delivery, eliminating the need for multiple alert touch points and improving time to respond. When an alert event occurs, the threat analytics engine allows the user to send alerts into third-party applications via Webhook. This capability enables the user to respond to a threat alert and contain the impact of a breach attempt.

Conclusion 
CentrifyForresterGartner, and Verizon each have used different methodologies and reached the same conclusion from their research: privileged access abuse is the most commonly used tactic for hackers to exfiltrate sensitive data. Breaches based on privileged credential abuse are extremely difficult to stop, as these credentials often have the greatest levels of trust and access rights associated with them. Leveraging threat analytics applications using machine learning that is adept at finding anomalies in behavioral data and thwarting a breach by denying access is proving very effective against privileged credential abuse.

Companies, including Centrify, use risk scoring combined with adaptive MFA to empower a least-privilege access approach based on Zero Trust. This Zero Trust Privilege approach verifies who or what is requesting privileged access, the context behind the request, and the risk of the access environment to enforce least privilege. These are the foundations of Zero Trust Privilege and are reflected in how threat analytics apps are being created and improved today.

How To Secure Mobile Devices In A Zero Trust World

  • 86% of enterprises are seeing mobile threats growing the fastest this year, outpacing other threat types.
  • 48% say they’ve sacrificed security to “get the job done” up from 32% last year.
  • 41% of those affected say the compromise is having major with lasting repercussions and 43% said that their efforts to remediate the attacks were “difficult and expensive.”

Bottom Line: The majority of enterprises, 67%, are the least confident in the security of their mobile assets than any other device or platform today according to Verizon’s Mobile Security Index 2019.

Why Mobile Devices Are the Fastest Growing Threat Surface Today     

Verizon found that 86% of enterprises see an upswing in the number, scale, and scope of mobile breach attempts in 2019. When broken out by industry, Financial Services, Professional Services, and Education are the most commonly targeted industries as the graphic below shows:

The threat surfaces every organization needs to protect is exponentially increasing today based on the combination of employee- and company-owned mobile devices. 41% of enterprises rate mobile devices as their most vulnerable threat surface this year:

Passwords and Mobile Devices Have Become A Hacker’s Paradise

“The only people who love usernames and passwords are hackers,” said Alex Simons, corporate vice president at Microsoft’s identity division in a recent Wall Street Journal article, Username and Password Hell: Why the Internet Can’t Keep You Logged In. Verizon found that mobile devices are the most vulnerable, fastest-growing threat surface there is, making it a favorite with state-sponsored and organized crime syndicates. How rapidly mobile devices are proliferating in enterprises today frequently outpace their ability to secure them, falling back on legacy Privileged Access Management (PAM) approaches that hacking syndicates know how to get around easily using compromised passwords and privileged access credentials. Here’s proof of how much of a lucrative paradise it is for hackers to target passwords and mobile devices first:

  • Hacker’s favorite way to gain access to any business is by using privileged access credentials, which are increasingly being harvested from cellphones using malware. Hacking organizations would rather walk in the front door of any organizations’ systems rather than expend the time and effort to hack in. It’s by far the most popular approach with hackers, with 74% of IT decision makers whose organizations have been breached in the past say it involved privileged access credential abuse according to a recent Centrify survey, Privileged Access Management in the Modern Threatscape. Only 48% of the organizations have a password vault, and just 21% have multi-factor authentication (MFA) implemented for privileged administrative access. The Verizon study found that malware is the most common strategy hackers use to gain access to corporate networks. MobileIron’s Global Threat Report, mid-year 2018 found that 3.5% of Android devices are harboring known malware. Of these malicious apps, over 80% had access to internal networks and were scanning nearby ports. This suggests that the malware was part of a larger attack.

Securing Mobile Devices In A Zero Trust World Needs To Happen Now

Mobile devices are an integral part of everyone’s identity today. They are also the fastest growing threat surface for every business – making identities the new security perimeter. Passwords are proving to be problematic in scaling fast enough to protect these threat surfaces, as credential abuse is skyrocketing today. They’re perennial best-sellers on the Dark Web, where buyers and sellers negotiate in bitcoin for companies’ logins and passwords – often with specific financial firms, called out by name in “credentials wanted” ads. Organizations are waking up to the value of taking a Zero Trust approach to securing their businesses, which is a great start. Passwords are still the most widely relied-on security mechanism – and continue to be the weakest link in today’s enterprise security.  That needs to change. According to the Wall Street Journal, the World Wide Web Consortium has recently ratified a standard called WebAuthN, which allows websites to authenticate users with biometric information, or physical objects like security keys, and skip passwords altogether.

MobileIron is also taking a unique approach to this challenge by introducing zero sign-on (ZSO), built on the company’s unified endpoint management (UEM) platform and powered by the MobileIron Access solution. “By making mobile devices your identity, we create a world free from the constant pains of password recovery and the threat of data breaches due to easily compromised credentials,” wrote Simon Biddiscombe, MobileIron’s President and Chief Executive Officer in his recent blog post, Single sign-on is still one sign-on too many. Simon’s latest post MobileIron: We’re making history by making passwords history, provides the company’s vision going forward with ZSO. Zero sign-on eliminates passwords as the primary method for user authentication, unlike single sign-on, which still requires at least one username and password. MobileIron paved the way for a zero sign-on enterprise with its Access product in 2017, which enabled zero sign-on to cloud services on managed devices.

Conclusion

Mobile devices are the most quickly proliferating threat surface there are today and an integral part of everyone’s identities as well. Thwarting the many breach attempts attempted daily over mobile devices and across all threat surfaces needs to start with a solid Zero Trust framework. MobileIron’s introduction of zero sign-on (ZSO) eliminates passwords as the method for user authentication, replacing single sign-on, which still requires at least one username and password. ZSO is exactly what enterprises need to secure the proliferating number of mobile devices they rely on to operate and grow in a Zero Trust world.

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