The Rising Threat of Compromised Credentials in State and Local Governments: The Case for UEBA

The growing prevalence of compromised credentials poses a significant challenge to state and local government agencies responsible for protecting sensitive data and critical infrastructure. In this blog post, we’ll explore how user and entity behavior analytics (UEBA), when incorporated with a security information and event management (SIEM) solution, can help detect anomalies indicative of credential compromise. We’ll discuss the limitations of static correlation rules, the advantages of advanced analytics, and how these capabilities can benefit security teams in the public sector.

In this article:

• The compromised credentials problem
• Consequences of compromised credentials
• The need for advanced analytics
• Establishing a baseline for normal user behavior
• The importance of detecting lateral movement in compromised credential attacks
• The role of automation and consolidation in UEBA
• The Exabeam Security Operations Platform
• Conclusion

The compromised credentials problem

Compromised credentials have become increasingly pervasive, especially in the public sector, as state and local government agencies often lack the adequate resources and expertise to defend against sophisticated cyberthreats. The 2021 Data Breach Investigations Report (DBIR) revealed that 80% of incidents in the public sector targeted credentials. The following year, the same report documented 2,792 security incidents, of which 537 involved confirmed data disclosure. Credentials accounted for 34% of the compromised data.

Consequences of compromised credentials

Government organizations store and transmit vast amounts of sensitive data, the security of which is essential to the wellbeing of millions of people. The potential consequences of a breach resulting in leaked data, stolen credentials, or a disruption in operations can have catastrophic results:

• Unauthorized access to sensitive data — Cybercriminals can use stolen credentials to access valuable information, such as social security numbers, financial records, and personal details, leading to identity theft, fraud, or espionage.
• Disruption of essential services — Unauthorized access to government systems can disrupt essential services, including emergency response, public utilities, and transportation, impacting public safety and the economy.
• Damage to government reputation and public trust — Cybersecurity breaches in government agencies can erode public trust, as people may question the ability of their government to protect their personal information and maintain essential services.

The need for advanced analytics

Traditional approaches to detecting compromised credentials rely on static correlation rules, which have significant drawbacks:

• High alert volumes — Static correlation rules often generate many benign alerts, leading to alert fatigue and the potential for critical alerts to be overlooked.
• Inability to detect new or sophisticated threats — Static rules are limited in their ability to detect new or advanced threats that do not match established patterns.
• Maintenance overhead — Security teams must continuously create and maintain custom rules to address new threats, increasing workload and diverting resources from more strategic tasks.

UEBA addresses the limitations of static correlation rules by leveraging machine learning to distinguish anomalous behavior from normal activity. Unlike static rules, UEBA adapts to changing threats and user behavior patterns over time, making it a more effective solution for detecting compromised credentials.

Establishing a baseline for normal user behavior

By collecting and analyzing data over time, UEBA can determine what constitutes typical activity for a given user, entity, or peer group. This baseline serves as a reference point against which all subsequent activity is compared. When a user’s behavior deviates significantly from the established baseline, the UEBA system generates an alert, indicating a potential security incident.

Behavioral analytics offer several key advantages for state and local government agencies, including:

• Minimized alert noise — UEBA reduces alerts generated by benign activity, allowing security teams to focus on true threats and avoid alert fatigue.
• Enhanced threat detection — By identifying signs of compromised credentials and other advanced threats without relying on predefined rules, UEBA can detect previously unknown or sophisticated attacks.
• Streamlined maintenance — UEBA’s continuous learning of normal behavior baselines eliminates the need for security teams to create and maintain custom rules, saving time and resources.
• Early detection of compromised credentials — UEBA identifies anomalous user behavior, such as unusual login times or locations, or accessing sensitive information, allowing for prompt detection of stolen or compromised credentials and swift action to prevent unauthorized access.
• Reduced reliance on traditional security measures — While traditional security measures like password policies and multifactor authentication (MFA) can be bypassed by advanced techniques, UEBA provides an additional layer of security that works in tandem with these methods.
• Improved incident response — UEBA enables security teams to quickly identify and investigate potential security incidents more quickly, streamlining their response to threats and minimizing potential damage.
• Adaptability to evolving threats — As cyberthreats and malicious techniques continue to evolve, UEBA helps security teams stay ahead by continuously monitoring user behavior and adapting to new patterns of malicious activity.

The importance of detecting lateral movement in compromised credential attacks

Detecting lateral movement is a critical aspect of identifying compromised credential attacks, as it can help security teams uncover an attacker’s presence in the network before they can cause significant damage. Lateral movement refers to the process by which an attacker, having gained initial access to a network, moves from one location within the system to another, escalating their privileges and collecting valuable data along the way.

By identifying unusual patterns of lateral movement, UEBA can help security teams detect attackers who have obtained valid credentials but are moving through the network in ways that deviate from normal behavior. This allows security teams to detect and respond to threats more quickly, reducing the potential for data exfiltration and other forms of damage.

Behavioral analytics can also pinpoint  insider threats. Insider threats are among the most challenging cybersecurity concerns, due to the complexities of defining the baseline of typical behavior for an insider. They aren’t usually just a single event, but a series of actions that collectively create a discernible threat. And users with broad access to information are particularly tricky. But behavior-based modeling techniques help to identify abnormal behavior for insiders like employees, contractors, vendors, and partners, significantly lowering the risk of a data breach or intellectual property theft.

The role of automation and consolidation in UEBA

To improve threat detection, identification, and response, UEBA tools must automate and consolidate information from various sources. This includes data from network devices, servers, applications, and user activity logs, among others. By consolidating and analyzing this data, UEBA solutions can provide a comprehensive picture of the threat landscape, enabling security teams to make better-informed decisions.

Automation plays a critical role in UEBA by streamlining data analysis and reducing the time it takes to detect and respond to threats. It allows UEBA tools to:

• Automatically establish baselines of normal user behavior by analyzing historical data, enabling continuous adaptation to evolving threats and user behavior patterns
• Identify and correlate anomalies across multiple data sources, increasing the likelihood of detecting sophisticated threats that might otherwise go unnoticed
• Reduce alert noise by distinguishing between benign and malicious deviations from normal behavior
• Provide real-time analysis and alerts, allowing security teams to act quickly and mitigate potential damage

The Exabeam Security Operations Platform

The Exabeam Security Operations Platform is a cloud-native solution designed to help state and local government agencies implement UEBA and improve their ability to detect compromised credentials. Built for security people by security people, the platform offers several key features that enable agencies to identify and respond to threats more effectively:

• Dynamic baselining — By continuously updating the baseline of normal user behavior Exabeam enables security teams to detect and respond to changing threats more effectively.
• Integration with existing systems — The platform can seamlessly integrate with an agency’s existing security infrastructure, including SIEM systems, log management solutions, and other security tools, providing a unified view of an organization’s security posture.
• Customizable risk scoring — Exabeam allows agencies to assign risk scores to individual users and entities based on their behavior, enabling security teams to prioritize investigations and focus on the most critical threats.
• Automated incident response — The platform streamlines the incident response process by automating workflows and providing security teams with actionable insights to quickly remediate threats.

Conclusion

State and local government agencies face considerable risks from compromised credentials, which can lead to unauthorized access to sensitive data, disruptions to essential services, and erosion of public trust. UEBA is a powerful tool for detecting and preventing these threats by analyzing behavior patterns and identifying unusual activity. By automating and consolidating information from various sources, UEBA tools amplify the detection and response capabilities of government security teams, enabling them to more effectively safeguard sensitive data and critical infrastructure from the growing threat of credential compromise and sophisticated cyberattacks.

As cyberthreats continue to advance and evolve, it’s crucial for state and local government agencies to embrace advanced technologies like UEBA to stay ahead of the curve. By adopting the Exabeam Security Operations Platform, government organizations can strengthen the protection of their sensitive data, critical infrastructure, and the wellbeing of the communities they serve. A proactive stance on cybersecurity will help state and local government agencies collaborate to build a more secure digital environment for all.

Want to learn more about combating credential attacks?

Read our guide, Six Ways to Combat Credential Attacks in State and Local Government Agencies.

State and local government agencies aren’t exempt from the challenges of compromised credentials. Is your agency struggling with this challenge? If so, you’re not alone. Cyberattacks are on the rise, and traditional security solutions often fail to provide a comprehensive view of threats. It’s time for a new approach.

Discover the key aspects to consider when evaluating solutions to detect and combat compromised insiders in this guide.

You’ll learn about:

• The benefits of UEBA for more effective threat detection
• Comprehensive, automatically compiled user timelines for faster investigations
• Lateral movement detection to monitor unauthorized movements within your organization
• Risk-based security alert framework for better resource allocation and prioritization

Don’t leave your organization vulnerable to the risks of compromised credentials. Equip your security team with the tools and strategies they need to effectively identify and combat this persistent threat.
Download the guide today!