The Latest Insider Threat Indicators: How to Predict, Detect and Respond

It’s common for organizations to spend most of their cybersecurity budget and efforts on preventing, detecting, and combatting threats that originate from outside the organization. However, while external threats might get more attention, the potential damage from insider threats should not be underestimated. Malicious or negligent actions from employees, contractors, or business partners can lead to significant breaches, data loss, and damage. An effective cybersecurity strategy should address both external and insider threats to ensure comprehensive protection of sensitive data and digital assets.

A different kind of mentality and different toolsets are required for detecting insider threats from the approaches used for external threats. This article discusses the latest insider threat indicators and looks at the tools and techniques for, not just detecting but actually predicting, when a threat poses real risk. This can be done by analyzing patterns and behaviors that serve as insider threat indicators.

Key Insider Threat Indicators

Detecting insider threats can be challenging because insiders often have legitimate access to systems and data. However, certain behaviors and patterns can serve as indicators of potential insider threats.

1. Unusual Access Patterns – Insiders may exhibit unusual patterns of accessing systems, networks, or data, such as accessing sensitive information at odd hours or accessing systems outside their normal job responsibilities.
2. Excessive Data Access or Downloads – An insider planning to steal sensitive data might access or download a larger amount of data than their typical usage, especially if the data is unrelated to their role.
3. Unauthorized Access – Insiders might attempt to access systems, databases, or files that are outside their authorized scope, role or granted entitlements.
4. Frequent Failed Access Attempts – Repeated failed attempts to access certain systems or data could indicate an insider trying to bypass security measures or escalate their privileges.
5. Accessing Restricted Areas – It could be a sign of an insider threat if an employee suddenly starts accessing areas or systems they have no legitimate reason to access.
6. Unapproved Copying or Transferring Data – Insiders might copy sensitive data to external storage devices, cloud services, or personal email accounts in preparation for unauthorized use or distribution.
7. Abnormal Data Access
   Malicious insiders may exhibit abnormal patterns of data access, such as accessing files or systems outside their normal job responsibilities, accessing data at unusual times or from unusual locations, or downloading large amounts of data without a legitimate business reason.
8. Privilege Escalation
   Malicious insiders may attempt to escalate their privileges or gain unauthorized access to systems or data beyond their authorized level. They may exploit vulnerabilities or misuse administrative privileges to bypass security controls and gain access to sensitive information.
9. Unusual Network Traffic
   Monitoring network traffic can reveal suspicious activities by insiders. Look for anomalies such as large data transfers to external destinations, unauthorized connections to suspicious IP addresses, or attempts to bypass network security controls.
10. Unauthorized System Modifications
    Malicious insiders may make unauthorized changes to systems, configurations, or security settings to gain access, hide their activities, or create backdoors for future access. Unauthorized system modifications can leave traces of their malicious intent.
11. Employee Behavior Changes
    Significant changes in an employee’s behavior, such as sudden job dissatisfaction, conflicts with coworkers, or disengagement from work, could be indicative of potential malicious intent or disgruntlement that might lead to insider threats.
12. Financial Stress or Personal Problems
    Malicious insiders may experience financial stress or personal problems that could motivate them to engage in fraudulent activities or seek financial gain through unauthorized actions, such as theft of intellectual property or selling sensitive information.
13. Attempted Data Exfiltration
    Monitoring for data exfiltration attempts, such as large transfers of sensitive data to external storage devices or suspicious network traffic patterns indicative of data theft, can help detect potential malicious insiders.
14. Violation of Security Policies
    Malicious insiders may repeatedly violate security policies, such as bypassing access controls, sharing sensitive information without authorization, or using unauthorized software or tools.
15. Unusual Work Patterns
    Insiders engaged in malicious activities may exhibit inconsistent or unusual work patterns, such as working late at odd hours, accessing systems during non-working hours, or attempting to access restricted areas without valid reasons.

The list of insider threat indicators is extensive, but some additional ones include: excessive use of privileges, unauthorized use of credentials, data exfiltration, logins from multiple locations, unapproved software installations, violations of policies, and excessive data printing.

How to Predict Threats and Malicious Insider Attacks

Given that an insider usually has access privileges that are a normal part of their work processes, the key to predicting an insider threat is to monitor all users for risky and anomalous behaviors, determine their severity, and assess whether they could cause damage or whether malicious activity is about to occur or is currently taking place.

User and Entity Behavior Analytics (UEBA) is often advocated as the best means to detect nefarious or potentially damaging activity by internal actors. UEBA involves keeping track of what users are doing and looking for behaviors that are outside the range of normal activities. This, then, is combined with in-depth intelligence about a user’s identity attributes and the privileges they have on the network. This approach involves analyzing the access rights and entitlements a person has; the activities they have been performing across multiple accounts, both now and in the past; and the typical activities that members of their peer groups are performing. It takes a combination of the right data sources, sophisticated machine learning, and perceptive data science to pinpoint truly aberrant actions that can be seen as insider threat indicators.

Preventing Insider Attacks Requires a Different Approach

Malicious or negligent workers, or those posing as one through the use of compromised credentials, can represent a significant cyber risk to any organization. Preventing and detecting such threats requires a different approach than the typical external cyberattacks.

The most effective way to pinpoint the presence of insider threats, without creating a lot of false positive alerts, is to overlay user activities with user identity intelligence, cluster identities into dynamic peer groups, create time-based behavioral baselines, and continuously learn what is acceptable behavior in order to spot the unacceptable behavior. It takes a combination of the right data sources, sophisticated machine learning, and predictive analytics to pinpoint truly divergent actions that are good indicators of misuse of assigned privileges.

Insider Threat Demo