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 looks at the tools and techniques for, not just detecting but actually predicting, when a threat poses real risk. This can be done trough analyzing patterns and behaviours which serves as insider threat indicators.
Insider threats refer to cybersecurity risks that originate from individuals within an organization, such as employees, contractors, business partners, or other trusted insiders who have access to the organization’s systems, networks, and sensitive information. These individuals might exploit their access privileges, intentionally or unintentionally, to compromise the confidentiality, integrity, or availability of data or systems.
Insider threats also can come from external actors who have attained compromised credentials that allow them to act as a legitimate insider. The credentials get them past perimeter security tools such as intrusion detection/prevention systems and onto the network where they can exploit the ill-gotten insider access.
The real danger of insider threats is that insiders know their way around their organization’s network, systems, and applications, and they know what data and information is most valuable. Insider threats can have significant and wide-ranging impacts on organizations, affecting their data security, operational integrity, financial stability, and reputation. Here are some ways insider threats can affect organizations:
Other impacts can include operational disruption, reputational damage, regulatory and legal consequences, supply chain risks, litigation and legal costs, and stakeholders’ loss of trust.
Insiders already have a certain level of access to perform specific activities on a network. What tends to distinguish them is their motivation for going rogue. Nevertheless, their activities follow certain patterns that make them detectable with the right technology.
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 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 he has on the network. This approach involves analyzing the access rights and entitlements a person has; the activities he has been performing across multiple accounts, both now and in the past; and the typical activities that members of his peer groups are doing. 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.
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.
Additional insider threat indicators are excessive use of privileges, unauthorized use of credentials, data exfiltration, logins from multiple locations, unapproved software installations, violations of policies, excessive data printing, and inconsistent work patterns.
Responding to an insider threat requires a combination of preventive measures, detection strategies, and appropriate responses.
Prevention and Preparation
Detection
Response
Learning and Improvement
Malicious or negligent inside 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 aberrant actions that are good indicators of misuse of assigned privileges.
How do insider threats differ from external threats?
The main distinction between insider threats and external threats lies in the source of the threat and the level of authorized access to the organization’s resources. Insider threats involve individuals who have internal access and often use their legitimate privileges to commit malicious actions. External threats come from unauthorized individuals outside the organization who seek to breach the organization’s defenses and gain access to sensitive information or disrupt operations. Both types of threats require tailored cybersecurity strategies to mitigate their risks effectively.
Are all insider threats intentional?
Not all insider threats are intentional. A person can accidentally or negligently violate a security policy that inadvertently results in a breach. For example, an employee could install software on their workstation that opens a backdoor into the organization’s network.
What are some behavioral indicators of insider threats?
The best way to monitor for insider threats is to look at users’ behaviors, watching for anything that seems to be unusual and risky. Some common behavioral indicators include logging in at unusual times or from unusual locations; moving, copying, or deleting large amounts of data; attempting to access systems or applications for which they have no legitimate business purpose; conducting activities that are not commonly performed by the worker’s peer group.
How can analytics help predict insider threats?
Predictive analytics adds an extra layer of sophistication to insider threat detection by leveraging advanced data analysis techniques to identify suspicious behaviors and patterns. This proactive approach is essential for mitigating the risks associated with insider threats and protecting an organization’s sensitive information and assets.
What is an Insider Threat?