"Keep your friends close and your enemies closer." Maybe this statement is uncomfortably close to the truth of insider threats—can you really trust the people with access to critical systems and sensitive data? After all, your biggest security risk might already have an access badge and valid login credentials.
It’s a common concern; 83% of organizations reported insider attacks in 2024, and this threat can happen to any business, large or small. The 2023 Pentagon leak, where an insider exposed classified military intelligence, wasn’t a sophisticated cyberattack—it was an abuse of access. In 2024, a former Samsung executive was caught stealing trade secrets to build a competing semiconductor facility in China. This incident proved even the most advanced tech companies aren’t immune and should prioritize insider threat detection.
Insider Threat Detection: Definition and Examples
Insider threats pose a unique challenge because the risks originate within your company from people who have legitimate access to your systems and data. Their familiarity with your network and security practices gives them a distinct advantage over external attackers.
Insider threat detection focuses on identifying and addressing these internal risks by deploying tools and processes that spot unusual behaviors or access patterns among your staff and partners. The goal is safeguarding your company’s critical assets from potential sabotage or data breaches.
Who could be an insider?
Technically, anyone who is an authorized user with access to your network, apps, or other systems could be an insider threat. For example:
Employees: Both current and former staff who have access to sensitive information.
Contractors and Consultants: These often have necessary but potentially risky access to your systems.
Business Partners: Other companies with whom you have strategic alliances that might include data or network access.
Motivations of Internal Threats
Why would someone with legitimate access use that access for nefarious reasons? Well, there are several motivations.
Financial Gain: The allure of high monetary rewards can drive people to misuse their access.
Revenge: Personal grievances might push someone to retaliate against your company.
Ideological Reasons: Commitment to personal or political beliefs might lead to data leaks or sabotage.
Curiosity: Sometimes, insiders test the limits of their access out of simple curiosity or for the thrill of it.
Top 5 Insider Threat Detection Red Flags
1. Anomalies in Code Commit Patterns
Changes in the volume, timing, and nature of code commits can indicate an insider threat. For instance, an employee might push code with embedded backdoors or execute commands that typically require higher permissions. DevOps teams should look for commits that bypass the usual review process and commits at odd hours that don’t align with the individual’s time zone or work patterns.
2. Irregular API Usage or Creation
API security threats can provide a discreet channel for data exfiltration or system manipulation. Indicators include the creation of new APIs without following standard approval processes, modifications to existing APIs that expand access capabilities beyond necessary scopes, or unusual patterns of API calls (e.g., high frequency or volume, accessing sensitive data not required for one’s role). These activities suggest attempts to interact with backend systems in ways that facilitate unauthorized actions like data theft or system compromise.
3. Escalation of Privileges
This insider threat detection indicator revolves around changes to permissions and roles that aren’t justified by job requirements. For example, an insider might alter cloud-based IAM roles to gain broader access than needed, allowing them to access restricted areas of your cloud environment. An increase in root account activities or the creation of new roles with administrative privileges could signal unauthorized attempts to elevate access to sensitive resources or infrastructure.
4. Behavioral Changes
Behavioral indicators include noticeable changes in an employee’s work habits, such as suddenly working odd hours, exhibiting poor job performance, or bypassing normal security procedures. When an employee starts working at unusual hours without a clear business need, especially in roles where access to sensitive systems and data is involved, it can be a big red flag. For example, if a systems engineer or a database administrator begins accessing the system late at night or during early morning hours, it could indicate they are attempting to perform unauthorized actions when fewer colleagues are online to notice.
5. Using External Devices
Using unauthorized external devices, such as USB drives, memory cards, and external hard drives connected to your systems, can be a big red flag in your insider threat detection strategy. External storage devices can be used to illicitly transfer sensitive information out of the corporate network. It's one of the simplest yet most effective methods for an insider to exfiltrate large amounts of data. For example, copying database files, source code, or confidential documents onto a USB drive can happen quickly and stealthily.
5 Approaches to Insider Threat Detection and Mitigation
1. Insider Threat Awareness Training
People are foundational in any insider threat detection strategy. Teach your team to recognize suspicious changes in commit logs, unexpected API calls, or unauthorized access to critical environments. This tailored approach helps technical teams understand their specific role in preventing insider threats and encourages them to take proactive measures.
2. Enhance Detection With Behavioral Analytics
Deploy sophisticated User Behavior Analytics (UBA) that can integrate seamlessly with your existing DevOps tools. For example, linking UBA to your continuous integration and deployment (CI/CD) pipelines can help detect real-time anomalies, such as unauthorized code deployments or unusual access to production environments during off-hours. This level of integration enables automated, context-aware alerts specific to your operational workflows.
3. Foster an Inclusive and Transparent Workplace Environment
Develop a workplace culture that emphasizes inclusivity and transparency, which can reduce the likelihood of insider threats. Employees who feel valued and engaged are less likely to act maliciously against their employer. Open communication channels between staff and management can help identify grievances early before they escalate into security risks. Encouraging a collaborative environment also means colleagues are likelier to notice and report unusual behaviors and stay proactive in insider threat detection.
4. Establish and Enforce Robust Security Policies
Create clear, comprehensive security policies that define acceptable use of company resources, data handling procedures, and response strategies for suspected security incidents. These policies should be regularly updated to reflect the evolving security landscape and new organizational needs. Crucially, enforce these policies consistently across all levels to underscore their importance.
5. Get Started on a Zero Trust Journey
Adopt a zero-trust architecture where no entity, whether inside or outside the network, is trusted by default—this means strict, continuous identity verification, micro-segmentation, and least privilege access principles to minimize lateral movement within your network. A zero trust approach ensures that insiders face the same stringent access controls as external actors. It's not a quick project to get to fully zero trust so perhaps consider rolling it out for a specific application or subnetwork first.
Types and Key Features of Insider Threat Detection Tools
Advanced analytics: The core of effective insider threat detection tools lies in their ability to analyze and understand normal user behaviors using machine learning. This capability enables the system to detect anomalies that deviate from the norm, such as unexpected large file downloads or unauthorized access attempts at unusual times.
Real-time alerts and automated responses: Immediate notification and response are crucial in mitigating insider threats. Look for tools that provide instant alerts when potential threats are detected and can automatically take corrective actions, such as disabling a user account or restricting access to sensitive areas.
User and Entity Behavior Analytics (UEBA): UEBA tools are essential for identifying unusual behavior patterns that indicate insider threats. They analyze your users’ activities over time to establish a baseline of normal behavior and then flag deviations from these patterns. Key features include advanced machine learning algorithms to detect anomalies, risk-scoring systems to prioritize threats, and integration capabilities with other systems.
Data Loss Prevention (DLP) systems: DLP tools help prevent unauthorized access to and transmission of sensitive information from your network. They monitor data in use, at rest, and in motion and apply rules to detect and block sensitive data leakage. Key features include content inspection, contextual analysis, and endpoint activities monitoring to ensure insiders don't misuse or transmit data outside your corporate network without authorization.
Holistic surveillance across systems: True security comes from having a complete view of all activities across your network. Insider threat detection and management tools need to break down the silos that typically separate data sources. By integrating data from various systems—like user behavior logs, application interactions, and network traffic—some tools can provide a unified view that spots inconsistencies and potential threats more effectively.
Using a WAF to Enhance Insider Threat Detection
WAFs enhance security at the application layer by actively monitoring, filtering, and responding to web traffic. They provide a crucial checkpoint that prevents insiders from exploiting web applications to conduct malicious activities. When integrated with other security systems, such as insider threat detection tools, WAFs can contribute valuable context for security alerts.
For example, suppose an insider threat detection system notes suspicious data access by a user. In that case, the WAF detects that the same user is making unusual requests to a web application, both pieces of information can be correlated to confirm malicious intent and guide your response actions.
open-appsec is an open-source project that builds on machine learning to provide pre-emptive web app & API threat protection against OWASP Top 10 and zero-day attacks. It simplifies maintenance as there is no threat signature upkeep and exception handling, like common in many WAF solutions.
To learn more about how open-appsec works, see this White Paper and the in-depth Video Tutorial. You can also experiment with deployment in the free Playground.
