Endpoint Detection and Response: 6 Best Practices You Must Know About

What Is Endpoint Detection and Response?

An endpoint detection and response (EDR) solution is a collection of tools and processes used to detect and analyze potential attacks and their traces on endpoint devices. Endpoints include desktops, laptops, mobile devices, and other devices connected to a corporate network. 

EDR solutions are designed to provide continuous monitoring and response to cyber threats and exploits. Security teams use EDR tools to gain visibility into activities occurring on endpoints. This level of visibility into endpoint threats is critical to ensure teams can quickly investigate threats, respond to them, and prevent similar threats in the future. 

According to Gartner, an EDR solution should be able to perform several tasks, including data exploration, threat hunting, detection of abnormal activities, searching and investigating incident data, triaging alerts, validating suspicious activities, and stopping attacks.

What are the Common Features of Endpoint Detection & Response (EDR) Software?

Most EDR solutions provide the following features. 

Detection 

Detection is the result of ongoing monitoring, which is used to collect information about the normal behavior of a system. Normal behaviour then becomes a benchmark for detection of abnormal behavior. Once abnormal behaviour is detected, IT and security teams are alerted and guided through the review and resolution process.

Containment

If a threat is detected in one endpoint, you need to restrict it from gaining access to the networks and other endpoints. These features (also called quarantine features) help protect your network right after a threat is detected.

Remediation

Once a threat is found, it must be addressed. EDR software enables teams to track incidents back to the point of origin and identify malicious software or suspicious actors.

Investigation 

After an incident, the EDR software collects a large amount of data related to the endpoint device and provides a historical record of the activity. You can use this information to quickly determine the cause of an accident and prevent future similar incidents.

Behavioral analysis

Behavioral analysis provides administrators with valuable insights related to end-user behavior. This data can help monitoring processes detect and compare anomalies.

Threat data documentation

An EDR system records events by automatically collecting and curating incident data. Security teams can use this information to gain a better understanding of the performance and health of endpoint devices.

Data exploration 

The data exploration functionality enables security teams to view data related to security incidents. Security teams can cross-reference and analyze these data points to provide insights on how to better protect your endpoints in the future.

Endpoint Detection and Response Best Practices

1. Start with Network Segmentation

EDR tools often respond to events by isolating endpoints—this type of response ensures that threat actors are quickly blocked. However, starting with a segmented network can provide better protection in the first place. Network segmentation allows you to limit access to certain services and data stores. This can reduce the risk of data loss and limit the scope of damage during a successful attack.

You can use Ethernet Switched Path (ESP) technology to further protect your network by hiding network structure. This makes it more difficult for an attacker to move laterally from one network segment to another.

2. Pay Attention to BYOD

In today’s organizations, it is very common to implement a Bring Your Own Device (BYOD) strategy, to enable employees to use personal computers, laptops, and mobile devices. In addition, modern networks include many connected devices such as printers and other office equipment, smart building devices, industrial sensors and wearables.

Poorly secured devices with active network connections are often targeted by attackers. Your endpoint protection strategy should take these new devices into account. Personally-owned devices introduce many risks that are not covered by traditional tooling. To protect the corporate network, security teams should consider BYOD security techniques like network segmentation and zero trust authentication. 

3. Monitor and Observe Process Executions

Security teams need to know the details of all activities on the endpoint. For example, what processes are running, where the processes are running, which files are being accessed, and which sockets were opened. Shell commands, process hash and process ancestry are all very important in identifying unauthorized or potentially malicious activity. 

4. Educate Employees

Cybercriminals often use social engineering to trick employees into taking harmful actions and revealing sensitive information. The only way to prevent this is to teach all employees proper security practices. For example, changing passwords regularly and ensuring that computers are locked when employees are away. It’s also important to teach them how to recognize email and phone phishing scams.

5. Enforce Least Privilege Access

The least privilege approach restricts access granted to endpoints and users to the minimum amount of resources needed. If a user tries to access content that violates policies, administrators are immediately notified of that behavior. If a user needs higher-level privileges, they must be validated using multi-factor authentication.

6. Be Aware that EDR Solutions Require Human Talent

In large organizations, EDR security solutions can generate thousands of alerts every day. Most of these warnings can be false positives. To realize the real benefits of EDR, organizations must invest in security analysts who can understand computer-generated data. However, hiring in-house experienced security analysts can be an expensive investment. Smaller organizations can consider managed detection and response (MDR)—a third-party service that offers both EDR and manual analysis performed by human analysts.

Conclusion

In this article, I covered 6 key best practices that can help you improve endpoint detection and response:

  • Use network segmentation – this is an important complement to endpoint security, as it prevents attackers from doing damage if an endpoint is compromised
  • Pay attention to BYOD – personal devices used at work represent additional security risks, and may be difficult to protect using traditional methods.
  • Monitor process executions – when attackers compromise a host, this usually manifests itself in malicious processes, making process monitoring critical.
  • Educate employees – employees are often the weakest link of the security chain, and should be educated on recognizing and avoiding social engineering attacks.
  • Enforce least privilege access – ensure each user and device has only the minimal privileges they need for their task, using a zero trust approach.
  • Make human talent available – trained security staff are needed to operate EDR solutions, and it is critical to ensure you have this talent available.

I hope this will help your organization better utilize EDR tools and take endpoint security to the next level.

Linumonk

Recent Posts

ModTask – Task Scheduler Attack Tool

ModTask is an advanced C# tool designed for red teaming operations, focusing on manipulating scheduled…

21 hours ago

HellBunny : Advanced Shellcode Loader For EDR Evasio

HellBunny is a malleable shellcode loader written in C and Assembly utilizing direct and indirect…

22 hours ago

SharpRedirect : A Lightweight And Efficient .NET-Based TCP Redirector

SharpRedirect is a simple .NET Framework-based redirector from a specified local port to a destination…

22 hours ago

Flyphish : Mastering Cloud-Based Phishing Simulations For Security Assessments

Flyphish is an Ansible playbook allowing cyber security consultants to deploy a phishing server in…

2 days ago

DeLink : Decrypting D-Link Firmware Across Devices With A Rust-Based Library

A crypto library to decrypt various encrypted D-Link firmware images. Confirmed to work on the…

2 days ago

LLM Lies : Hallucinations Are Not Bugs, But Features As Adversarial Examples

LLMs (e.g., GPT-3.5, LLaMA, and PaLM) suffer from hallucination—fabricating non-existent facts to cheat users without…

2 days ago