Why EDR is not sufficient to protect your organization

Endpoint detection and response (EDR) tools are a cornerstone of most cybersecurity defenses today. But while the technology has an important role to play in investigating threats, too many organizations have made the mistake of relying on EDR as their first line of defense against security breaches.

EDR tools

The reality is that an “assume breach” mindset means that it is already too late. EDR solutions are increasingly evaded by the latest malware and attack techniques, particularly when it comes to ransomware and zero-day exploits.

Organizations can not solely rely on EDR to keep their environments safe from the latest threats. So why is EDR not sufficient on its own, and what can enterprises do about it?

Why detection is too late

The greatest drawback of EDR is that it is a reactive approach. Traditional EDR tools rely on behavioral analysis which means the threat has executed on the endpoint and it’s a race against time to stop it before any damage is done. Upon observing malicious intent or activity, the EDR will block it, and the security team will move in for remediation and clean up.

At a time when skilled resources are scarce, SOC productivity is important to protecting your organization. A typical EDR produces a high volume of alerts and false positives, impacting the SOC team’s ability to perform valuable proactive tasks, like patching and hardening systems.

Serious threats can easily be lost in all this noise, making it more likely that threat actors will fly under the radar and achieve longer dwell times.

As such, visibility across every endpoint is critical to protecting an organization. Yet a typical enterprise does not know if all the endpoints are instrumented, leaving holes in the fabric. Ensuring that every device is covered has been made increasingly challenging by trends like BYOD and remote working.

To be truly effective, organizations need to have full visibility across every endpoint connected to the network. However, this very rarely the case. Indeed, an investigation from Deep Instinct found that just one percent of firms believed that all their endpoints were protected.

A reactive approach is no longer enough

Some of the fastest malware can infect in less than a second after executing on the endpoint. Ransomware, for example, can begin to encrypt systems before it is detected and blocked, and the malware may have left droppers and artifacts behind that are missed in remediation.

The fastest and most sophisticated malware variants used to be the province of organized cyber gangs and state-sponsored actors. But thanks to an increasingly well-developed shadow economy, advanced malware and zero-day exploits have never been more accessible. The ransomware-as-a-service (RaaS) trend is a prominent example, mimicking the structure of legitimate SaaS offerings to provide criminals with affordable access to execute powerful new ransomware attacks. The brisk malware trade has also led to an increased number of variants appearing in the wild, with hundreds of thousands of new versions appearing daily.

The need for a prevention-first strategy

Prevention-first approach is needed to stop more attacks before they are deployed.

While XDR addresses many of EDR’s issues, it is still stuck with a reactive model that is vulnerable to advanced and unknown malware and is prone to creating many security alerts. Indeed, unless it is tightly managed, the greater volume of alerts created through the increased telemetry can make things even more difficult for SOC teams to handle.

Rather than a reactive approach that can only deal with threats as they emerge, security strategies need to center around a preventative approach. Incoming malware needs to be detected and blocked before it can execute within the network environment. Neutralizing attacks before they can execute greatly reduces the risk of a breach occurring. It also means that SOC teams can more effectively use their EDR and XDR tools to investigate and remediate other issues without the constant fear of a serious attack occurring.

To get ahead of fast-moving cyber threats, security solutions need to move even more swiftly. Deep learning technology presents one of the best opportunities for succeeding, because its self-learning nature can enable us to understand the DNA of an attack without having to know its hash, and to predict and prevent unknown threats.




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