Successful attacks can lead to severe security issues with long-lasting implications, beyond computing resource theft. Bad actors have been known to deploy other forms of malware alongside cryptominers, using compromised systems in distributed denial of service (DDoS) attacks.

While organizations may treat cryptojacking attempts as a mere inconvenience, they should be treated as a serious threat. As cyber initiatives, such as the advent of the metaverse and the incorporation of cryptocurrency into more business practices, expand across the U.S., cryptocurrency security needs to be a top cyber priority.

Cryptojackers present numerous threats to organizations. For one, organizational leadership should be concerned about the incredible speed with which cryptominers act. Once a cryptojacker gains access to an environment, they can get right to work. Per the November 2021 Threat Horizons report, it takes an average of just 22 seconds for an attacker to download cryptomining software to the user’s resources.

Moreover, the effects of a cryptomining attack can linger far beyond the initial point of compromise. After accessing a user’s cloud data and infrastructure, a cryptojacker can target it with increasingly sophisticated attacks.

Meanwhile, victims find their computers growing painfully slow as their cloud usage costs skyrocket. Couple that with the probability that the bad actor has co-deployed their cryptomining malware with additional malicious tooling, and organizations have a huge security problem.

Luckily, while the cloud may have accelerated this issue, the right cloud security approach can drastically reduce the risk.

Finding cryptominers through behavior-based threat detection

The key to protecting organizations from malicious cryptominers is a proactive, automated approach to threat detection. Automation can help prevent cryptojacking because cloud complexity makes manual intervention difficult.

This type of approach is helpful for many modern cyberattacks like cryptojacking and data exfiltration. Unlike a cyberattack such as ransomware, these new threats aren’t interested in quickly locking up organizational systems and then broadcasting their presence. Instead, they are content to do damage over the long haul, hiding beneath the noise of the cloud environment.

Security teams should consider a time-series model approach to detecting crypto threats due to the complicated threat landscape facing the currency technology. This cloud security approach uses automated learning and behavioral analytics to first build a baseline of expected activity volume and frequency over time within a cloud environment. Once that baseline has been built, the technology monitors for activity spikes that deviate from that unique baseline to detect potential threats. The time series model can scan cloud logs for heightened CPU or GPU usage that accompanies cryptomining operations. It can also detect changes in the volume and frequency of authentication and authorization requests.

Cryptojacking defense for the present and the future

No matter where the cryptocurrency industry heads next, the cloud’s complexity and wide attack surface mean that cryptojacking may remain a major issue for cloud users across a range of industries.

To stay one step ahead of cryptominers, it’s critical to monitor organizational cloud environments for notable changes to new and existing entities. With an approach to threat detection that incorporates time-based automation, tracking malicious activity can become simpler for organizational cybersecurity teams.