In the ever-evolving landscape of cybersecurity, the shortcomings of traditional log analytics have become increasingly apparent. Over the past decade, a series of high-profile cyberattacks have exposed the limitations of relying solely on this passive method of threat detection. In the wake of incidents like the notorious Target credit card breach and the more recent Storm-0058 attack against federal agencies, it has become evident that log analytics alone are insufficient to protect organizations from the relentless onslaught of cyber threats.
A big price to pay
The Target breach serves as a striking example of the challenges posed by log analytics, and its inability to adequately protect organizations. While there were warning signs and suspicious activities leading up to the breach that were flagged by log analytics, the sheer volume of threat alerts was overwhelming. With tens of thousands of alerts clamoring for attention, it was virtually impossible to sift through the noise and pinpoint the true threat. In this scenario, the passive nature of log analytics left the organization vulnerable and unable to respond effectively when it mattered most—to the tune of $300 million lost.
More recently, the Storm-0058 attack targeting federal agencies also demonstrated a critical flaw in using log analytics. In this case, the first detection took over a month, leaving government agencies exposed and unaware of the impending danger. In fact, a single government data breach is estimated to cost an average of $2 million per occurrence. The stark reality is that log analytics can swing from providing an excess of data to failing to detect threats altogether, leaving organizations in a tenuous position they can’t afford to be in.
Log analytics is reactive, slow, and inaccurate
Organizations have traditionally adopted log analytics for cyber defense. Log analytics is based on the logs collected from various systems and applications within an organization’s network. When used for primary threat detection, log analytics comes up woefully short. One of the key issues with log analytics is the high volume of false positives, leading to overburdened security teams that miss the real signal among the noise. Logs contain free format and unstructured data, leading to tremendous complexity for the analytics and resulting in significant delays to obtain the findings.
Log availability and retention is a huge challenge, in the Storm-0558 attacks, most of the affected agencies did not have access to the logs in the first place. Attackers target embedded devices such as IoT devices, printers for which no logs are available and leverage the trusted foothold to propagate in the enterprise network without raising detections. Additionally, log analytics is unable to detect evolving threats, greatly limiting its utility in the current threat landscape with rapidly evolving threats.
Embracing proactive cybersecurity
In the wake of attacks like the Target breach and Storm-0058, it’s clear that organizations can no longer rely solely on passive log analytics. The risks are simply too great, and the consequences of failure are severe. Organizations need to shift their mindset from reactionary historical analysis to proactive threat detection that is precise. Organizations should seek out threat detection systems that are designed to predict an attacker’s movement, set traps and proactively detect the attacker rather than simply finding them after the fact.
Deception technology brings an active element to cybersecurity by placing traps for the attacker, deflecting the threat actor away from the critical assets and protecting the organization. By placing relevant traps based on the objectives and goals of the attacker rather than the specific attack mechanisms, organizations can be prepared for future threats as they evolve. By being proactive, organizations can fortify their defenses and preemptively thwart cyber adversaries before they can gain a foothold.
Regaining the defender’s advantage to protect organizations
The reactive nature of traditional defense approaches such as log analytics has placed the advantage with the attacker that can bypass the detection mechanisms. Organizations that adopt an active defense strategy can regain the defender’s advantage. Active defense based on deception technology provides precise and rapid threat detection that detects current threats and future threats as they evolve. This shifts the balance of power back to the defenders.
Relying solely on log analytics is a cybersecurity strategy that should be in the rearview mirror. With more data at stake than ever, a reactionary approach fails to protect what’s most important. Organizations need to prioritize immediate and precise threat detection with proactive response mechanisms. By doing so, they’ll be better prepared at any moment when hit with a cyberattack.
