The status quo of threat hunting is broken
Why do CISOs think that threat hunting is broken?
Threat Correlation/Hunting
It's a bold statement but here are a few of the reasons that CISOs tell me why the status quo of threat hunting is broken and why autonomous threat correlation capabilities like the ones provided by Tego Cyber are so important:
Reactive Approach: The current method of threat hunting often follows a reactive approach, where security teams wait for alerts or incidents to occur before initiating investigations. This approach heavily relies on detecting and responding to known threats, leaving organizations vulnerable to emerging and sophisticated attacks. By the time an incident is detected, the damage may have already been done, and valuable time and resources are spent on incident response rather than proactive threat hunting.
Manual and Resource-Intensive: Traditional threat hunting methods are often manual and resource-intensive. Security analysts manually sift through vast amounts of data, logs, and alerts in search of anomalies or indicators of compromise. This process is time-consuming and can lead to fatigue, human error, and missed signals. Moreover, as the volume of data continues to grow exponentially, it becomes increasingly challenging for human analysts to keep pace with the scale and complexity of the threat landscape.
Lack of Context and Automation: The current method of threat hunting often lacks context and automation. Analysts struggle to piece together disparate pieces of information and make connections between events, leading to difficulties in understanding the full scope and impact of an attack. Additionally, the absence of automation means that repetitive and mundane tasks consume valuable analyst time, preventing them from focusing on higher-value activities such as proactive threat hunting and strategic planning.
Limited Visibility: The current method of threat hunting often suffers from limited visibility into the organization's entire digital environment. Traditional approaches may focus on specific areas or data sources, leaving blind spots where threats can go undetected. This limited visibility hampers the ability to identify and correlate indicators of compromise across the entire infrastructure. As a result, threats may remain hidden, and attackers can exploit these blind spots to infiltrate and persist within the organization's systems.
Lack of Contextual Intelligence: Effective threat hunting requires contextual intelligence that goes beyond individual security events or indicators of compromise. It involves understanding the broader context of an attack, such as the attacker's tactics, techniques, and motivations. However, the current method often lacks access to comprehensive and contextual threat intelligence. Without this holistic view, security teams may struggle to prioritize threats, differentiate between noise and genuine threats, and effectively respond to sophisticated attacks.
Overall, the current method of threat hunting falls short in terms of proactivity, efficiency, and effectiveness. Organizations need a shift towards a more proactive, automated, and intelligent approach to stay ahead of the evolving threat landscape and effectively identify and mitigate potential risks. Addressing these limitations is crucial for organizations to enhance their threat hunting capabilities and proactively detect and mitigate threats. By adopting advanced technologies such as artificial intelligence, machine learning, and automation, organizations can gain broader visibility, context-rich intelligence, and efficient processes, enabling a more proactive and effective approach to threat hunting.
