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Cyber crime has always been in a state of flux.
But as individual threats are changing, the very ecosystem of cyber crime is also evolving.
We now have an increasingly complex, service-based shadow economy that freely trades in TTPs.
The result is more sophisticated attacks that are likely to outfox traditional threat profiling.
So how can organizations defend against these unpredictable attacks?
They would undertake the initial access, conduct reconnaissance and discovery, and proceed with escalation and lateral movement.
Now, though, we increasingly see attacks involving multiple parties.
Senior Security Researcher at WithSecure.
Each tool was carefully chosen for its job, and the combined arsenal made for a formidable threat.
This allows the defenders to get ahead of the attacker and block or mitigate the attack.
Now though, traditional profiling techniques are falling behind in effectiveness due to their static nature.
This creates blind spots in security postures, leaving organisations vulnerable to undetected threats.
Gathered data can also be used to train machine learning algorithms to aid in identifying and predicting attacks.
Predictive modelling also provides actionable data to help organizations invest in the right defensive tools and capabilities.
This multifaceted approach enables quicker responses to emerging threats and a more robust understanding of complex attack sequences.
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