The large-scale journey to the cloud has fundamentally reshaped the digital business and the traditional paradigm of the network perimeter. Hybrid infrastructure and distributed workers are now a part of the furniture of an increasingly diverse digital estate, with multi-cloud practices introducing a new layer of complexity that most organizations are ill-equipped to address.
In the cloud, security teams not only struggle with a lack of visibility and control, but also diverse and incompatible defenses that often lead to overly relaxed permissions and simple mistakes. This traditional ‘stovepipe’ approach to security is rarely robust and unified enough to provide sufficient coverage, relying on static and siloed methods that fail to detect compromised credentials, insider threats, and critical misconfigurations.
Darktrace’s Cyber AI Platform fills these gaps with self-learning AI that understands ‘normal’ at every layer, dynamically analyzing the dispersed and unpredictable behaviors that show up in email, cloud, and the corporate network. This unified scope allows the system to spot subtle deviations indicative of a threat – from an unusual resource creation or open S3 bucket in AWS, to suspicious data movement in Salesforce, to a new inbox rule or strange login location in Microsoft 365.
Unlike policy-based controls, the immune system understands the human behind every trusted account in the cloud, providing a unified detection engine that can correlate the weak and subtle signals of an advanced attack.