New LLM-powered engine helps secure complex cloud environments
While moving systems to the cloud delivers many benefits, it also leads to complex dynamic environments that can be a real challenge when it comes to keeping them secure.
With the launch of a new Large Language Model (LLM)-powered cloud detection engine, Sweet Security aims to cut through the noise and allow security teams to tackle these environments with greater precision and confidence.
By evaluating cloud variables and anomalies in real time -- and adapting the findings to the nuances of the particular cloud environment -- Sweet's cloud detection engine is capable of uncovering zero-day attacks and 'unknown unknowns' -- threats that have not been introduced or published to the world. This cuts the need to predefine what counts as abnormal or malicious behavior and streamlines the differentiation between unusual activity and actual attacks.
Each incident is labeled as either 'malicious,' 'suspicious,' or 'bad practice,' indicating whether the anomaly is could be an attack and requires further attention from SecOps or is unusual but legitimate activity that needs to be reviewed by DevOps. This helps security teams eliminate false positives, streamline workflows, and focus their attention where it matters most.
"This new capability is a game-changer for cloud security," says Dror Kashti, CEO of Sweet Security. "By harnessing the power of LLMs, we’re not only reducing detection noise to near-zero levels but also providing security teams with the tools they need to act swiftly and decisively. This is a major leap forward in our commitment to delivering unparalleled detection and response for the cloud."
Features include immediate mapping of 'danger zones' in the environment through an intuitive heat map, clear incident labeling, providing context and clarity for security analysts, and identification of relevant problem owners within the organization to streamline incident response.
You can find out more on the Sweet Security site.
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