CloudGuard Workload Protection
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Video Transcription
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>> CloudGuard Workload Protection, which is part
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of the CloudGuard Native Security Platform,
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provides a unified view of container assets across
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all Cloud environments to ensure configurations
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are in compliance with known baselines such as CIS,
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Kubernetes security benchmarks, or NIST 800-190.
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In addition, security and
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compliance configurations can be built
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into CI/CD to automate
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container security during development.
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During runtime, CloudGuard protects the container assets
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using dynamic protection based on customized rules,
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behavioral analysis,
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as well as other threat intelligence modules,
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automating protection and remediation.
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CloudGuard's breakthrough code-centric platform
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automate security and
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visibility for Cloud native serverless applications
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from development to runtime,
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enabling organizations to securely
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innovate at Cloud speed.
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By analyzing the serverless application code
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before and after deployment,
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organizations can achieve
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a continuous serverless security posture,
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automating application hardening, minimizing
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the attack surface, and simplifying governance.
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Utilizing machine-based analysis
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and deep learning algorithms,
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CloudGuard builds a model of
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normal application and function behavior to
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detect and block application layer attacks
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for enhanced serverless security.
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Up to this point, we've covered
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the security threats Cloud workloads face,
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and how CloudGuard can help protect against them.
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But what about the applications themselves?
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What about the APIs use to
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interact with Cloud resources and services?
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How do we protect these elements?
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First, let's take a moment and talk
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about the threats we face in these areas.
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Web applications face a broad range of
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possible attacks described in the OWASP Top 10 standard.
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The decentralized nature of Cloud implementations,
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and the speed and scale of working in the Cloud,
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means apps are prime targets
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for various malign activities,
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from code injection,
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to broken access control,
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coupled with a lack of sufficient logging and monitoring.
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These attacks can result in site defacing,
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information leakage, digital theft,
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and user session hijacking.
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In the realm of APIs,
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command injections and the API key extraction can lead to
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exposure of sensitive data
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and the hijacking of resources.
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Furthermore, malicious bot attacks using
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automated web requests can be used to manipulate,
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defraud, or disrupt a website application,
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API, and even end users.
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Traditionally, you would use a legacy Web Application
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Firewall to defend against these attacks.
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These WAFs are rule-based and use
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binary rules to match
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requests to attack signature databases.
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This creates enormous administrative overhead
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and blocks legitimate application users,
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or as we like to call it, false positives.
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Faced with these threats and
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the gap left by legacy WAFs,
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CloudGuard AppSec can stop
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OWASP Top 10 attacks, prevent bot attacks,
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and stop any malicious interaction with
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applications and APIs across any environment.
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CloudGuard AppSec is fully
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automated and leverages contextual AI
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analysis to provide precise threat prevention
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from modern web applications,
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lessening the need for ongoing administration,
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and increasing applications security at scale.
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Gone are the days where rules had to be
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tuned manually with exceptions
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every time an update to
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the web application or API was necessary.
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From implementation through runtime,
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CloudGuard AppSec automatically analyzes
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every user transaction and
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URL to create a risk score to
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stop attacks without creating false positives.
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There you have it. We've gone
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through the major security challenges
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we are faced when implementing
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Cloud services in applications,
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and the specific threats targeting Cloud workloads,
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applications, and APIs.
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We introduced CloudGuard's solutions to
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these complex, ever-evolving challenges.
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In our next session, we will start drilling
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down into CloudGuard's workload protection,
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and see how we can perform a deployment.
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We will start with protecting containers.
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Thank you for taking this introductory session.
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I hope you enjoyed it,
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>> and I'll see you in our next one.
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>> [MUSIC]
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