Sweet Security

Your company is in the market for a runtime-powered CNAPP and you've heard of Sweet Security. You're wondering if they use AI, and how do they use it? Sweet Security positions itself as a runtime-powered Cloud-Native Application Protection Platform, designed to watch your applications and cloud workloads while they are actually running. Traditional CSPM and code scanners are valuable before deployment, but they can miss fast-moving threats and zero-days that emerge in production. By focusing on real-time protection, Sweet Security aims to detect and stop risks as they unfold across containers, Kubernetes, serverless, and virtual machines in AWS, Azure, and Google Cloud. Do they use AI? Runtime analytics in modern CNAPPs typically leverage machine learning techniques for anomaly detection, behavior profiling, and automated correlation. Expect capabilities that learn normal patterns for processes, identities, and network flows, then surface suspicious deviations with high-priority alerts. As with any vendor, confirm details during your proof of concept: models used, data sources, explainability, false-positive handling, and how detections map to MITRE ATT&CK. Core capabilities to look for include runtime threat detection and response, workload and container protection, Kubernetes visibility, and posture management that ties misconfigurations to live exploitation risk. Many buyers also evaluate identity insight similar to CIEM, attack path analysis, and exposure scoring that blends CSPM findings with runtime signals. Integrations with SIEM and SOAR platforms, ticketing tools like Jira and ServiceNow, and messaging tools such as Slack or Microsoft Teams are common and reduce operational friction. How it works in production: a runtime-first platform typically ingests cloud-native telemetry like AWS CloudTrail, VPC Flow Logs, GuardDuty findings, Azure Activity Logs, Microsoft Defender for Cloud alerts, GCP Audit Logs, and Kubernetes audit events. It may add lightweight sensors at the node or container layer, often using Linux eBPF to observe process, file, and network activity with minimal overhead, or it can operate agentless for certain use cases via cloud APIs. The goal is to correlate signals in real time so security teams can see lateral movement, privilege misuse, suspicious outbound traffic, and attempts to exploit zero-day vulnerabilities even when no patch exists yet. Pricing and packaging are typically subscription-based SaaS, tiered by factors such as number of workloads or nodes, cloud accounts, data volume, and retention. Expect enterprise options for SSO, RBAC, audit logging, and support SLAs. The best path is to request a scoped trial or POC that includes high-fidelity test scenarios, deployment to a non-production Kubernetes cluster like EKS, AKS, or GKE, and measurable success criteria around alert quality and mean time to detect. How does Sweet Security compare to other cloud security vendors like Wiz, Palo Alto Networks Prisma Cloud, Orca Security, Lacework, and CrowdStrike Falcon Cloud Security? Its differentiation is the runtime-first strategy. If your priority is catching active threats in production and shrinking alert noise by adding live context to posture findings, a runtime-powered CNAPP can be compelling. If your immediate need is breadth of posture checks or compliance-only reporting, more traditional CSPM-led tools may be sufficient, but adding runtime context usually improves prioritization and response. Who should consider it? Teams running Kubernetes, microservices, and serverless at scale, organizations with strict compliance needs such as PCI DSS, SOC 2, HITRUST, or financial services standards, and any enterprise that wants to merge shift-left security with runtime detection and response. Key questions for vendors include: multi-cloud depth, Kubernetes coverage, data residency, performance overhead, integration breadth, and the transparency of AI-driven detections. Video Chapters - 00:00 Does Sweet Security use AI? - 01:35 What is Runtime-Powered CNAPP? - 03:10 Core Capabilities - 05:02 How it Works in Production - 06:28 Integrations and Deployments - 07:45 Pricing and Packaging - 09:02 Pros and Cons vs Competitors - 10:40 Who Should Buy - 11:30 Demo and Next Steps #CloudSecurity #CNAPP #RuntimeSecurity #Kubernetes #DevSecOps More information on stackinsight.net/sweet-security-review

As part of Tamnoon’s CDR Showdown, Orel Ben Ishay, VP of R&D at Sweet Security, delivers a full live demo of our Cloud Detection and Response (CDR) capabilities. See how Sweet Security unifies runtime visibility, AI-powered threat detection, and rapid response across the entire cloud stack. In this session, Orel demonstrates how our CDR detects advanced threats in real time, correlates activity across the attack chain, and provides the context and tooling to investigate and respond fast. Whether you’re in cloud security, incident response, or DevSecOps, this Tamnoon-hosted showcase reveals how Sweet Security helps you stay ahead of modern cloud attacks.