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Sysdig Blog

Masterclass: AI is more than ChatGPT and LLMs CVE-2026-39987 update: How attackers weaponized marimo to deploy a blockchain botnet via HuggingFace 5 steps to securing AI workloads Marimo OSS Python Notebook RCE: From Disclosure to Exploitation in Under 10 Hours Security briefing: March 2026 The Sysdig MCP server is now available in AWS Marketplace Risk isn’t reduced until you take action: How teams resolve issues in the cloud AI infrastructure security: Why it deserves its own category Three pillars for building effective runtime-powered cloud defense, the right way Closing the cloud security gap with runtime security Seeing risk isn’t stopping it: Why visibility alone isn’t enough TeamPCP expands: Supply chain compromise spreads from Trivy to Checkmarx GitHub Actions AI coding agents are running on your machines — Do you know what they're doing? Runtime security for AI coding agents: Protecting AI-assisted development How runtime insights power every cloud security use case CVE-2026-33017: How attackers compromised Langflow AI pipelines in 20 hours Inline Cloud Response: Accelerating AWS threat containment for SOC teams Runtime malware detection for AWS Fargate Detecting CVE-2026-3288 & CVE-2026-24512: Ingress-nginx configuration injection vulnerabilities for Kubernetes Malware detection with Sysdig Security briefing: February 2026 Leveling up Kubernetes Posture: From baselines to risk-aware admission Eliminating runtime blind spots: How CleanStart and Sysdig build continuous trust across the container lifecycle LLMjacking: From Emerging Threat to Black Market Reality Real risks live at runtime: Why CISOs must care about deep telemetry in 2026 Sysdig named a Leader in the Forrester Wave™: Cloud Native Application Protection Solutions, Q1 2026 How to run rootless containers AI-assisted cloud intrusion achieves admin access in 8 minutes Security briefing: January 2026 Securing GPU-accelerated AI workloads in Oracle Kubernetes Engine Bringing OSS runtime security to AWS: Falco integration with AWS Security Hub CSPM Our customers have spoken: Sysdig rated a Strong Performer in Gartner® Voice of the Customer for Cloud-Native Application Protection Platforms Protecting sensitive business data in preparation for the organization's Gen AI VoidLink threat analysis: Sysdig discovers C2-compiled kernel rootkits AI is still a workload: A practical guide to securing AI workloads How threat actors are using self-hosted GitHub Actions runners as backdoors How Sysdig Sage delivers AI-powered, real-world vulnerability management Security briefing: December 2025 Top 10 ways to get breached in 2026 EtherRAT dissected: How a React2Shell implant delivers 5 payloads through blockchain C2 Introducing runtime file integrity monitoring and response with Sysdig FIM How to detect multi-stage attacks with runtime behavioral analytics EtherRAT: DPRK uses novel Ethereum implant in React2Shell attacks Detecting React2Shell: The maximum-severity RCE vulnerability affecting React Server Components and Next.js The rise of AI agents: How autonomous AI Is transforming cloud security Kubernetes 1.35 - New security features The Urgency of Securing AI Workloads for CISOs Security briefing: November 2025 Quantum and the cloud: Science fiction turned security strategy Cloud security, the right way: What the industry should demand (and why "good enough" isn't) Return of the Shai-Hulud worm affects over 25,000 GitHub repositories Detecting CVE-2024-1086: The decade-old Linux kernel vulnerability that’s being actively exploited in ransomware campaigns What’s old is new again: How to demystify AI security with AIBOMs Securing Kubernetes with agentic cloud security How agentic cloud security reduces real risks Hunting reverse shells: How the Sysdig Threat Research Team builds smarter detection rules Shifting left with AI and MCP: Sysdig + Amazon Q Developer How Falco and Stratoshark close the gap between open source runtime detection and deep forensic analysis Investigating security issues with ChatGPT and the GitHub MCP server New runc vulnerabilities allow container escape: CVE-2025-31133, CVE-2025-52565, CVE-2025-52881 Harden your LLM security with OWASP Security briefing: October 2025 How agentic AI is changing cloud security Kubernetes Incident Response: Detect, investigate, and contain in under 10 minutes Sysdig recognized as a Cloud Security Leader in Latio Tech Cloud Security Market Report AI echolocation of cloud risks using Sysdig & Snyk MCP servers Sysdig MCP Server: Bridging AI and cloud security insights Understanding CVE-2025-49844: “RediShell” Critical Remote Code Execution in Redis How Sysdig secures your containers and Kubernetes Sysdig Security Briefing: September 2025 Cloud security, the right way: The 3 pillars of real-time defense Open source spotlight: Bringing web application security to Falco with Falcoya's Nginx plugin Malicious NPM packages: Are you exposed? 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From air-gapped to private cloud: Security that adapts to your environment
Blair Howard · 2026-04-17 · via Sysdig Blog

Security should align to deployment constraints, not redefine them

Many cloud-native security platforms are primarily designed around a fully connected, SaaS-based operating model.

But that model does not apply for a large segment of organizations.

Globally, infrastructure decisions are shaped by data sovereignty requirements, regulatory frameworks, and internal governance policies. As a result, organizations operate across a range of environments, including private cloud, on-premises infrastructure, and fully air-gapped systems where external connectivity is restricted by design.

These are established operating models, not exceptions.

Security platforms that depend on continuous external connectivity or centralized SaaS processing can introduce architectural friction in these environments. In practice, this often leads to trade-offs between visibility, control, and compliance. Teams may find themselves limiting coverage or redesigning infrastructure to accommodate the tool rather than selecting a solution that fits their constraints.

Sysdig is designed to operate across these constraints.

A cloud-native security architecture that supports multiple deployment models

Sysdig Secure is a cloud-native security platform that protects Kubernetes, containers, and hosts across SaaS and self-managed deployments, including on-premises, private cloud, and air-gapped environments.

Rather than enforcing a single delivery model, the platform supports multiple deployment patterns while maintaining a consistent runtime security foundation. This foundation is based on runtime visibility using eBPF and Falco, which provides system-level telemetry across environments. Behavioral detection capabilities are derived from this telemetry and are adapted to each deployment model, including differences in how rules are delivered and updated.

This consistency applies specifically to how runtime activity is captured and analyzed. At the same time, features, integrations, and data workflows vary depending on the deployment model.

Across these environments, Sysdig enables runtime threat detection using behavioral signals derived from system activity. It supports vulnerability management from build through runtime, with prioritization based on exploitability. It also supports continuous compliance monitoring aligned with frameworks such as CIS, PCI DSS, NIST, and ISO, along with incident response and forensic analysis using system-level telemetry.

However, how these capabilities are delivered and operationalized differs depending on the deployment model.

SaaS deployments can leverage centralized data processing, broader integrations, and continuous analytics. In environments where SaaS delivery is viable, this model typically enables faster access to new capabilities and a broader set of analytics and integrations. In contrast, self-managed and air-gapped deployments prioritize local data processing, controlled data flows, and investigation workflows that operate entirely within the environment.

The objective is not feature parity across environments. It is to provide a consistent security model that functions effectively within each set of constraints.

Private cloud: Kubernetes security with controlled data residency

Private cloud environments are often used to balance cloud-native architecture with data residency and governance requirements. This is particularly relevant for organizations operating under GDPR and similar regulatory frameworks, where data location and handling are subject to strict controls.

Sysdig Secure can be deployed within private cloud environments to ensure that security telemetry, detection, and analysis remain within defined boundaries. In this model, organizations can apply runtime threat detection, enforce compliance controls, and maintain visibility into Kubernetes workloads without exporting sensitive data outside of the environment.

For example, a financial institution operating within a regional private cloud can enforce runtime security policies and monitor workload behavior while ensuring that all security data remains within jurisdictional limits. This approach allows the organization to maintain both regulatory alignment and modern cloud-native security practices.

On-premises: System-level visibility with local control

On-premises environments remain critical for workloads with latency sensitivity, legacy dependencies, or regulatory constraints.

In these environments, traditional security approaches often provide visibility at the host level but lack insight into containerized and orchestrated workloads. This creates gaps in understanding how applications behave at runtime.

Sysdig addresses this by capturing system-level activity using eBPF and correlating it with container and Kubernetes context. This enables detailed visibility into process behavior, network activity, and file access within modern workloads.

Because deployment is self-managed, data collection, processing, and storage remain under the organization’s control.

For example, an organization running Kubernetes on-premises can detect anomalous process execution within containers and investigate runtime behavior without relying on external services or data transfer. This ensures that operational requirements and data control are maintained without sacrificing visibility.

Air-gapped environments: Security within isolated environments

Air-gapped environments impose strict constraints. External connectivity is not available, and all security capabilities must operate entirely within the environment.

Sysdig Secure supports these scenarios through self-managed deployments designed to function without external dependencies.

In air-gapped environments, Sysdig doesn’t rely on a constant internet connection for security updates. Instead, new Falco rules and vulnerability intelligence are packaged into update bundles that teams can periodically download in a connected location, move into their secure environment, and apply locally. This keeps detection content current while ensuring sensitive systems remain fully isolated from external networks

In this model, runtime detection, compliance checks, and forensic capabilities are executed locally. Data does not leave the environment, and integrations are limited to systems available within the isolated network.

Operationally, this changes how security teams interact with the platform. Instead of relying on continuous external analytics, investigations are typically scoped and targeted based on specific detections.

Using tools such as Sysdig Inspect and capture-based analysis, analysts can investigate activity within defined time windows. They can examine processes, network connections, and file behavior, then analyze system-level events to understand what occurred.

In critical infrastructure or defense environments, this allows analysts to perform full investigations locally while maintaining strict control over sensitive data. This approach emphasizes precision and relevance, which is essential in highly controlled environments.

Consistency in detection and investigation, not uniform capability

While deployment models differ, Sysdig maintains consistency in the underlying approach to runtime security.

Behavioral signals derived from system activity, Falco-based detection logic, and investigation workflows remain aligned across environments. This allows security teams to apply a consistent methodology when identifying and responding to threats.

At the same time, capabilities are adapted to reflect the constraints of each deployment model.

SaaS environments can support continuous analytics and broader ecosystem integrations. As a result, SaaS deployments can provide a more extensive set of capabilities, while self-managed and air-gapped deployments prioritize predictable and controlled operation, local processing, and controlled data handling.

This distinction is intentional. It ensures that security capabilities remain effective and operationally viable within each environment, rather than attempting to replicate SaaS behavior in contexts where that behavior is not feasible.

Reduces fragmentation across environments

Organizations operating across multiple environments often deploy different security tools for each one. This leads to fragmented visibility, inconsistent workflows, and increased operational overhead.

Sysdig provides a unified platform approach with deployment-specific implementations, all while maintaining a consistent runtime security foundation. Where supported, it integrates with SIEM, SOAR, and ticketing systems within each environment.

This approach allows organizations to standardize their security model without requiring identical infrastructure or deployment patterns.

Security aligned to real-world infrastructure

Modern infrastructure is inherently heterogeneous. Workloads may span public cloud, private cloud, on-premises systems, and isolated environments.

Security platforms need to operate within this reality.

Sysdig Secure enables organizations to protect Kubernetes, containers, and hosts across these environments while maintaining control over data handling, deployment architecture, and operational workflows.

The platform does not assume uniform infrastructure. It is designed to function within differing constraints while preserving a consistent approach to runtime security.

Sysdig provides adaptable security within defined constraints

Across all environments, the objectives remain consistent: Organizations need to reduce risk, maintain control, and respond effectively to threats.

Sysdig Secure supports these objectives by providing runtime visibility, threat detection, and forensic capabilities that can be deployed according to environmental constraints.

Effective cloud-native security is not defined by identical capabilities across environments. It is defined by the ability to deliver appropriate and effective security within each environment’s operational model.

See how Sysdig fits your environment, and book a demo today.