Cloud Security: Threat & Vulnerability Management (CTVM) Framework

The era of static, monthly vulnerability scans is over. In a cloud environment where infrastructure is spun up and torn down in seconds via code, traditional vulnerability management (VM) creates a dangerous visibility gap.

Modern security demands a shift from passive scanning to Cloud-native Vulnerability Management a dynamic process that fuses threat intelligence with automated remediation.

This guide provides a process-oriented framework for architects and CISOs. We move beyond generic patch everything advice to a Threat-Led Prioritization model, distinguishing the critical nuances between VMs, containers, and serverless functions.

1. The Cloud Security Landscape: Beyond the Perimeter

Cloud security is no longer about guarding a perimeter; it is about managing the integrity of the workload and the identity accessing it.

The fundamental challenge in the cloud is velocity. DevOps teams deploy code faster than security teams can manually review it. This velocity creates a discovery gap. By the time a traditional scanner identifies a vulnerability in a container, that container may have already been replaced three times.

The Shared Responsibility Model Reality

Before implementing any tool, you must map the Shared Responsibility Model to your vulnerability landscape.

• IaaS (e.g., EC2, Azure VM): You own the OS patching, application dependencies, and network configuration.
• PaaS/Container (e.g., EKS, AKS): You own the container image and code; the provider manages the underlying node kernel (usually).
• Serverless (e.g., Lambda): You own only the application code and libraries.

Key Insight: Effective CTVM requires different workflows for different compute types. Applying a standard CVSS v3.1 threshold to a Serverless function often leads to false positives regarding OS-level flaws you cannot patch.

2. Anatomy of Cloud Vulnerabilities: VM vs. Container vs. Serverless

To build a robust Cloud Security Vulnerability Management Lifecycle, we must first dissect the target. A “vulnerability” looks different depending on the asset.

A. Virtual Machines (The Legacy Cloud)

• The Threat: Unpatched OS kernels, open RDP/SSH ports, legacy agent fatigue.
• Management Style: Agent-based scanning (e.g., AWS Inspector agents).
• Persistence: Long-lived assets.

B. Containerized Environments (Kubernetes)

• The Threat: Malicious base images, insecure container runtimes, privilege escalation (breaking out of the container).
• Guidance: Adherence to NIST SP 800-190 (Application Container Security Guide).
• Management Style: Registry scanning (pre-deployment) and runtime defense.
• Nuance: Vulnerabilities here are often “ephemeral.” If a pod is vulnerable, you do not patch the pod; you rebuild the image.

C. Serverless Functions

• The Threat: Insecure third-party libraries (supply chain attacks), over-permissive IAM roles, hardcoded secrets.
• Management Style: Static Application Security Testing (SAST) and Software Composition Analysis (SCA).
• Blind Spot: Traditional network scanners cannot see serverless functions.

Scenario: A misconfigured S3 bucket (Infrastructure vulnerability) combined with a vulnerable library in a Lambda function (Code vulnerability) allows an attacker to extract data without ever hitting a firewall. This is why Cloud Workload Protection Platforms (CWPP) must cover the entire stack.

3. The CTVM Operational Framework: A 5-Step Lifecycle

This framework bridges the gap between Threat Intelligence and Vulnerability Management.

Phase 1: Continuous Discovery & Asset Inventory

You cannot secure what you cannot see. In the cloud, assets include code repositories, running workloads, and IaC templates.

• Action: Integrate Cloud Security Posture Management (CSPM) tools to auto-discover resources across multi-cloud environments.
• Goal: 100% real-time asset visibility.

Phase 2: Vulnerability Assessment (Shift-Left)

Move assessment early into the CI/CD pipeline (DevSecOps).

• Technique: Scan Infrastructure as Code (IaC) templates (Terraform, CloudFormation) for misconfigurations before deployment.
• Tooling: Use tools that benchmark against CIS Benchmarks for AWS, Azure, and GCP.

Phase 3: Threat-Informed Prioritization

This is the most critical maturity step. DO NOT prioritize based on CVSS score alone. A CVSS 9.8 vulnerability on a private, disconnected subnet is less urgent than a CVSS 7.5 vulnerability on a public-facing web app actively being exploited.

The Prioritization Formula:
$$Priority = (Asset Criticality) \times (Vulnerability Severity) \times (Threat Intelligence)$$

• Threat Intel Sources:
  • CISA KEV Catalog (Known Exploited Vulnerabilities).
  • MITRE ATT&CK Cloud Matrix (Mapping vulnerability to attacker TTPs).
  • Real-time Exploit Maturity (Is there a POC kit available?).

Phase 4: Automated Remediation

Manual patching fails at cloud scale.

• Mutable Infrastructure: Use systems managers to patch running VMs.
• Immutable Infrastructure: Fail the build in Jenkins/GitLab if a vulnerability exceeds risk thresholds. Force the developer to update the base image.

Phase 5: Verification & Reporting

Confirm remediation via a follow-up scan. Track “Mean Time to Remediate” (MTTR) as a KPI.

4. Selecting the Right Tools: Solution Comparison

When evaluating Cloud-native vulnerability management solutions, the debate often centers on Agent-based vs. Agentless scanning.

Feature	Agent-Based Scanning	Agentless Scanning (Snapshot)	Hybrid Approach (Recommended)
Depth	High. Can see active processes and memory.	Medium. Inspects disk snapshots/APIs.	Maximum.
Performance	Consumes resources on the workload.	Zero impact on running workload.	Balanced.
Deployment	Difficult. Requires installation on every asset.	Easy. API-connected instantly.	Use agents for critical VMs, agentless for full coverage.
Real-time	Yes. Continuous monitoring.	No. Periodic (snapshot frequency).	Near real-time.
Examples	CrowdStrike, Tenable Agents	Orca Security, Wiz	Azure Defender for Cloud, Google Cloud SCC

Selection Criteria:

1. Multi-Cloud Support: Does it normalize data across AWS, Azure, and GCP?
2. Container Visibility: Does it map vulnerabilities to specific Kubernetes clusters and pods?
3. Context Awareness: Can it visualize the “Attack Path” (e.g., Vulnerability + Internet Exposure + IAM Admin Rights)?

5. Execution Framework: The Maturity Model & Best Practices

To guide your organization, use this Cloud Security Maturity Model. Most organizations currently sit at Level 2.

The Cloud Security Maturity Model

Stage	Description	Characteristics
1. Ad-Hoc	Reactive & Manual	Manual scanning, spreadsheets, patching only after audits. No distinction between cloud vs. on-prem strategies.
2. Defined	Compliance-Driven	Regular scans using standard tools (AWS Inspector). Focus on meeting CIS Benchmarks. CVSS-only prioritization.
3. Integrated	DevSecOps	Scans integrated into CI/CD pipelines. Container registries scanned automatically. Basic IaC scanning.
4. Managed	Threat-Centric	Prioritization driven by Threat Intelligence (CISA KEV). Automated ticketing (Jira integration). Agentless scanning adopted for coverage.
5. Optimized	Self-Healing	Automated remediation code triggers. Shift-left security blocks insecure builds. AI-driven risk analysis of attack paths.

Practical Execution: IaC Remediation Example

Moving to Optimized requires fixing problems at the source (Code), not the symptom (Runtime).

Scenario: A security scan identifies a publicly accessible security group in AWS.
Remediation: Do not close the port in the AWS Console. Fix the Terraform code.

Bad Terraform:

resource "aws_security_group" "allow_all" {
  name        = "allow_all"
  description = "Allow all inbound traffic"
  ingress {
    from_port   = 0
    to_port     = 0
    protocol    = "-1"
    cidr_blocks = ["0.0.0.0/0"] # VULNERABILITY: World Open
  }
}

Secure Terraform (Remediated):

resource "aws_security_group" "app_sg" {
  name        = "app_specific_sg"
  description = "Allow HTTP from Load Balancer only"
  ingress {
    from_port       = 80
    to_port         = 80
    protocol        = "tcp"
    security_groups = [aws_security_group.lb_sg.id] # SECURE: Chained SG
  }
}

Strategic Recommendations for 2026

• Adopt EPSS (Exploit Prediction Scoring System): Move beyond CVSS. EPSS predicts the probability of exploitation.
• Enforce Risk Acceptance Policies: If a vulnerability cannot be fixed (business requirement), it must be formally accepted with an expiration date and compensating controls (e.g., WAF rules).
• Unified Dashboard: Use a CNAPP (Cloud-Native Application Protection Platform) to view VM, Container, and Serverless issues in a single pane of glass.

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Disclaimer: Tool capabilities (AWS Inspector, Azure Defender, etc.) are based on features available as of mid-2026. Always verify the latest documentation from cloud providers.