spotter
by madhuakula
Spotter is a versatile Kubernetes security scanner that detects vulnerabilities, misconfigurations, and compliance issues using CEL-based rules.
Spotter is a comprehensive Kubernetes security scanner that uses CEL-based rules to identify security vulnerabilities, misconfigurations, and compliance violations across your Kubernetes clusters, manifests, and CI/CD pipelines.
Primary Use Case
Spotter is designed for DevOps and security teams to enhance the security posture of Kubernetes environments. It scans Kubernetes clusters, manifests, and CI/CD pipelines to identify and address security vulnerabilities and compliance violations.
- CEL-based rule definitions for flexible security scanning
- Supports multiple output formats including JSON and SARIF
- Scans both Kubernetes manifests and live clusters
- Custom rule management and validation
- Extensible and performance-oriented architecture
Installation
- go install github.com/madhuakula/spotter@latest
- docker pull ghcr.io/madhuakula/spotter:latest
- Download the latest release from GitHub Releases
Usage
>_ spotter scan manifests --path deployment.yamlScan a single Kubernetes manifest file for security issues.
>_ spotter scan clusterScan the current Kubernetes cluster context for security vulnerabilities.
>_ spotter rules listList all available security rules.
>_ spotter rules validate --path ./custom-rules/Validate custom security rules.
>_ spotter scan manifests --path ./manifests/ --output jsonScan manifests and output results in JSON format.
- Repurposing: Spotter can be adapted to scan non-Kubernetes environments by converting configurations into Kubernetes-like manifests, allowing it to identify misconfigurations in other cloud services.
- Chaining: Combine Spotter with a tool like Falco for real-time threat detection and alerting, leveraging Spotter's scanning capabilities to preemptively identify vulnerabilities that Falco can then monitor for exploitation attempts.
- Evasion/Detection: Attackers might bypass Spotter by using obfuscated or encrypted configurations. To detect such attempts, integrate Spotter with a decryption tool or a configuration management system that logs changes.
- Data Fusion: Correlate Spotter's output with network traffic analysis tools like Zeek to identify anomalous patterns that coincide with detected misconfigurations, enhancing threat detection capabilities.
- Automation: Integrate Spotter into a CI/CD pipeline using tools like Jenkins to automatically scan Kubernetes manifests before deployment, ensuring vulnerabilities are caught early and reducing the risk of deploying insecure configurations.
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