detecting-container-drift-at-runtime▌
mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026
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Detect unauthorized modifications to running containers by monitoring for binary execution drift, file system changes, and configuration deviations from the original container image.
| name | detecting-container-drift-at-runtime |
| description | Detect unauthorized modifications to running containers by monitoring for binary execution drift, file system changes, and configuration deviations from the original container image. |
| domain | cybersecurity |
| subdomain | container-security |
| tags | - container-drift - runtime-security - immutable-containers - falco - kubernetes - container-security - drift-detection - microsoft-defender |
| version | '1.0' |
| author | mahipal |
| license | Apache-2.0 |
| nist_csf | - PR.PS-01 - PR.IR-01 - ID.AM-08 - DE.CM-01 |
Detecting Container Drift at Runtime
Overview
Container drift occurs when running containers deviate from their original image state through unauthorized file modifications, unexpected binary execution, configuration changes, or package installations. Since containers should be treated as immutable infrastructure, any drift is a potential indicator of compromise. Detection techniques leverage the DIE (Detect, Isolate, Evict) model -- an immutable workload should not change during runtime, so any observed change is potentially evidence of malicious activity.
When to Use
- When investigating security incidents that require detecting container drift at runtime
- When building detection rules or threat hunting queries for this domain
- When SOC analysts need structured procedures for this analysis type
- When validating security monitoring coverage for related attack techniques
Prerequisites
- Kubernetes cluster v1.24+ with runtime security tooling
- Falco or Sysdig for runtime drift detection
- Container image registry with image manifests available
- Familiarity with Linux filesystem layers and OverlayFS
Core Concepts
Types of Container Drift
- Binary drift: Execution of binaries not present in the original image (downloaded malware, compiled tools)
- File drift: Creation, modification, or deletion of files in the container filesystem
- Configuration drift: Changes to environment variables, mounted secrets, or runtime parameters
- Package drift: Installation of new packages via apt, yum, pip, or npm at runtime
- Network drift: New listening ports or outbound connections not expected for the workload
Detection Methods
Image-Based Comparison: Compare the running container's filesystem against its source image to identify added, modified, or removed files.
Behavioral Monitoring: Use eBPF or kernel-level monitoring to detect process execution, file access, and network activity that deviates from expected behavior.
Digest Verification: Continuously verify that running container image digests match the approved deployment manifests.
Implementation with Falco
Detecting New Binary Execution
- rule: Drift Detected (Container Image Modified Binary)
desc: Detect execution of a binary not present in the original container image
condition: >
spawned_process and
container and
not proc.pname in (container_entrypoint) and
proc.is_exe_upper_layer = true
output: >
Drift detected: new binary executed in container
(user=%user.name command=%proc.cmdline container=%container.name
image=%container.image.repository:%container.image.tag
exe_path=%proc.exepath)
priority: WARNING
tags: [container, drift]
- rule: Container Shell Spawned
desc: Detect interactive shell in a container that should be immutable
condition: >
spawned_process and
container and
proc.name in (bash, sh, dash, zsh, csh, ksh) and
not proc.pname in (container_entrypoint)
output: >
Shell spawned in container (user=%user.name shell=%proc.name
container=%container.name image=%container.image.repository)
priority: WARNING
tags: [container, drift, shell]
Detecting Package Manager Usage
- rule: Package Manager Execution in Container
desc: Detect use of package managers indicating drift
condition: >
spawned_process and
container and
proc.name in (apt, apt-get, yum, dnf, apk, pip, pip3, npm, gem, cargo)
output: >
Package manager executed in container (user=%user.name
command=%proc.cmdline container=%container.name
image=%container.image.repository)
priority: ERROR
tags: [container, drift, package-manager]
Detecting File System Modifications
- rule: Container File System Write
desc: Detect writes to container upper layer filesystem
condition: >
open_write and
container and
fd.typechar = 'f' and
not fd.name startswith /tmp and
not fd.name startswith /var/log and
not fd.name startswith /proc
output: >
File write in container (user=%user.name file=%fd.name
container=%container.name)
priority: NOTICE
tags: [container, drift, filesystem]
Implementation with Kubernetes Enforcement
Read-Only Root Filesystem
Prevent drift by making container filesystems immutable:
apiVersion: apps/v1
kind: Deployment
metadata:
name: immutable-app
spec:
template:
spec:
containers:
- name: app
image: app:v1.0@sha256:abc123...
securityContext:
readOnlyRootFilesystem: true
allowPrivilegeEscalation: false
runAsNonRoot: true
volumeMounts:
- name: tmp
mountPath: /tmp
- name: cache
mountPath: /var/cache
volumes:
- name: tmp
emptyDir:
sizeLimit: 100Mi
- name: cache
emptyDir:
sizeLimit: 50Mi
Pod Security Standards Enforcement
apiVersion: v1
kind: Namespace
metadata:
name: production
labels:
pod-security.kubernetes.io/enforce: restricted
pod-security.kubernetes.io/audit: restricted
pod-security.kubernetes.io/warn: restricted
Image Digest Verification
Continuous Digest Monitoring
#!/bin/bash
# Compare running container digests against approved manifest
NAMESPACE="production"
kubectl get pods -n "$NAMESPACE" -o json | jq -r '
.items[] |
.spec.containers[] |
"\(.image) \(.imageID)"
' | while read IMAGE IMAGE_ID; do
APPROVED_DIGEST=$(kubectl get deploy -n "$NAMESPACE" -o json | \
jq -r ".items[].spec.template.spec.containers[] | select(.image==\"$IMAGE\") | .image")
if [[ "$IMAGE" != *"@sha256:"* ]]; then
echo "[WARN] Container using mutable tag: $IMAGE"
fi
done
Microsoft Defender for Containers Integration
For Azure Kubernetes environments, Microsoft Defender provides built-in binary drift detection:
{
"alertType": "K8S.NODE_ImageBinaryDrift",
"severity": "Medium",
"description": "Binary executed that was not part of the original container image",
"remediationSteps": [
"Investigate the binary origin and purpose",
"Check if the container was compromised",
"Rebuild the container from a clean image",
"Enable readOnlyRootFilesystem"
]
}
Drift Response Playbook
- Detect: Alert fires on drift event (Falco, Defender, Sysdig)
- Validate: Confirm the drift is not from an approved process (init containers, config reloads)
- Isolate: Apply a deny-all NetworkPolicy to the affected pod
- Investigate: Capture container filesystem diff and process list
- Evict: Delete the drifted pod (ReplicaSet will recreate from clean image)
- Remediate: Fix the root cause (patch vulnerability, update image, tighten RBAC)
References
How to use detecting-container-drift-at-runtime on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add detecting-container-drift-at-runtime
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches detecting-container-drift-at-runtime from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate detecting-container-drift-at-runtime. Access the skill through slash commands (e.g., /detecting-container-drift-at-runtime) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
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Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★46 reviews- ★★★★★Zaid Flores· Dec 12, 2024
detecting-container-drift-at-runtime reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Zaid Nasser· Dec 8, 2024
detecting-container-drift-at-runtime has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Aisha Martinez· Dec 4, 2024
Keeps context tight: detecting-container-drift-at-runtime is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Hassan Bhatia· Nov 27, 2024
Useful defaults in detecting-container-drift-at-runtime — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Anika Ndlovu· Nov 27, 2024
Solid pick for teams standardizing on skills: detecting-container-drift-at-runtime is focused, and the summary matches what you get after install.
- ★★★★★Sofia Sharma· Nov 23, 2024
We added detecting-container-drift-at-runtime from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Noah Thomas· Nov 3, 2024
Registry listing for detecting-container-drift-at-runtime matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Xiao Flores· Oct 22, 2024
detecting-container-drift-at-runtime fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Aisha Anderson· Oct 18, 2024
detecting-container-drift-at-runtime is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Arjun Chen· Oct 18, 2024
We added detecting-container-drift-at-runtime from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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