跳到正文
cccskills
免费在 GitHub 公开

detecting-container-drift-at-runtime

Detect unauthorized modifications to running containers by monitoring for binary execution drift, file system changes, and configuration deviations from the original container image.

中文简介正在准备中。当前显示原文说明。

集成工具Kubernetes
查看安装方法

包含的文件(8)

  • SKILL.md7.8 KB
  • assets/template.md728 B
  • LICENSE11.0 KB
  • references/api-reference.md2.0 KB
  • references/standards.md1.2 KB
  • references/workflows.md1.7 KB
  • scripts/agent.py5.8 KB
  • scripts/process.py7.6 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

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

  1. Binary drift: Execution of binaries not present in the original image (downloaded malware, compiled tools)
  2. File drift: Creation, modification, or deletion of files in the container filesystem
  3. Configuration drift: Changes to environment variables, mounted secrets, or runtime parameters
  4. Package drift: Installation of new packages via apt, yum, pip, or npm at runtime
  5. 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

  1. Detect: Alert fires on drift event (Falco, Defender, Sysdig)
  2. Validate: Confirm the drift is not from an approved process (init containers, config reloads)
  3. Isolate: Apply a deny-all NetworkPolicy to the affected pod
  4. Investigate: Capture container filesystem diff and process list
  5. Evict: Delete the drifted pod (ReplicaSet will recreate from clean image)
  6. Remediate: Fix the root cause (patch vulnerability, update image, tighten RBAC)

References

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

Create forensically sound bit-for-bit disk images using dd and dcfldd while preserving evidence integrity through hash verification.

中文简介正在准备中。当前显示原文说明。

micsapp/micstec-skills42026年3月20日 更新

Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.

中文简介正在准备中。当前显示原文说明。

micsapp/micstec-skills42026年3月20日 更新

Detect dangerous ACL misconfigurations in Active Directory using ldap3 to identify GenericAll, WriteDACL, and WriteOwner abuse paths

中文简介正在准备中。当前显示原文说明。

micsapp/micstec-skills42026年3月20日 更新

Perform static analysis of Android APK malware samples using apktool for decompilation, jadx for Java source recovery, and androguard for permission analysis, manifest inspection, and suspicious API call detection.

中文简介正在准备中。当前显示原文说明。

micsapp/micstec-skills42026年3月20日 更新

Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect BOLA/IDOR attacks, rate limit bypass, credential scanning, and injection attempts. Uses pandas for statistical analysis of request patterns and anomaly detection. Use when investigating API abuse or building API-specific threat detection rules.

中文简介正在准备中。当前显示原文说明。

micsapp/micstec-skills42026年3月20日 更新

Analyze advanced persistent threat (APT) group techniques using MITRE ATT&CK Navigator to create layered heatmaps of adversary TTPs for detection gap analysis and threat-informed defense.

中文简介正在准备中。当前显示原文说明。

micsapp/micstec-skills42026年3月20日 更新

查看 micsapp 的全部技能

报告此技能的问题