analyzing-kubernetes-audit-logs
Parses Kubernetes API server audit logs (JSON lines) to detect exec-into-pod, secret access, RBAC modifications, privileged pod creation, and anonymous API access, and builds SIEM detection rules from the event patterns. Use when investigating a suspected cluster compromise, reconstructing what an attacker did through the API server, or writing Kubernetes-specific detection content. Keywords: audit policy, audit log, kube-apiserver, exec into pod, RBAC change, anonymous access, detection rules. Do not use for syscall-level detection inside a running container - use detecting-container-runtime-threats-with-falco. '
- License 许可
- Apache-2.0
- 最近更新
- 2026-08-31
- Stars
- ★ 3.6w
- Forks
- 4.4k
01 前言 Front Matter
- name
- analyzing-kubernetes-audit-logs
- tags
- [ "kubernetes-security", "container-security", "audit-log-analysis", "rbac", "privilege-escalation", "k8s-api-server", "threat-detection" ]
- author
- mahipal
- domain
- cybersecurity
- license
- Apache-2.0
- version
- 1.0
- nist_csf
- [ "PR.PS-01", "PR.IR-01", "ID.AM-08", "DE.CM-01" ]
- subdomain
- container-security
- description
- Parses Kubernetes API server audit logs (JSON lines) to detect exec-into-pod, secret access, RBAC modifications, privileged pod creation, and anonymous API access, and builds SIEM detection rules from the event patterns. Use when investigating a suspected cluster compromise, reconstructing what an attacker did through the API server, or writing Kubernetes-specific detection content. Keywords: audit policy, audit log, kube-apiserver, exec into pod, RBAC change, anonymous access, detection rules. Do not use for syscall-level detection inside a running container - use detecting-container-runtime-threats-with-falco. '
- mitre_attack
- [ "T1610", "T1613", "T1078", "T1552.007" ]
02 资源文件 3
- 许可证LICENSE11.0 KB
- 参考文档references/api-reference.md1.6 KB
- 脚本scripts/agent.py7.7 KB
03 SKILL.md 正文
Analyzing Kubernetes Audit Logs
When to Use
- When investigating security incidents that require analyzing kubernetes audit logs
- 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
- Familiarity with container security concepts and tools
- Access to a test or lab environment for safe execution
- Python 3.8+ with required dependencies installed
- Appropriate authorization for any testing activities
Instructions
Parse Kubernetes audit log files (JSON lines format) to detect security-relevant events including unauthorized access, privilege escalation, and data exfiltration.
import json
with open("/var/log/kubernetes/audit.log") as f:
for line in f:
event = json.loads(line)
verb = event.get("verb")
resource = event.get("objectRef", {}).get("resource")
user = event.get("user", {}).get("username")
if verb == "create" and resource == "pods/exec":
print(f"Pod exec by {user}")
Key events to detect:
- pods/exec and pods/attach (shell into containers)
- secrets access (get/list/watch)
- clusterrolebindings creation (RBAC escalation)
- Privileged pod creation
- Anonymous or system:unauthenticated access
Examples
# Detect secret enumeration
if verb in ("get", "list") and resource == "secrets":
print(f"Secret access: {user} -> {event['objectRef'].get('name')}")
04 同仓库更多 Skills
verifying-build-provenance-with-slsa-sigstore
Verifies artifact signatures and SLSA provenance using Sigstore's cosign (verify, verify-attestation, verify-blob-attestation) and slsa-verifier (verify-artifact), enforcing keyless OIDC builder identity and source repo against SLSA Build levels. Use in CI/CD before deploying artifacts, when consuming third-party attestations, establishing a SLSA Build L3 pipeline, or confirming provenance during incident response or admission control.
validating-tpm-measured-boot-attestation
Verifies TPM 2.0 measured-boot integrity and remote attestation with tpm2-tools -- reading PCRs (tpm2_pcrread), replaying the boot event log, generating and checking signed quotes (tpm2_quote/tpm2_checkquote), and sealing secrets to a PCR policy. Use to confirm a system booted trusted firmware/kernel for Zero Trust device posture, detect boot-chain tampering via PCR drift, or build a golden-value baseline for fleet attestation.
validating-backup-integrity-for-recovery
Validates backup integrity through cryptographic hash verification, automated restore testing, corruption detection, and recoverability checks to confirm backups are reliable for disaster recovery and ransomware response. Use before relying on backups for recovery, when building post-backup validation pipelines, auditing backup infrastructure for compliance, or checking immutable/air-gapped backups for silent corruption or tampering.
triaging-windows-with-kape
Runs KAPE (Kroll Artifact Parser and Extractor) to collect targeted forensic artifacts (registry hives, $MFT, event logs, prefetch, browser data) via Targets and parse them with Modules wrapping Eric Zimmerman's EZ Tools (PECmd, MFTECmd, RECmd). Use during early incident containment/triage when full disk imaging is impractical but a defensible, parseable Windows artifact set is needed quickly, including at-scale remote collection.
triaging-vulnerabilities-with-ssvc-framework
Triages and prioritizes vulnerabilities with CISA's Stakeholder-Specific Vulnerability Categorization (SSVC) decision tree, weighing exploitation status (via the CISA KEV catalog and FIRST EPSS API), technical impact, automatability, and mission prevalence to output Track/Track*/Attend/Act decisions. Use when prioritizing vulnerability scan results (OpenVAS, Nessus, Qualys) for remediation planning beyond raw CVSS scores.
triaging-security-incident
Performs initial triage of security incidents using the NIST SP 800-61r3 and SANS PICERL frameworks, classifying incident type, assigning priority by business impact, and routing to the appropriate response team. Use when a SIEM/EDR alert needs human classification, concurrent alerts must be prioritized, or a user report or threat-intel IOC match requires initial incident categorization.