k8s-webhook-abuse
Fail
Audited by Gen Agent Trust Hub on Sep 23, 2026
Risk Level: HIGHCREDENTIALS_UNSAFEDATA_EXFILTRATIONCOMMAND_EXECUTIONPRIVILEGE_ESCALATIONINDIRECT_PROMPT_INJECTION
Full Analysis
- [CREDENTIALS_UNSAFE]: The skill is designed to capture and extract sensitive information, including Secrets, Tokens, and Flags, from Kubernetes Mutating Webhooks by forging AdmissionReview requests.
- Evidence: Phase 3 in
SKILL.mddemonstrates extracting Base64 patches containing values likewiz_k8s_lan_party{...}. - [DATA_EXFILTRATION]: Forging AdmissionReview requests to trick internal cluster services into revealing sensitive configuration data intended for other resources.
- Evidence: Usage of
curlto POST fake requests to internal service endpoints such ashttps://kyverno-svc.kyverno.svc.cluster.local/mutate. - [COMMAND_EXECUTION]: Utilizes system commands to perform network operations, file creation, and data processing.
- Evidence: Usage of
curl,cat,base64, andjqto interact with Webhooks and parse stolen data. - [PRIVILEGE_ESCALATION]: The techniques facilitate bypassing admission control security mechanisms to obtain privileged credentials, enabling lateral movement within a Kubernetes environment.
- [INDIRECT_PROMPT_INJECTION]: The skill processes responses from external services (Webhooks) without sufficient sanitization, creating an attack surface for indirect injection if the service is compromised.
- Ingestion points: Responses from
curlcommands inSKILL.mdPhase 2 and Phase 4. - Boundary markers: Absent; response data is piped directly to processing tools.
- Capability inventory: Network operations (
curl), file writing (cat), and data parsing (jq,base64). - Sanitization: Absent; the skill directly decodes and parses responses from the target service.
Recommendations
- AI detected serious security threats
Audit Metadata