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Este documento descreve um tipo de descoberta de ameaça no Security Command Center. As descobertas de ameaças são geradas por
detectores de ameaças quando eles detectam
uma ameaça potencial nos seus recursos da nuvem. Para uma lista completa das descobertas de ameaças disponíveis, consulte o índice de descobertas de ameaças.
Visão geral
Um modelo de machine learning identificou um código Python executado como malicioso.
Os invasores podem usar o Python para transferir ferramentas e executar comandos sem binários. Garantir que os contêineres sejam imutáveis é uma prática recomendada importante.
O uso de scripts para transferir ferramentas pode imitar a técnica de transferência de ferramentas de entrada do invasor e resultar em detecções indesejadas.
Como responder
Para responder a essa descoberta, faça o seguinte:
Etapa 1: verificar os detalhes da descoberta
Abra uma descoberta Execution: Malicious Python executed, conforme direcionado em Como verificar descobertas. O painel de detalhes da descoberta é aberto na guia Resumo.
Na guia Resumo, confira as informações nas seguintes seções:
O que foi detectado, especialmente os seguintes campos:
Binário do programa: detalhes sobre o interpretador que invocou o script.
Script: caminho absoluto do nome do script no disco. Esse atributo só aparece para scripts gravados em disco, não para execução de scripts literais, por exemplo, python3 -c
Argumentos: os argumentos fornecidos ao invocar o script.
Recurso afetado, especialmente os seguintes campos:
Nome completo do recurso: o nome completo do recurso
do cluster, incluindo o número, o local e o nome do projeto.
Links relacionados, principalmente os seguintes campos:
Indicador do VirusTotal: link para a página de análise do VirusTotal.
Na visualização detalhada da descoberta, clique na guia JSON.
No JSON, observe os seguintes campos.
finding:
processes:
script:
contents: o conteúdo do script executado, que pode ser truncado por
motivos de desempenho. Isso pode ajudar na sua investigação
sha256: o hash SHA-256 de script.contents
resource:
project_display_name: o nome do projeto que contém o recurso.
sourceProperties:
Pod_Namespace: o nome do namespace do Kubernetes do pod.
Pod_Name: o nome do pod do GKE.
Container_Name: o nome do contêiner afetado.
Container_Image_Uri: o nome da imagem do contêiner que está sendo executada.
VM_Instance_Name: o nome do nó do GKE em que o pod foi executado.
Identifique outras descobertas que ocorreram em um momento semelhante para esse contêiner. Por exemplo, se o script soltar um binário, verifique se há descobertas relacionadas a ele.
Etapa 2: verificar o cluster e o nó
No console Google Cloud , acesse a página Clusters do Kubernetes.
Na barra de ferramentas do console do Google Cloud , selecione o projeto listado em
resource.project_display_name, se necessário.
Selecione o cluster listado na linha Nome completo do recurso na guia Resumo dos detalhes da descoberta. Anote os metadados sobre o cluster e o proprietário dele.
Clique na guia Nós. Selecione o nó listado em VM_Instance_Name.
Clique na guia Detalhes e anote a
anotação container.googleapis.com/instance_id.
Etapa 3: verificar o pod
No console Google Cloud , acesse a página Cargas de trabalho do Kubernetes.
Verifique o valor de hash SHA-256 do binário sinalizado como malicioso no
VirusTotal clicando no link em
Indicador do VirusTotal. O VirusTotal é um serviço da Alphabet que
fornece contexto sobre arquivos, URLs, domínios e endereços IP
potencialmente maliciosos.
Para desenvolver um plano de resposta, combine os resultados da investigação com a pesquisa do MITRE e a análise do VirusTotal.
Etapa 7: implementar a resposta
O plano de resposta a seguir pode ser apropriado para essa descoberta, mas também pode afetar as operações.
Avalie cuidadosamente as informações coletadas na investigação para determinar a melhor maneira de
resolver as descobertas.
Se o Python estiver fazendo as mudanças pretendidas no contêiner, recrie a imagem do contêiner para que nenhuma mudança seja necessária. Assim, o contêiner pode
ser
imutável.
Caso contrário, entre em contato com a pessoa a quem o projeto com o contêiner comprometido pertence.
Interrompa ou exclua o
contêiner comprometido e substitua-o por um
novo contêiner.
[[["Fácil de entender","easyToUnderstand","thumb-up"],["Meu problema foi resolvido","solvedMyProblem","thumb-up"],["Outro","otherUp","thumb-up"]],[["Difícil de entender","hardToUnderstand","thumb-down"],["Informações incorretas ou exemplo de código","incorrectInformationOrSampleCode","thumb-down"],["Não contém as informações/amostras de que eu preciso","missingTheInformationSamplesINeed","thumb-down"],["Problema na tradução","translationIssue","thumb-down"],["Outro","otherDown","thumb-down"]],["Última atualização 2025-09-05 UTC."],[],[],null,["| Premium and Enterprise [service tiers](/security-command-center/docs/service-tiers)\n\nThis document describes a threat finding type in Security Command Center. Threat findings are generated by\n[threat detectors](/security-command-center/docs/concepts-security-sources#threats) when they detect\na potential threat in your cloud resources. For a full list of available threat findings, see [Threat findings index](/security-command-center/docs/threat-findings-index).\n\nOverview\n| **Preview**\n|\n|\n| This feature is subject to the \"Pre-GA Offerings Terms\" in the General Service Terms section\n| of the [Service Specific Terms](/terms/service-terms#1).\n|\n| Pre-GA features are available \"as is\" and might have limited support.\n|\n| For more information, see the\n| [launch stage descriptions](/products#product-launch-stages).\n\nA machine learning model identified executed Python code as malicious.\nAttackers can use Python to transfer tools and execute commands without binaries. Ensuring that your containers are immutable is an important [best practice](https://kubernetes.io/docs/concepts/containers/#container-images).\nUsing scripts to transfer tools can mimic the attacker technique of [ingress tool transfer](https://attack.mitre.org/techniques/T1105/) and result in unwanted detections.\n\nHow to respond\n\nTo respond to this finding, do the following:\n\nStep 1: Review finding details\n\n1. Open an `Execution: Malicious Python executed` finding as directed in\n [Reviewing findings](/security-command-center/docs/how-to-investigate-threats#reviewing_findings). The details panel for the\n finding opens to the **Summary** tab.\n\n2. On the **Summary** tab, review the information in the following sections:\n\n - **What was detected** , especially the following fields:\n - **Program binary**: details about the interpreter that invoked the script.\n - **Script** : absolute path of the name of the script on disk; this attribute only appears for scripts written to disk, not for literal script execution---for example, `python3 -c`.\n - **Arguments**: the arguments provided when invoking the script.\n - **Affected resource** , especially the following fields:\n - **Resource full name** : the [full resource name](/apis/design/resource_names) of the cluster, including the project number, location, and cluster name.\n - **Related links** , especially the following fields:\n - **VirusTotal indicator**: link to the VirusTotal analysis page.\n3. In the detail view of the finding, click the **JSON** tab.\n\n4. In the JSON, note the following fields.\n\n - `finding`:\n - `processes`:\n - `script`:\n - `contents`: contents of the executed script, which might be truncated for performance reasons; this can aid in your investigation\n - `sha256`: the SHA-256 hash of `script.contents`\n - `resource`:\n - `project_display_name`: the name of the project that contains the asset.\n - `sourceProperties`:\n - `Pod_Namespace`: the name of the Pod's Kubernetes namespace.\n - `Pod_Name`: the name of the GKE Pod.\n - `Container_Name`: the name of the affected container.\n - `Container_Image_Uri`: the name of the container image being executed.\n - `VM_Instance_Name`: the name of the GKE node where the Pod executed.\n5. Identify other findings that occurred at a similar time for this container. For instance, if the script drops a binary, check for findings related to the binary.\n\nStep 2: Review cluster and node\n\n1. In the Google Cloud console, go to the **Kubernetes clusters** page.\n\n [Go to Kubernetes clusters](https://console.cloud.google.com/kubernetes/list)\n2. On the Google Cloud console toolbar, select the project listed in\n `resource.project_display_name`, if necessary.\n\n3. Select the cluster listed on the **Resource full name** row in the\n **Summary** tab of the finding details. Note any metadata about\n the cluster and its owner.\n\n4. Click the **Nodes** tab. Select the node listed in `VM_Instance_Name`.\n\n5. Click the **Details** tab and note the\n `container.googleapis.com/instance_id` annotation.\n\nStep 3: Review Pod\n\n1. In the Google Cloud console, go to the **Kubernetes Workloads** page.\n\n [Go to Kubernetes Workloads](https://console.cloud.google.com/kubernetes/workload)\n2. On the Google Cloud console toolbar, select the project listed in\n `resource.project_display_name`, if necessary.\n\n3. Filter on the cluster listed in `resource.name` and the Pod namespace\n listed in `Pod_Namespace`, if necessary.\n\n4. Select the Pod listed in `Pod_Name`. Note any metadata about the Pod and\n its owner.\n\nStep 4: Check logs\n\n1. In the Google Cloud console, go to **Logs Explorer**.\n\n \u003cbr /\u003e\n\n [Go to Logs Explorer](https://console.cloud.google.com/logs/query)\n\n \u003cbr /\u003e\n\n2. On the Google Cloud console toolbar, select the project listed in\n `resource.project_display_name`, if necessary.\n\n3. Set **Select time range** to the period of interest.\n\n4. On the page that loads, do the following:\n\n 1. Find Pod logs for `Pod_Name` by using the following filter:\n - `resource.type=\"k8s_container\"`\n - `resource.labels.project_id=\"`\u003cvar class=\"edit\" translate=\"no\"\u003eresource.project_display_name\u003c/var\u003e`\"`\n - `resource.labels.location=\"`\u003cvar class=\"edit\" translate=\"no\"\u003elocation\u003c/var\u003e`\"`\n - `resource.labels.cluster_name=\"`\u003cvar class=\"edit\" translate=\"no\"\u003ecluster_name\u003c/var\u003e`\"`\n - `resource.labels.namespace_name=\"`\u003cvar class=\"edit\" translate=\"no\"\u003ePod_Namespace\u003c/var\u003e`\"`\n - `resource.labels.pod_name=\"`\u003cvar class=\"edit\" translate=\"no\"\u003ePod_Name\u003c/var\u003e`\"`\n 2. Find cluster audit logs by using the following filter:\n - `logName=\"projects/`\u003cvar class=\"edit\" translate=\"no\"\u003eresource.project_display_name\u003c/var\u003e`/logs/cloudaudit.googleapis.com%2Factivity\"`\n - `resource.type=\"k8s_cluster\"`\n - `resource.labels.project_id=\"`\u003cvar class=\"edit\" translate=\"no\"\u003eresource.project_display_name\u003c/var\u003e`\"`\n - `resource.labels.location=\"`\u003cvar class=\"edit\" translate=\"no\"\u003elocation\u003c/var\u003e`\"`\n - `resource.labels.cluster_name=\"`\u003cvar class=\"edit\" translate=\"no\"\u003ecluster_name\u003c/var\u003e`\"`\n - \u003cvar class=\"edit\" translate=\"no\"\u003ePod_Name\u003c/var\u003e\n 3. Find GKE node console logs by using the following filter:\n - `resource.type=\"gce_instance\"`\n - `resource.labels.instance_id=\"`\u003cvar class=\"edit\" translate=\"no\"\u003einstance_id\u003c/var\u003e`\"`\n\nStep 5: Investigate running container\n\nIf the container is still running, it might be possible to investigate the\ncontainer environment directly.\n\n1. In the Google Cloud console, go to the **Kubernetes clusters** page.\n\n [Go to Kubernetes clusters](https://console.cloud.google.com/kubernetes/list)\n2. Click the name of the cluster shown in `resource.labels.cluster_name`.\n\n3. On the **Clusters** page, click **Connect** , and then click **Run in\n Cloud Shell**.\n\n Cloud Shell launches and adds commands for the cluster in the\n terminal.\n4. Press \u003ckbd\u003eEnter\u003c/kbd\u003e and, if the **Authorize Cloud Shell** dialog appears,\n click **Authorize**.\n\n5. Connect to the container environment by running the following command:\n\n kubectl exec --namespace=\u003cvar class=\"edit\" translate=\"no\"\u003e\u003cspan class=\"devsite-syntax-n\"\u003ePod_Namespace\u003c/span\u003e\u003c/var\u003e -ti \u003cvar class=\"edit\" translate=\"no\"\u003e\u003cspan class=\"devsite-syntax-n\"\u003ePod_Name\u003c/span\u003e\u003c/var\u003e -c \u003cvar class=\"edit\" translate=\"no\"\u003e\u003cspan class=\"devsite-syntax-n\"\u003eContainer_Name\u003c/span\u003e\u003c/var\u003e -- /bin/sh\n\n This command requires the container to have a shell installed at `/bin/sh`.\n\nStep 6: Research attack and response methods\n\n1. Review MITRE ATT\\&CK framework entries for this finding type: [Command and Scripting\n Interpreter](https://attack.mitre.org/techniques/T1059/), [Ingress Tool Transfer](https://attack.mitre.org/techniques/T1105/).\n2. Check the SHA-256 hash value for the binary flagged as malicious on [VirusTotal](https://www.virustotal.com) by clicking the link in **VirusTotal indicator**. VirusTotal is an Alphabet-owned service that provides context on potentially malicious files, URLs, domains, and IP addresses.\n3. To develop a response plan, combine your investigation results with the MITRE research and VirusTotal analysis.\n\nStep 7: Implement your response\n\n\nThe following response plan might be appropriate for this finding, but might also impact operations.\nCarefully evaluate the information you gather in your investigation to determine the best way to\nresolve findings.\n\n- If Python was making intended changes to the container, rebuild the container image such that no changes are needed. This way, the container can be [immutable](https://kubernetes.io/docs/concepts/containers/#container-images).\n- Otherwise, contact the owner of the project with the compromised container.\n- Stop or [delete](/container-registry/docs/managing#deleting_images) the compromised container and replace it with a [new container](/compute/docs/containers).\n\nWhat's next\n\n- Learn [how to work with threat\n findings in Security Command Center](/security-command-center/docs/how-to-investigate-threats).\n- Refer to the [Threat findings index](/security-command-center/docs/threat-findings-index).\n- Learn how to [review a\n finding](/security-command-center/docs/how-to-investigate-threats#reviewing_findings) through the Google Cloud console.\n- Learn about the [services that\n generate threat findings](/security-command-center/docs/concepts-security-sources#threats)."]]
