SkillAgentSearch skills...

google-cloud-scc-remediation

Remediates Google Cloud Security Command Center findings, including IAM permission fixes, cloud resource misconfigurations, vulnerabilities, and Toxic Combinations

Install / Use

npx skills add google/skills --skill google-cloud-scc-remediation

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

89/100

Category

Security

Supported Platforms

Universal

Our assessment of google-cloud-scc-remediation

google-cloud-scc-remediation scores 89/100 on our quality scale, 548th of 1,120 Security skills we index (top 49%).

Its SKILL.md is 12 KB long, split into 6 sections and no code examples: a thorough specification that gives an agent plenty to work with.

With 20,340 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
30/30
Structure
11/20
Description
15/15
Adoption
18/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 26 days ago, so google-cloud-scc-remediation is actively maintained.
  • It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

google-cloud-scc-remediation compared with similar skills

All 4 of these similar skills score higher than google-cloud-scc-remediation; compare them before choosing.

SkillScoreStarsUpdatedFormat
google-cloud-scc-remediation (this skill)by google8920.3k26d agoSKILL.md
algorithmic-artby anthropics100177.9k27d agoSKILL.md
pptxby anthropics100177.9k27d agoSKILL.md
designby nextlevelbuilder100137.2k5d agoSKILL.md
ui-ux-pro-maxby nextlevelbuilder100137.2k5d agoSKILL.md

Frequently asked questions

How do I install google-cloud-scc-remediation?
Run npx skills add google/skills --skill google-cloud-scc-remediation. The install tabs above show the steps for each supported agent.
Which AI agents does google-cloud-scc-remediation work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is google-cloud-scc-remediation safe to use?
It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is google-cloud-scc-remediation still maintained?
The repository was last updated 26 days ago, so google-cloud-scc-remediation is actively maintained.

name: google-cloud-scc-remediation metadata: category: Security version: "1.0.0" description: >- Remediates Google Cloud Security Command Center findings, including IAM permission fixes, cloud resource misconfigurations, vulnerabilities, and Toxic Combinations. Use when asked to fix, remediate, or mitigate a Security Command Center finding or address attack paths. Don't use for general IAM policy querying without a Security Command Center finding. For runtime threat detections, this skill provides containment and investigation guidance rather than automated configuration fixes.

Google Cloud Security Command Center Remediation

Overview

A unified remediation skill for Google Cloud Security Command Center findings. It handles both single-domain findings and multi-domain Toxic Combinations.

1. Safety & Consent Gate

Security Command Center remediations modify infrastructure, access policies, or workload deployments.

  • Mandatory Consent Gate: NEVER execute mutating gcloud, terraform, or API commands without first presenting a structured remediation plan and the exact command/config diff to the user. STOP after presenting the plan and ALWAYS ask: "Do you approve executing this remediation plan?" before execution. Automatic mutation of security policies or resource configurations can cause unintended outages, lockouts, or compliance violations.

  • Confirm the Target Project: Before executing, confirm that the active gcloud account and project match the project of the finding's resource. Every mutating command MUST specify the target explicitly, with --project or a full resource path, rather than relying on the default gcloud project.

  • Verification & Rollback Required: Every proposed remediation plan MUST explicitly include, for each mutating step:

    • the mutating remediation command(s),
    • the verification check command(s) (gcloud ... describe or list), and
    • the rollback command(s) that undo the change, or an explicit statement that the step cannot be undone (for example, service account key deletion).

    Use the commands from the loaded playbook where they exist. If the playbook lacks a verification or rollback command for a step, derive the command and label it as not sourced from a playbook.

  • Dependency & Impact Checks: Every remediation plan MUST state what could break as a result of each change and ask the user to confirm nothing depends on it. For example:

    • IAM role changes or revocations: you MUST explicitly advise the user to verify cross-project dependencies and CI/CD pipeline workflows that rely on the existing permissions before revoking a project-level role binding.
    • Firewall rule changes: other traffic the same rule allows (such as web traffic on ports 80 or 443).
    • External IP removal: inbound access and outbound internet access for the VM.
    • Public Access Prevention on a bucket: sites or users that legitimately read it publicly.
  • CRITICAL WORKFLOW RULE: Do NOT execute any mutating commands in the same turn that you present the remediation plan. You MUST end your turn immediately after asking for approval and wait for the user's next message.

    • If there is no interactive user (for example, a scheduled or pipeline run), stop at the plan and never execute.
    • If the user approves only part of the plan, or the plan changes after approval, present the updated plan and ask for approval again before executing.
  • Narrowly Scoped Changes: Always propose the narrowest possible fix that resolves the finding. When more than one fix would work, prefer reversible changes over irreversible ones (for example, disable a key before deleting it), resource-level changes over project, folder, or organization-level changes, and changes that affect only the finding's resource over changes that affect other resources. Do not bundle fixes for unrelated issues noticed along the way; mention them to the user separately.

2. Intent Router & Progressive Disclosure

Do not load all reference playbooks into memory at once. Analyze the Security Command Center finding's category, findingClass, or attack path, then read ONLY the relevant reference document(s).

Match on the finding's category first, and fall back to findingClass only when no category matches. Routing on findingClass alone misroutes IAM findings: Security Health Analytics IAM findings are MISCONFIGURATION class, and IAM recommender findings are Vulnerability class, so neither would ever reach the IAM playbook.

| Match On | Values | Target Reference Playbook | | :---------------------- | :---------------------------------------- | :--------------------------------------------------------------------------- | | category | PRIMITIVE_ROLES_USED, | references/remediation_iam.md | : (Security Health : OVER_PRIVILEGED_SERVICE_ACCOUNT_USER, : : : Analytics) : ADMIN_SERVICE_ACCOUNT, : : : : SERVICE_ACCOUNT_ROLE_SEPARATION, : : : : KMS_ROLE_SEPARATION, : : : : USER_MANAGED_SERVICE_ACCOUNT_KEY, : : : : SERVICE_ACCOUNT_KEY_NOT_ROTATED : : | category | IAM_ROLE_HAS_EXCESSIVE_PERMISSIONS, | references/remediation_iam.md | : (IAM recommender) : UNUSED_IAM_ROLE, : : : : SERVICE_AGENT_GRANTED_BASIC_ROLE, : : : : SERVICE_AGENT_ROLE_REPLACED_WITH_BASIC_ROLE : : | category | PUBLIC_BUCKET_ACL, PUBLIC_IP_ADDRESS, | references/remediation_misconfig.md | : (Security Health : OPEN_FIREWALL, OPEN_SSH_PORT, : : : Analytics) : OPEN_RDP_PORT, KMS_KEY_NOT_ROTATED : : | category | OS_VULNERABILITY, SOFTWARE_VULNERABILITY, | references/remediation_vuln.md | : : GKE_RUNTIME_OS_VULNERABILITY (CVEs, OS : : : : patch, container base image upgrade, : : : : vulnerable package, GKE node pool upgrade). : : : : Note: Web Security Scanner (WSS) findings : : : : fall through to no match below. : : | findingClass | TOXIC_COMBINATION — attack path | Sequential Load: Identify each exposed facet in the attack path and load | : : exposure, multi-domain attack vector : the matching reference playbooks sequentially. : | no match | Any other category or finding class | See Findings Without Dedicated Playbooks below. Do not force a finding | : : : into a playbook that does not cover it. :

Findings Without Dedicated Playbooks & Runtime Threat Detections

When presented with Security Command Center findings that do not have automated configuration remediation playbooks—such as runtime threat detections (e.g., Cloud Run Threat Detection, Agent Platform Threat Detection, Event Threat Detection, Container Threat Detection):

  1. Do NOT execute automated mutation commands: Runtime threat detections represent active alerts or behavioral anomalies rather than static resource misconfigurations.
  2. Provide Documentation & Containment Guidance:
    • Refer the user to the relevant Security Command Center documentation (e.g., Cloud Run Threat Detection, Agent Platform Threat Detection).
    • Recommend manual investigation steps: analyzing audit logs in Cloud Logging, identifying compromised service accounts or API keys, and isolating affected workloads.
    • Advise the user on containment options (e.g., revoking active credentials, blocking malicious IPs at Cloud Armor/firewall).

3. Standard Remediation Workflow

  1. Inspect Finding Details & Intentionality:
    • If the finding's details are not already in the conversation, retrieve them using the google-cloud-scc-query skill. Verify the finding name, affected resource (resourceName), category, and attack exposure score.
    • Before planning a fix, ask the user whether the flagged configuration is intentional (for example, a bucket serving a public website, or a VM that must accept public traffic). If it is, do not propose a remediation. Suggest muting the finding with a documented justification instead; muting changes the finding's state, so it also requires the user's approval.
  2. Route & Load Reference: Read the matching reference playbook(s) from the routing table above.
  3. Formulate Least-Privilege Remediation: Before drafting, check whether the resource is managed by infrastructure as code (ask the user, and check for signals such as the goog-terraform-provisioned label). If it is, draft the change to the Terraform configuration rather than a gcloud command. Otherwise, draft the exact CLI (gcloud) or IAM binding change needed to close the exposure without disrupting business workloads.
  4. Present Plan & Seek Consent: Show the user the plan required by the Safety & Consent Gate: for each step, the remediation command, the verification command, the rollback command, and what could break. STOP execution here and ALWAYS ask the explicit question: "Do you approve executing this remediation plan?"
  5. Execute on Approval: ONLY after receiving explicit user confirmation, execute the remediation commands and run the verification commands to confirm the resource is fixed. If a command fails, stop and report the error; do not try a different command without presenting it and getting approval again. Tell the user that the f

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars20.3k
CategorySecurity
Updated26d ago
Forks1.7k

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions