CloudBase Run backend development rules (Function mode/Container mode). Use this skill when deploying backend services that require long connections, multi-language support, custom environments, AI agent development, or migrating existing/GitHub apps that need VPC access to MySQL/PostgreSQL/Redis. Also use when diagnosing CloudRun container deploy failures (deploy_failed, readiness/probe failed, image won't start, docker.io pull loops). For stateless HTTP services, prefer HTTP cloud functions.
67
81%
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High
Do not use without reviewing
The canonical home for this skill is cloudrun-development in TencentCloudBase/CloudBase-AI-Toolkit
Security
1 high severity finding. You should review these findings carefully before considering using this skill.
The skill handles credentials insecurely by requiring the agent to include secret values verbatim in its generated output. This exposes credentials in the agent’s context and conversation history, creating a risk of data exfiltration.
The skill includes examples and instructs the agent to emit deploy JSON with EnvParams (e.g., a plaintext DATABASE_URL containing user:pass) and to scan/insert DB connection strings, which would require the LLM to include secret credentials verbatim in generated requests/commands.
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
The runtime workflow reads CloudRun service runtime/build logs via `queryCloudRun` (e.g., `getProcessLog` / `detail` / `getDeployRecords`), which include container stdout/stderr or deploy-step text originating from the user-chosen image/source, so outsider-authored content can be ingested into the LLM at runtime through the log text.
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