T09 · Insecure Skill Coding Practices
- Location
scripts/run-seedance-workflow.cjs:286- Finding
Weak Endpoint Validation Can Disclose API Credentials and Local Media
- Content
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- Remediation
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Security audit
Security checks for vulnerabilities and agentic risk
The skill is a coherent video-generation workflow, but it handles API keys and private media with under-scoped endpoint and download controls.
Review before installing. Use only trusted, official provider endpoints or explicitly trusted gateways, keep API keys out of chat and shared logs, expect configured prompts/images/audio/video to leave your machine, and avoid direct-run modes unless you are ready to spend provider quota. Rotate any key that may have been used with an untrusted config endpoint.
scripts/run-seedance-workflow.cjs:286Weak Endpoint Validation Can Disclose API Credentials and Local Media
scripts/download-official-video.cjs:45Unrestricted Video URL Download Enables Server-Side Request Forgery
This second mismatch finding is more specific: the skill claims support for Seedance, Vidu, and MiniMax plus ASR/TTS/merge delivery, but the analyzed implementation reportedly only supports a subset and omits several claimed features. In a workflow skill, inaccurate capability claims are dangerous because downstream users may expose credentials, trigger network actions, or rely on absent post-processing/validation stages under false assumptions.
This second mismatch finding is more specific: the skill claims support for Seedance, Vidu, and MiniMax plus ASR/TTS/merge delivery, but the analyzed implementation reportedly only supports a subset and omits several claimed features. In a workflow skill, inaccurate capability claims are dangerous because downstream users may expose credentials, trigger network actions, or rely on absent post-processing/validation stages under false assumptions.
Referenced artifact was not completely inspected
When scheduling with `scripts/run-seedance-workflow.cjs`, continue actions must map to stage-specific approvals:
Referenced artifact was not completely inspected
- `scripts/submit-official-video.ts`
Referenced artifact was not completely inspected
- `scripts/poll-official-video.ts`
Referenced artifact was not completely inspected
- `scripts/download-official-video.ts`
Referenced artifact was not completely inspected
- `scripts/generate-tts.ts` (TTS 选择后子脚本级配置检查,缺失返回结构化 `configuration-guidance`)
Referenced artifact was not completely inspected
- `scripts/self-test-workflow-driver.cjs` (用于校验 workflow driver 的阶段/审批映射)
Referenced artifact was not completely inspected
- `scripts/run-video-submit-chain.cjs` (首图确认后统一调度 提交/轮询/下载)
Referenced artifact was not completely inspected
- `scripts/build-dispatch-plan.cjs` (只产出调度指令与检查点,不执行)
Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.
Rules:
- spoken text must be intentional, not accidental
- if the video prompt implies mouth movement, ensure the audio plan is explicitly decided
- do not leave a “mouth moving but no speech” mismatch without warning
## Ambience acceptance rules
Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.
## Purpose
Every clip should have a clear state label so the pipeline never confuses candidate outputs with deliverables.
## Recommended states
The skill describes workflow execution that relies on environment variables and networked vendor/API access, but it does not declare any explicit tool scope or permissions boundary. That makes invocation and review less predictable, increases the chance of over-broad runtime capability use, and weakens least-privilege controls around API keys and outbound requests.
The auto-trigger rules are broad enough to match many ordinary creative-writing or ideation requests, causing the skill to activate when the user may not intend a networked or stateful production workflow. Unintended invocation can lead to unnecessary external calls, premature workflow state changes, or collection/use of configuration secrets in contexts where a simple text response would have been safer.
This example config uses Chinese field names throughout, such as "厂商", "接口地址", and "模型名", with no indication that other languages are supported. That can violate a language/locale policy when a skill implicitly requires one language without explicit user opt-in or documented justification.
Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
"upstream": {
"seedance": {
"厂商": "MiniMax",
"接口地址": "https://api.minimaxi.com/v1",
"模型名": "your-upstream-model",
"APIKey": "your-upstream-key"
}
Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
"upstream": {
"seedance": {
"厂商": "MiniMax",
"接口地址": "https://api.minimaxi.com/v1",
"模型名": "your-upstream-model",
"APIKey": "your-upstream-key"
}
Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
"upstream": {
"seedance": {
"厂商": "MiniMax",
"接口地址": "https://api.minimaxi.com/v1",
"模型名": "your-upstream-model",
"APIKey": "your-upstream-key"
}
Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
"upstream": {
"seedance": {
"厂商": "MiniMax",
"接口地址": "https://api.minimaxi.com/v1",
"模型名": "your-upstream-model",
"APIKey": "your-upstream-key"
}
Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
"upstream": {
"seedance": {
"厂商": "MiniMax",
"接口地址": "https://api.minimaxi.com/v1",
"模型名": "your-upstream-model",
"APIKey": "your-upstream-key"
}
Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
"upstream": {
"seedance": {
"厂商": "MiniMax",
"接口地址": "https://api.minimaxi.com/v1",
"模型名": "your-upstream-model",
"APIKey": "your-upstream-key"
}
The document instructs users to use specific Chinese labels for user-facing setup guidance, which effectively forces a locale/language choice. This is a natural-language policy concern because no opt-in, alternative language option, or region-specific justification is provided.
The guidance explicitly tells the operator to provide API keys, tokens, app IDs, and endpoint details, but it does not warn against placing secrets in prompts, logs, screenshots, shared config, or other insecure channels. In a first-run setup guide, this omission can lead users to expose credentials during onboarding, especially because the file frames credential collection as normal configuration rather than sensitive handling.
This documentation includes commands that can trigger real third-party video generation, polling, downloads, and image uploads, which may incur cost and transmit user media or prompts off-machine, but it does not clearly warn the operator before those steps. In this skill context, the risk is elevated because the file is an execution-policy note for an automation pipeline, so readers may treat the commands as safe defaults and run them without realizing the financial and privacy consequences.
The documented direct-start behavior states that a start action may immediately call downstream production when config is ready, yet it does not present a prominent warning that this can launch external jobs, upload assets, and consume paid quota. Because this is framed as first-run onboarding behavior, it is especially dangerous: a new operator on a fresh machine may expect diagnostics or dry-run behavior and instead trigger real external actions.
Detected: suspicious.dangerous_exec, suspicious.env_credential_access