suspicious.dangerous_exec
- Location
- scripts/generate.js:9
- Finding
- Shell command execution detected (child_process).
AdvisoryAudited by Static analysis on May 10, 2026.
Detected: suspicious.dangerous_exec
Artifact-based informational review of SKILL.md, metadata, install specs, static scan signals, and capability signals. ClawScan does not execute the skill or run runtime probes.
The agent may use a preloaded account session and spend credits or act under an account identity that the user did not explicitly configure.
The script includes a default cached authentication session and later sends it as a Bearer token, so the skill can use account authority even when the user does not provide their own session.
let sessionToken = "b79fc...39978"; // 默认缓存的认证 session
Remove the embedded session token, require the user to provide their own credential through a declared secure mechanism, and clearly document credit-spending behavior.
Running the skill can unexpectedly fetch and execute package-install behavior from npm on the user's machine.
If the dependency is missing, the script automatically runs a shell-based npm install during execution, downloading unpinned code outside the declared install process.
const { execSync } = require('child_process');
execSync('npm install form-data --no-save', { stdio: 'ignore' });Move dependency installation into a reviewed install spec, pin package versions with a lockfile, and avoid runtime npm installs.
When invoked, the agent has broad local shell capability rather than only a narrowly limited video-generation action.
The skill grants broad Bash access. This is used for the stated local video-generation workflow, but it is broader than a single scoped command.
allowed-tools: Bash(*)
Prefer limiting allowed commands to the specific script and required log-reading commands, or ask for user confirmation before shell actions.
Images provided in chat may be saved locally and submitted to the local Jimeng service and its generation/moderation flow.
The skill is designed to extract user-sent images and send them into the video-generation pipeline. That is purpose-aligned, but it is sensitive media handling.
automatically intercept clothing/character images sent by the user in the chat interface and seamlessly pass them to the generation model
Use only with images the user intends to process, disclose the upload/moderation behavior, and clean up temporary image files after generation.