AI电商专家｜服装时尚电商图片视频

• Outcome: Pass
• Latest audit: Aug 23, 2026 · 9:37 AM UTC
• Version: 1.0.0

Overview

This skill is a coherent IMIVA ecommerce content workflow that discloses its external MCP use, token requirement, local media handling, and paid-task confirmation steps.

Install this only if you intend to use IMIVA's ecommerce generation service and are comfortable providing an IMIVA MCP token and product media to that service. Confirm credits and task parameters before creating paid image or video jobs, and consider pinning the npm package version instead of using @latest for production use.

SkillSpector

Vulnerability Patterns

• Data Exfiltration: External Transmission, Env Variable Harvesting, File System Enumeration
• Behavioral AST: exec() Call, eval() Call, Dynamic Import
• MCP Least Privilege: Underdeclared Capability, Wildcard Permission, Missing Permission Declaration
• Prompt Injection: Instruction Override, Hidden Instructions, Exfiltration Commands
• Privilege Escalation: Excessive Permissions, Sudo/Root Execution, Credential Access

Findings (8)

subprocess module call

Medium

• Category: Dangerous Code Execution

Content

env = os.environ.copy()
    env["MCP_TOKEN"] = token
    env["API_URL"] = os.environ.get("IMIVA_API_URL", os.environ.get("API_URL", DEFAULT_API_URL))
    proc = subprocess.Popen(
        [npx, "-y", PACKAGE],
        stdin=subprocess.PIPE,
        stdout=subprocess.PIPE,

• Confidence: 70% confidence
• Finding: subprocess module calls execute external commands. Without careful input validation, this enables command injection.

Lp3

Medium

• Category: MCP Least Privilege
• Confidence: 70% confidence
• Finding: Without declared permissions the skill's intent is opaque and cannot be validated.

Natural-Language Policy Violations

Medium

• Confidence: 93% confidence
• Finding: The manifest metadata explicitly sets the skill language to zh-CN, and the description later states it is especially suitable for Chinese users. This creates a natural-language locale constraint without indicating that users can choose another language or opt in to the restriction.

Natural-Language Policy Violations

Medium

• Confidence: 91% confidence
• Finding: The phrase '特别适合...的中文用户' indicates the skill is oriented toward Chinese-language users, but the document does not provide an explicit language choice or user opt-in. Under the policy, forcing or preferring a specific language/locale without choice should be flagged unless clearly justified as region-specific.

Natural-Language Policy Violations

Medium

• Confidence: 95% confidence
• Finding: The display name, short description, and default prompt are entirely in Chinese, which imposes a specific language on users without offering a choice or documenting that the skill is intended only for a Chinese-speaking or region-specific audience. Under the policy, language constraints must be opt-in or clearly justified.

Natural-Language Policy Violations

Low

• Confidence: 97% confidence
• Finding: This code presents user-facing error messages entirely in Chinese, and later help/description strings are also Chinese. The file does not offer any language or locale selection, which is a natural-language policy concern under the rule for forced language without user opt-in.

Env Variable Harvesting

High

• Category: Data Exfiltration

Content

npx = shutil.which("npx")
    if not npx:
        raise SystemExit("未找到 npx。请先安装 Node.js 18 或更高版本。")
    token = os.environ.get("MCP_TOKEN", "").strip()
    if not token:
        raise SystemExit("缺少 MCP_TOKEN。请在 IMIVA 的 MCP Token 页面创建后通过环境变量提供。")
    return npx, token

• Confidence: 70% confidence
• Finding: Code accesses environment variables that may contain secrets (API keys, tokens). This is a common pattern for credential theft.

Env Variable Harvesting

High

• Category: Data Exfiltration

Content

def invoke(method: str, params: dict | None = None) -> dict:
    npx, token = require_runtime()
    env = os.environ.copy()
    env["MCP_TOKEN"] = token
    env["API_URL"] = os.environ.get("IMIVA_API_URL", os.environ.get("API_URL", DEFAULT_API_URL))
    proc = subprocess.Popen(

• Confidence: 60% confidence
• Finding: Code accesses environment variables that may contain secrets (API keys, tokens). This is a common pattern for credential theft.

Static analysis

No suspicious patterns detected.