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Security audit

ecom-price-monitor跨境电商价格监控神器 - 竞品一动，秒级预警

Security checks for vulnerabilities and agentic risk

Overview

This is a coherent ecommerce price-monitoring skill, with ordinary setup and no evidence of hidden exfiltration or destructive behavior, but it needs careful credential and scraping hygiene.

Before installing, review the product URLs and monitoring frequency, respect marketplace terms and rate limits, keep API keys, SMTP passwords, webhooks, and 1688 cookies out of prompts/logs/source control, and leave email or webhook notifications disabled unless you trust the destination.

SkillSpector

Vulnerability Patterns
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
  • Excessive AgencyUnrestricted Tool Access, Autonomous Decision Making, Scope Creep
Findings (8)

Missing User Warnings

Medium
Confidence
90% confidence
Finding
The skill explicitly advertises scheduled automated scraping, competitor monitoring, and email/Feishu notifications, but it does not warn users about legal, compliance, rate-limiting, account, or privacy risks associated with scraping third-party sites and sending outbound alerts. This omission can lead users to deploy the skill in ways that violate platform terms, trigger blocking, or expose monitored data through notification channels.

Missing User Warnings

Medium
Confidence
91% confidence
Finding
The README instructs users to obtain and use a logged-in 1688 Cookie but does not warn that session cookies are sensitive credentials equivalent to account access. This can lead users to paste, store, or share active session tokens insecurely, increasing the risk of account takeover, privacy exposure, or accidental credential leakage through config files, logs, or support requests.

Unpinned Dependencies

Low
Category
Supply Chain
Content
requests>=2.31.0
beautifulsoup4>=4.12.0
schedule>=1.2.0
pyyaml>=6.0
Confidence
96% confidence
Finding
The dependency is specified with a lower bound only, which allows future unreviewed versions to be installed and can also produce non-reproducible builds. This is a supply-chain hygiene weakness rather than an immediately exploitable flaw in this file by itself, but it increases exposure to breaking or vulnerable upstream releases.

Unpinned Dependencies

Low
Category
Supply Chain
Content
requests>=2.31.0
beautifulsoup4>=4.12.0
schedule>=1.2.0
pyyaml>=6.0
pandas>=2.0.0
Confidence
96% confidence
Finding
Using a non-pinned version range for beautifulsoup4 permits installation of arbitrary newer releases without explicit review, reducing build reproducibility. While not a direct exploit on its own, it increases supply-chain risk and makes it harder to ensure only vetted versions are deployed.

Unpinned Dependencies

Low
Category
Supply Chain
Content
requests>=2.31.0
beautifulsoup4>=4.12.0
schedule>=1.2.0
pyyaml>=6.0
pandas>=2.0.0
python-dotenv>=1.0.0
Confidence
95% confidence
Finding
The schedule package is not pinned to an exact version, so environments may resolve different releases over time. That weakens reproducibility and can unintentionally introduce vulnerable or incompatible upstream changes.

Unpinned Dependencies

Low
Category
Supply Chain
Content
requests>=2.31.0
beautifulsoup4>=4.12.0
schedule>=1.2.0
pyyaml>=6.0
pandas>=2.0.0
python-dotenv>=1.0.0
Confidence
97% confidence
Finding
PyYAML is declared with only a minimum version, allowing uncontrolled upgrades and inconsistent dependency resolution. Given PyYAML's history of deserialization-related issues, leaving the version unpinned increases operational and security uncertainty.

Unpinned Dependencies

Low
Category
Supply Chain
Content
beautifulsoup4>=4.12.0
schedule>=1.2.0
pyyaml>=6.0
pandas>=2.0.0
python-dotenv>=1.0.0
Confidence
92% confidence
Finding
An unpinned pandas dependency allows different versions to be installed depending on environment and timing, undermining reproducibility. This is primarily a supply-chain risk and maintenance issue, not a standalone direct exploit in the requirements file.

Unpinned Dependencies

Low
Category
Supply Chain
Content
schedule>=1.2.0
pyyaml>=6.0
pandas>=2.0.0
python-dotenv>=1.0.0
Confidence
93% confidence
Finding
python-dotenv is specified with a lower-bound constraint only, so future versions may be installed without review and builds may differ across environments. This broadens the attack surface from dependency drift and makes secure version governance harder.

Static analysis

No suspicious patterns detected.