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Security audit

vwu.ai MiniMax Models

Security checks for vulnerabilities and agentic risk

Overview

This skill is a small vwu.ai chat wrapper, but it can send prompts and an API key to an undocumented, environment-controlled endpoint.

Review before installing. Only use this with a vwu.ai API key you are comfortable using for model calls, avoid placing secrets or regulated data in prompts, and make sure VWU_BASE_URL is unset or explicitly trusted. The script should ideally validate HTTPS vwu.ai endpoints and JSON-encode prompt/model values before broad use.

Vulnerability Patterns
  • Insecure Skill Coding PracticesFinds exploitable flaws such as hardcoded secrets or command injection
  • Skill Instruction HijackingAlters the agent's session goals or safety constraints when the skill loads
  • Agent Memory PoisoningWrites attacker-controlled rules into memory that affect later sessions
  • Remote Payload Retrieval and ExecutionFetches external code whose behavior can change after review
  • Embedded Malicious CodeShips malicious scripts inside the skill and executes them locally
Findings (2)

T09 · Insecure Skill Coding Practices

Error
Location
vwu-chat.sh:6
Finding

Attacker-Controlled API Endpoint Can Receive Credentials and Prompts

Content
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Remediation
View remediation
&2 exit 1 fi ``` If multiple endpoints are legitimate, compare parsed schemes and hostnames against a fixed allowlist rather than relying on string prefixes. ]]>

T09 · Insecure Skill Coding Practices

Warning
Location
vwu-chat.sh:29
Finding

Unescaped User Input Permits JSON Request Manipulation

Content
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Remediation
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Vulnerability Patterns
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Excessive AgencyUnrestricted Tool Access, Autonomous Decision Making, Scope Creep
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
  • Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code
Findings (6)

External Model or Provider Selection

High
Category
Excessive Agency
Confidence
90% confidence
Finding

Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.

Content

Scanner excerpt · SKILL.md (reported line 27)May include surrounding context.

bash
# 调用模型
vwu-chat --model MiniMax-Hailuo-02 "你的问题"

API 兼容性

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
92% confidence
Finding

The skill instructs users to set an API key and send prompts to vwu.ai, but it does not disclose that user inputs will be transmitted to an external third-party service. This creates a real privacy and data-governance risk because users may unknowingly submit sensitive prompts, credentials, or proprietary data to a remote provider.

Content

No source excerpt is available for this finding.

External Transmission

Medium
Category
Data Exfiltration
Confidence
77% confidence
Finding

The script transmits both user-supplied prompt content and the bearer token to an externally configurable endpoint via VWU_BASE_URL, with no validation that the host is trusted. If an attacker can influence the environment variable or persuade a user to point it at a malicious server, prompts and credentials could be exfiltrated to an attacker-controlled endpoint.

Content

Scanner excerpt · vwu-chat.sh (reported line 32)May include surrounding context.

sh
fi

# 调用 API
response=$(curl -s "$VWU_BASE_URL/v1/chat/completions" \
    -H "Content-Type: application/json" \
    -H "Authorization: Bearer $VWU_API_KEY" \
    -d "{

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
91% confidence
Finding

This code transmits the user-supplied prompt to a remote service and includes an Authorization bearer token, which is a safety-relevant network operation. While the script has error messages, it does not provide any prior disclosure, confirmation, or explanatory comment warning that prompt content will be sent to an external API.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Low
Category
Not specified by scanner
Confidence
83% confidence
Finding

SQP-3 applies to natural-language policy issues in all file types, including markdown. The content appears to force a specific language for instructions and warnings, which may violate a language-choice policy when no opt-in or justification is provided.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Low
Category
Not specified by scanner
Confidence
95% confidence
Finding

The script's comments, usage text, and error messages are written in Chinese throughout, which imposes a specific language on all users. There is no opt-in, fallback, or documentation that this skill is intentionally limited to Chinese-speaking users or a Chinese-only environment.

Content

No source excerpt is available for this finding.