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Security audit

Alibaba Cloud Security Id Verification Cloudauth

Security checks for vulnerabilities and agentic risk

Overview

This skill is a disclosed Alibaba Cloud Cloudauth helper that uses expected cloud credentials and metadata discovery for its stated purpose, with no hidden persistence or deceptive behavior found.

Install this only for Alibaba Cloud Cloudauth work. Use least-privilege Alibaba Cloud credentials, review any mutating API call before execution, and avoid saving secrets, full identity records, or unredacted customer data in the output artifacts.

A.I.G

Vulnerability Patterns
  • 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
  • Unauthorized Access and Privilege EscalationObtains permissions beyond the task's legitimate needs

SkillSpector

Vulnerability Patterns
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Trigger AbuseOverly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
  • Taint TrackingDirect Taint Flow, Variable-Mediated Taint Flow, Credential Exfiltration Chain
  • MCP Least PrivilegeUnderdeclared Capability, Wildcard Permission, Missing Permission Declaration
  • MCP Tool PoisoningHidden Instructions, Unicode Deception, Parameter Description Injection
Findings (9)

Tainted flow: 'timeout' from os.getenv (line 34, credential/environment) → urllib.request.urlopen (network output)

Critical
Category
Data Flow
Content
def fetch_json(url: str, timeout: int) -> dict:
    req = urllib.request.Request(url, headers={"User-Agent": "codex-skill"})
    with urllib.request.urlopen(req, timeout=timeout) as resp:
        return json.loads(resp.read().decode("utf-8"))
Confidence
90% confidence
Finding
Credentials or environment variables flow to a network sink. This is a high-confidence indicator of credential exfiltration.

Tp4

High
Category
MCP Tool Poisoning
Confidence
96% confidence
Finding
The skill is presented as managing Cloudauth resources and troubleshooting live workflows, but the described executable path centers on metadata discovery and local artifact generation rather than actual resource operations. This mismatch is dangerous because users and orchestration systems may grant higher trust or broader cloud permissions based on the declared purpose, while the real behavior performs a different set of actions than expected.

Lp3

Medium
Category
MCP Least Privilege
Confidence
93% confidence
Finding
The skill instructs use of environment variables, local file writes, and network-based API discovery, but it does not declare any explicit tool scope or permissions boundaries. This is dangerous because an agent may invoke credentialed cloud access and write artifacts without clear least-privilege constraints or operator visibility into what capabilities the skill requires.

Vague Triggers

Medium
Confidence
93% confidence
Finding
The activation description is broad enough to trigger for many generic identity-verification or troubleshooting requests, which can cause the skill to run in contexts where cloud credentials, network calls, or file writes are unnecessary. Overbroad invocation increases the chance of unintended exposure of sensitive environment data or unnecessary API interaction.

Missing User Warnings

Medium
Confidence
90% confidence
Finding
The skill directs the use of Alibaba Cloud credentials and API calls but does not provide an explicit warning about sensitive credential handling, logging, or artifact storage. In a cloud-management context, this raises the risk that secrets, request parameters, or account metadata may be exposed in outputs, logs, or evidence files during routine use.

External Transmission

Medium
Category
Data Exfiltration
Content
output_dir.mkdir(parents=True, exist_ok=True)

    url = (
        f"https://api.aliyun.com/meta/v1/products/{args.product_code}"
        f"/versions/{args.version}/api-docs.json"
    )
    payload = fetch_json(url, timeout)
Confidence
60% confidence
Finding
Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.

External Transmission

Medium
Category
Data Exfiltration
Content
output_dir.mkdir(parents=True, exist_ok=True)

    url = (
        f"https://api.aliyun.com/meta/v1/products/{args.product_code}"
        f"/versions/{args.version}/api-docs.json"
    )
    payload = fetch_json(url, timeout)
Confidence
60% confidence
Finding
Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.

External Transmission

Medium
Category
Data Exfiltration
Content
output_dir.mkdir(parents=True, exist_ok=True)

    url = (
        f"https://api.aliyun.com/meta/v1/products/{args.product_code}"
        f"/versions/{args.version}/api-docs.json"
    )
    payload = fetch_json(url, timeout)
Confidence
60% confidence
Finding
Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.

External Transmission

Medium
Category
Data Exfiltration
Content
output_dir.mkdir(parents=True, exist_ok=True)

    url = (
        f"https://api.aliyun.com/meta/v1/products/{args.product_code}"
        f"/versions/{args.version}/api-docs.json"
    )
    payload = fetch_json(url, timeout)
Confidence
60% confidence
Finding
Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.

Static analysis

No suspicious patterns detected.