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Security audit

qa-scenario-tree

Security checks for vulnerabilities and agentic risk

Overview

This is a read-only QA scenario-tree helper with disclosed sensitive-data cautions; the main caution is an optional unpinned install command for a broader skill set.

Use this skill for Chinese-language QA scenario-tree work, and avoid pasting real customer, identity, payment, or production data. Before running the optional `npx` install command for the broader skill set, review the source and prefer a pinned version or trusted release.

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
Vulnerability Patterns
  • Trigger AbuseOverly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
  • Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code
Findings (5)

Vague Triggers

Medium
Category
Not specified by scanner
Confidence
91% confidence
Finding

The activation guidance includes broad phrases like '构建场景', '测试场景', and '场景设计', which are common in normal QA discussion and can cause unintended invocation. If auto-invoked, the skill could process sensitive requirement or test data in contexts where the user did not intend to use this workflow, increasing the chance of over-collection, confusion, or unsafe downstream actions.

Content

No source excerpt is available for this finding.

Vague Triggers

Medium
Category
Not specified by scanner
Confidence
89% confidence
Finding

The when-to-use field defines activation conditions using broad natural-language examples rather than strict criteria, making accidental triggering plausible. In agent ecosystems, ambiguous activation can cause the wrong skill to run, leading to unintended access to workspace data or generation of outputs that the user did not request.

Content

No source excerpt is available for this finding.

Rp1

Medium
Category
MCP Rug Pull
Confidence
91% confidence
Finding

The skill instructs users to run npx skills add Kokxi/qa-test-skills without pinning a specific package version or immutable source reference. This creates a supply-chain risk: a future compromised or maliciously updated package could be fetched and executed at install time, and npx commonly executes remote package code during resolution/install.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
92% confidence
Finding

This markdown template forces a specific language/locale for all users through its headings, instructions, and examples. Under the policy, language-specific constraints should either offer user opt-in/choice or be clearly justified as region-specific; neither is present here.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
93% confidence
Finding

The entire skill reference is written in Chinese and does not indicate that users may choose another language or that the skill is intentionally restricted to a Chinese-speaking context. Under the policy, forcing a specific language without user opt-in is a natural-language locale violation.

Content

No source excerpt is available for this finding.