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Security audit

qa-ai-prompt-strategy

Security checks for vulnerabilities and agentic risk

Overview

This is a read-only prompt-template skill for QA test-case generation, with some broad activation wording and an optional unpinned install suggestion users should treat carefully.

Install this skill if you want Chinese QA prompt templates for test-case generation. Before following the optional npx command for the larger skill set, review the source and prefer a pinned revision. Be aware that broad trigger phrases may make the skill appear for general prompt-optimization requests, so invoke it only when you are working on QA test prompts.

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
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • Trigger AbuseOverly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
  • 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
95% confidence
Finding

The description defines very broad trigger conditions such as '怎么问AI', '提示词', and 'AI回答不好', which can cause the skill to activate for many ordinary conversations unrelated to the intended workflow. Over-broad activation increases the chance of inappropriate prompt injection into unrelated tasks, bypassing user intent and potentially causing workflow hijacking or unsafe context propagation.

Content

No source excerpt is available for this finding.

Vague Triggers

Medium
Category
Not specified by scanner
Confidence
93% confidence
Finding

The when-to-use field uses ambiguous activation criteria like '需要不同测试视角' and 'AI输出太浅需要更深时' without defining boundaries, prerequisites, or non-applicable cases. In an agent environment, such ambiguity can cause accidental invocation and overreach, leading the skill to steer outputs or workflow steps even when the user did not request this behavior.

Content

No source excerpt is available for this finding.

Rp1

Medium
Category
MCP Rug Pull
Confidence
96% confidence
Finding

The skill includes an installation command using npx skills add Kokxi/qa-test-skills without pinning an exact package version or immutable source reference. This creates a supply-chain risk: a future compromised or maliciously updated package could be fetched and executed implicitly by users following the instruction.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
84% confidence
Finding

The skill contains a dedicated section prescribing Chinese-model-specific adaptation strategies and Chinese-language prompting behavior without any opt-in or language preference check. This can override user expectations, leak assumptions about model/provider choice, and cause inappropriate transformation of prompts or outputs in multilingual or policy-sensitive environments.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Low
Category
Not specified by scanner
Confidence
89% confidence
Finding

The document title and instructional text are entirely in Chinese and present the prompt templates as the default interaction format, with no indication that users may choose another language. Under the policy, a skill that imposes a specific language without user opt-in is a natural-language policy concern.

Content

No source excerpt is available for this finding.