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Security audit

python-ai-course

Security checks for vulnerabilities and agentic risk

Overview

This is a Chinese-language AI course tutor skill with broad teaching triggers, but it contains only markdown guidance and no hidden execution, persistence, or data exfiltration behavior.

Install this if you want a structured Chinese AI-learning tutor. Expect it to ask assessment questions and push a fixed course workflow when AI-learning topics come up; users who only want brief Q&A may find the trigger scope too aggressive.

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
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Trigger AbuseOverly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
  • Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code
Findings (9)

Vague Triggers

Medium
Category
Not specified by scanner
Confidence
97% confidence
Finding

The skill metadata states it should auto-activate whenever a user expresses broad interest in learning AI, which is an overly permissive trigger. In practice this can hijack ordinary conversations, causing the agent to switch into a rigid workflow unexpectedly and potentially collect unnecessary user profiling information before the user explicitly asked for the skill.

Content

No source excerpt is available for this finding.

Vague Triggers

Medium
Category
Not specified by scanner
Confidence
98% confidence
Finding

The trigger section explicitly says the full standardized teaching flow should start automatically without extra confirmation for a wide range of common phrases. Because these phrases are ambiguous and common in normal Q&A, the skill can activate without informed user intent, leading to unwanted behavior, excessive questioning, and reduced user control over agent actions.

Content

No source excerpt is available for this finding.

Vague Triggers

Medium
Category
Not specified by scanner
Confidence
95% confidence
Finding

The listed technical phrases include many generic topics such as 'machine learning,' 'Transformer,' 'RAG,' and 'Prompt Engineering,' which are common discussion subjects and not reliable indicators that the user wants this skill engaged. This makes accidental activation more likely and is more dangerous here because the skill imposes a mandatory, non-skippable flow that can override the conversational context and push the user into a predefined process.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
96% confidence
Finding

The entire skill content is written exclusively in Chinese and presents all guidance, labels, and teaching instructions in that language. There is no indication that the user can opt into another language or that the skill is intentionally limited to a Chinese-speaking or region-specific audience, which creates a natural-language locale policy concern.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
90% confidence
Finding

The title and the entire instructional content are written exclusively in Chinese, with no indication that other languages are supported or that the language choice is optional. Under the policy, forcing a specific language without user opt-in is a natural-language locale violation unless clearly justified as region-specific.

Content

No source excerpt is available for this finding.

Ae4

Medium
Category
analysis-evasion
Confidence
80% confidence
Finding

Suspicious Unicode normalization or mixed-script content

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
91% confidence
Finding

The file is written entirely in Chinese and presents itself as a general teaching/reference document, but it does not indicate that Chinese is optional, user-selected, or required for a region-specific purpose. Under the policy rule for natural-language violations, this can be interpreted as forcing a specific language without user opt-in.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
93% confidence
Finding

The file title and directive are written as a strict standard template in Chinese, and L003 says every chapter must strictly follow this structure. That creates a natural-language locale constraint without user opt-in or an explicit justification that this skill is intended only for a Chinese-language context.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Low
Category
Not specified by scanner
Confidence
92% confidence
Finding

This markdown file is entirely presented in Chinese and the title explicitly frames it as the authoritative course outline, without any indication that other languages are available. Under the policy rule for language or locale constraints, forcing a specific language without user opt-in is a natural-language policy concern.

Content

No source excerpt is available for this finding.