Security audit

Repo Analysis

Security checks for vulnerabilities and agentic risk

Overview

This skill is a coherent repository-analysis helper with no executable payload, persistence, credential handling, or hidden behavior found.

Before installing, expect the skill to inspect repository files and, for public GitHub projects, optionally use basic public project-health signals. Clarify the repository scope and preferred output language when your request could be ambiguous.

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

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 (6)

Vague Triggers

Medium

Category: Not specified by scanner
Confidence: 93% confidence
Finding: The trigger list includes very broad natural-language phrases such as '读一下这个项目', '看看这个 GitHub 仓库', and '这个项目怎么样', which can match many ordinary requests and cause the skill to activate when the user did not intend a repository-analysis workflow. Unintended invocation can redirect the assistant into repo-scanning behavior, increasing the chance of irrelevant tool use, scope creep, or accidental processing of repository/GitHub targets when a lighter response would have been safer.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium

Category: Not specified by scanner
Confidence: 90% confidence
Finding: The skill is centered on Chinese-named modes and Chinese trigger/examples without explicitly preserving user language preference, which can cause language mismatches and reduce transparency about what the skill is doing. While this is not a direct code-execution issue, forced or assumed language can confuse users, lead to misunderstood summaries, and make safety-critical clarifications less reliable.
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 file is written entirely in Chinese and does not indicate that language selection is optional or limited to a region-specific context. Under the stated policy, forcing a specific language without user opt-in is a natural-language policy violation.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium

Category: Not specified by scanner
Confidence: 92% confidence
Finding: The skill instructions are written entirely in Chinese and include no indication that the user can choose another language or that Chinese is required for a region-specific purpose. Under the policy, forcing a specific language without opt-in is a natural-language policy violation.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium

Category: Not specified by scanner
Confidence: 94% confidence
Finding: The instruction "按用户意图选择一种，不必每次都全写。" appears in Chinese and, in the context of the whole template being written entirely in Chinese, effectively fixes the skill's output/instructions to a specific language. The file does not provide any opt-in, fallback, or user-selectable language behavior, which is a natural-language locale policy concern.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Low

Category: Not specified by scanner
Confidence: 88% confidence
Finding: The natural-language content of this markdown file is written entirely in Chinese, while the surrounding headings and broader skill context are not documented as Chinese-only or region-specific. Under the stated policy, forcing a specific language without user opt-in or justification is a locale-policy concern.
Content: No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.