Security audit

无形资产摊销与研发资本化核对（免费版）

Security checks for vulnerabilities and agentic risk

Overview

This skill is a local Chinese-language ledger checking tool that does what it says and does not show hidden network, persistence, or credential behavior.

Install only if you are comfortable running a local Node-based checker on Chinese-format accounting ledgers. Review results as arithmetic checks, not legal, tax, or audit advice, because the skill explicitly leaves several higher-level compliance checks out of scope.

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
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
Excessive AgencyUnrestricted Tool Access, Autonomous Decision Making, Scope Creep

Findings (4)

Ae1

High

Category: analysis-evasion
Content: node scripts/run.mjs --sample # 先看内置样例（这张样例本身是干净的）
Confidence: 100% confidence
Finding: Referenced artifact was not completely inspected

Ae1

High

Category: analysis-evasion
Content: node scripts/run.mjs --sample # 先看内置样例（这张样例本身是干净的）
Confidence: 100% confidence
Finding: Referenced artifact was not completely inspected

Ae1

High

Category: analysis-evasion
Content: node scripts/run.mjs --sample # 先看内置样例（这张样例本身是干净的）
Confidence: 100% confidence
Finding: Referenced artifact was not completely inspected

Natural-Language Policy Violations

Medium

Confidence: 97% confidence
Finding: The file’s natural-language interface, comments describing behavior, user-facing advice, and sample input/output labels are all written in Chinese, indicating the skill is designed to operate in a fixed language/locale. There is no visible opt-in, fallback, or user choice for language, which can violate a language/locale policy requiring user selection rather than forced locale.

Static analysis

No suspicious patterns detected.