Security audit

A-Stock Kline Analyzer

Security checks for vulnerabilities and agentic risk

Overview

This A-share analyzer mostly matches its stated purpose, but its system-level install guidance and documentation mismatches warrant review before use.

Install only in a virtual environment, avoid the documented --break-system-packages command, review/pin dependencies including requests, and treat generated trading suggestions as educational analysis rather than financial advice. Be aware that some advertised features may not work as documented.

A.I.G

Vulnerability Patterns

Insecure DependenciesIntroduces malicious components through unsafe dependency sources
Insecure Skill Coding PracticesFinds exploitable flaws such as hardcoded secrets or command injection
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

Findings (2)

T08 · Insecure Dependencies

Warning

Location: SKILL.md:54
Finding: Unpinned dependencies installed while bypassing system package protections
Content: View full analysis
Remediation: View remediation

T09 · Insecure Skill Coding Practices

Warning

Location: batch_analyze.py:5
Finding: Current working directory is given priority during Python module resolution
Content: View full analysis
Remediation: View remediation

SkillSpector

Vulnerability Patterns

MCP Least PrivilegeUnderdeclared Capability, Wildcard Permission, Missing Permission Declaration
MCP Tool PoisoningHidden Instructions, Unicode Deception, Parameter Description Injection
Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access

Findings (5)

Tp4

High

Category: MCP Tool Poisoning
Confidence: 91% confidence
Finding: The metadata and documentation overclaim functionality and version state, including v1.0.6 features that static analysis indicates are only partially implemented and a version mismatch with the underlying code. In security terms, misleading capability claims reduce operator trustworthiness checks and can cause users to rely on analyses, outputs, or data provenance that the skill does not actually provide, which is especially risky for a networked financial-analysis tool.
Content: No source excerpt is available for this finding.

Undeclared Tool Scope

Medium

Category: MCP Least Privilege
Confidence: 91% confidence
Finding: The skill advertises live quote retrieval from Sina Finance and historical data retrieval from Baostock, which implies outbound network access, but it does not declare any explicit tool scope or permissions. This creates an authorization and review gap: operators and users cannot easily see or constrain what external connectivity the skill requires, increasing the risk of unintended data egress or broader-than-necessary network use.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium

Category: Not specified by scanner
Confidence: 94% confidence
Finding: The skill name, description, and all user-facing documentation are entirely in Chinese and specifically position the tool as an A-share analyzer, but there is no indication that language is configurable or that Chinese-only operation is an explicit user choice. Under the policy, forcing a specific language without opt-in is a natural-language policy violation unless the locale constraint is clearly documented and justified.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium

Category: Not specified by scanner
Confidence: 95% confidence
Finding: The HTTP header hard-codes Accept-Language: zh-CN,zh;q=0.9, which enforces a specific language/locale preference in network requests. The file does not offer a user choice or document this locale restriction as an explicit, justified regional constraint.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Low

Category: Not specified by scanner
Confidence: 90% confidence
Finding: This Python file contains natural-language strings exclusively in Chinese, including the module docstring and console output, with no indication that the skill is region-specific or that users can select another language. That creates a language/locale policy issue under the stated rule because the skill implicitly forces a specific language without opt-in.
Content: No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.