Security audit

Stock Trend Scanner

Security checks for vulnerabilities and agentic risk

Overview

This is a straightforward stock-analysis tool, but its buy/sell labels should be treated as informational signals, not financial advice.

Install only if you want a heuristic technical stock scanner that downloads public market data and prints Chinese-language reports. Do not treat its buy/sell labels as personalized financial advice, and prefer explicit requests like running a scan for named tickers rather than letting generic stock questions trigger it automatically.

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

Trigger AbuseOverly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
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 (8)

Ae1

High

Category: analysis-evasion
Confidence: 100% confidence
Finding: Referenced artifact was not completely inspected
Content: Scanner excerpt · SKILL.md (reported line 11)May include surrounding context.
md
python3 scripts/stock_scanner.py [SYMBOLS...]

Ae1

High

Category: analysis-evasion
Confidence: 100% confidence
Finding: Referenced artifact was not completely inspected
Content: Scanner excerpt · SKILL.md (reported line 16)May include surrounding context.
md
python3 scripts/stock_scanner.py [SYMBOLS...]

Ae1

High

Category: analysis-evasion
Confidence: 100% confidence
Finding: Referenced artifact was not completely inspected
Content: Scanner excerpt · SKILL.md (reported line 17)May include surrounding context.
md
python3 scripts/stock_scanner.py [SYMBOLS...]

Ae1

High

Category: analysis-evasion
Confidence: 100% confidence
Finding: Referenced artifact was not completely inspected
Content: Scanner excerpt · SKILL.md (reported line 18)May include surrounding context.
md
python3 scripts/stock_scanner.py [SYMBOLS...]

Vague Triggers

Medium

Category: Not specified by scanner
Confidence: 95% confidence
Finding: The skill advertises broad trigger phrases such as "stock analysis," "analyze [ticker]," and "check [stock symbol]," which can overlap with ordinary market discussion or informational requests. This can cause the agent to invoke the trading-oriented skill in contexts where the user did not explicitly ask for technical scanning or recommendations, increasing the chance of unintended financial guidance or inappropriate tool use.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium

Category: Not specified by scanner
Confidence: 96% confidence
Finding: This markdown file contains user-facing sample output entirely in Chinese, including headings and trading signals, with no indication that the user can choose another language or that the skill is intentionally limited to a Chinese-speaking locale. The policy explicitly flags language or locale constraints that are imposed without opt-in or justification.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium

Category: Not specified by scanner
Confidence: 94% confidence
Finding: This Python file’s natural-language docstrings and all user-facing report strings are written exclusively in Chinese, indicating the skill is designed to operate in a fixed language. Under the policy rule, forcing a specific language without user opt-in is a natural-language policy violation unless the locale constraint is explicitly documented and justified, which is not present here.
Content: No source excerpt is available for this finding.

Description-Behavior Mismatch

Medium

Category: Not specified by scanner
Confidence: 96% confidence
Finding: The code does more than neutral scanning: it assigns weighted scores and emits explicit trading recommendations such as '强烈买入', '买入', '卖出', and '强烈卖出'. In a stock-analysis skill, this is risky because users may treat the output as actionable financial advice despite the underlying logic being simplistic, heuristic, and lacking suitability checks, disclosures, or risk controls.
Content: No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.