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Security audit

A股多Agent投研

Security checks for vulnerabilities and agentic risk

Overview

This skill appears to be an A-share investment research tool, but its metadata, execution authority, and install guidance are too mismatched and under-scoped for automatic trust.

Review this skill carefully before installing. It is not clearly an SEO tool despite its manifest text; it is a financial analysis skill that may use market-data APIs, API keys, local command execution, and an unpinned Python package. Only use it in an isolated environment, avoid privileged installs, verify the package source and version, and do not treat its investment outputs as decisions without human review.

Vulnerability Patterns
  • Insecure DependenciesIntroduces malicious components through unsafe dependency sources
  • 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
Findings (1)

T08 · Insecure Dependencies

Warning
Location
SKILL.md:222
Finding

Unpinned and Unverified Third-Party Package Installation

Content
View full analysis

Vulnerability Details

File Location: SKILL.md, line 222
Vulnerability Type: Insecure third-party dependency installation
Risk Level: Medium

Complete Code Snippet:

markdown
| Q1 | 如何安装agent-research? | 请确保您的系统满足最低要求,然后通过pip安装:`pip install agent-research` |

Technical Analysis

The documentation instructs users to install agent-research from the Python package index configured in their environment. The command does not pin an exact version, verify a package hash, identify a trusted publisher, or reference reviewable source code.

Because this project contains only SKILL.md and no implementation, the externally resolved package would provide the executable behavior. Its contents may differ from the audited Skill and may change over time. This creates a supply-chain exposure through package compromise, an unsafe configured index, package-name takeover, or installation of an unexpectedly modified release.

Python packages may execute package-controlled code during installation or later when imported and run. Consequently, following this instruction crosses the boundary from reviewed documentation to unreviewed executable code.

Attack Path

  1. An attacker compromises or takes control of the package, one of its dependencies, or a package index used by the target environment.
  2. The attacker publishes a malicious package version under the expected name or manipulates dependency resolution.
  3. A user follows the documented instruction and runs pip install agent-research.
  4. pip resolves and installs the attacker-controlled package because no exact version or integrity hash is required.
  5. Malicious code executes during installation or when the installed package is subsequently imported or invoked.

Impact Assessment

Malicious package code could execute with the privileges of the user running pip. Depending on those privileges and the environment, this could permit access to projec ...[truncated 446 chars]

Remediation
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Remediation Suggestions

  1. Remove the installation instruction unless the package identity, ownership, and source can be independently verified.
  2. Pin the dependency to a reviewed exact version, for example agent-research==X.Y.Z.
  3. Distribute and verify cryptographic hashes, using a locked requirements file and pip install --require-hashes.
  4. Document the trusted package index and verified publisher or official source repository.
  5. Review the package and its complete transitive dependency tree before recommending installation.
  6. Install into an isolated virtual environment or sandbox under a non-privileged account.
  7. Avoid administrator or root installation and restrict access to credentials and sensitive files during package installation and execution.
  8. Use a controlled internal package mirror and automated dependency scanning where appropriate.
Vulnerability Patterns
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Excessive AgencyUnrestricted Tool Access, Autonomous Decision Making, Scope Creep
  • 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
Findings (6)

Description-Behavior Mismatch

High
Category
Not specified by scanner
Confidence
99% confidence
Finding

The manifest description advertises SEO/keyword-ranking optimization, while the body documents A-share stock research and investment decision support. This mismatch can cause the skill to be invoked in the wrong contexts and prevents users or policy layers from accurately assessing the risks of financial analysis, external data access, and possible command execution.

Content

No source excerpt is available for this finding.

Vague Triggers

High
Category
Not specified by scanner
Confidence
96% confidence
Finding

An overly broad and ambiguous invocation phrase makes it easier for the skill to trigger outside its intended domain. Because this skill also advertises external data access and execution-related capabilities, vague routing language increases the chance of unintended activation, mishandling of sensitive inputs, or misuse in contexts where financial tooling is inappropriate.

Content

No source excerpt is available for this finding.

Description-Behavior Mismatch

Medium
Category
Not specified by scanner
Confidence
94% confidence
Finding

The generic name/slug 'agent-research' understates that the skill is specialized for A-share investment analysis and decision support. Mislabeling can bypass user expectations, routing controls, or reviews that depend on metadata, making a higher-risk financial skill appear broader and less sensitive than it is.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
91% confidence
Finding

The markdown describes API/data-source access and command-execution capability without a clear warning that data may be transmitted externally or that local/system commands may run. Users and reviewers may therefore provide sensitive inputs or enable the skill without understanding the operational risk, which is especially dangerous in a finance-oriented workflow that may use credentials and external providers.

Content

No source excerpt is available for this finding.

Context-Inappropriate Capability

Medium
Category
Not specified by scanner
Confidence
92% confidence
Finding

The skill declares exec capability even though its documented purpose is research/analysis, creating an unnecessary path to run shell commands. In agent platforms, surplus execution privileges materially increase the blast radius of prompt injection, malicious inputs, or operator misuse, especially when combined with API keys and file access.

Content

No source excerpt is available for this finding.

Intent-Code Divergence

Low
Category
Not specified by scanner
Confidence
76% confidence
Finding

The '安全性优化' section states that all external repository references and sensitive-leakage paths were removed. Yet the document later explicitly references external data sources and APIs such as Wind, 同花顺, Tushare, and discusses API key configuration, which contradicts the claim of removing such external references.

Content

No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.