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Security audit

Ai Intelligent Blockchain Platform

Security checks for vulnerabilities and agentic risk

Overview

This skill describes a blockchain app, but its install steps download and run unreviewed mutable code from GitHub, which makes it a Review item.

Review this skill before installing. Do not run the documented clone, pip install, or app.py commands unless you have inspected the referenced repository, pinned a trusted revision, and are using an isolated environment without wallet keys or sensitive credentials available.

Vulnerability Patterns
  • Remote Payload Retrieval and ExecutionFetches external code whose behavior can change after review
  • 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
  • Embedded Malicious CodeShips malicious scripts inside the skill and executes them locally
  • Unauthorized Access and Privilege EscalationObtains permissions beyond the task's legitimate needs
Findings (1)

T03 · Remote Payload Retrieval and Execution

Error
Location
SKILL.md:39
Finding
Unpinned Remote Repository Retrieval and Execution## Vulnerability Details **File Location**: `SKILL.md`, lines 39-42 **Vulnerability Type**: Remote payload retrieval and insecure dependency installation **Risk Level**: High ```bash git clone https://github.com/openclaw-skills/ai-intelligent-blockchain-platform cd ai-intelligent-blockchain-platform pip install -r requirements.txt python app.py ``` ### Technical Analysis The installation instructions clone a mutable external Git repository without pinning it to a reviewed commit hash, release tag, or verified artifact checksum. They then install packages from the remote repository's unavailable and unaudited `requirements.txt` file and execute its `app.py` file. Consequently, the code that users execute can differ from the content reviewed in this artifact. The audited package does not contain `requirements.txt`, `app.py`, or any other implementation files, so neither the application behavior nor its dependency chain can be verified locally. A compromised repository, malicious maintainer update, or unsafe dependency declaration could introduce arbitrary executable code after publication of the skill. Python package installation may itself execute code through package build backends or installation hooks. Running `python app.py` provides a second direct code-execution path. ### Attack Path 1. An attacker compromises the referenced GitHub repository, gains control of its publishing workflow, or otherwise causes malicious content to be served from the referenced mutable repository. 2. The attacker modifies `app.py`, `requirements.txt`, or a package referenced by the dependency manifest. 3. A user follows the documented installation commands. 4. `pip install -r requirements.txt` executes malicious package installation or build behavior, or installs a compromised dependency. 5. Alternatively or additionally, `python app.py` directly executes the attacker's modified application code. 6. The payload runs with the operating ...[truncated 551 chars]
Remediation
## Remediation Suggestions - Include the complete application implementation and dependency manifests in the skill package so they can be audited together. - If external retrieval is unavoidable, pin the repository to a specific reviewed commit hash rather than cloning the mutable default branch. - Distribute release artifacts with cryptographic checksums or signatures and verify them before installation or execution. - Pin every Python dependency to an exact reviewed version and use a lockfile containing integrity hashes, such as hashes enforced by `pip --require-hashes`. - Review direct and transitive dependencies for malicious packages, dependency confusion, typosquatting, and known vulnerabilities. - Avoid immediately executing newly downloaded code. Require a separate verification and approval step. - Perform installation and execution in a sandboxed, least-privileged environment without unnecessary credentials, wallet secrets, filesystem access, or network access. - Document the exact reviewed revision and provide a reproducible build or deployment process.
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 (3)

Natural-Language Policy Violations

Medium
Confidence
95% confidence
Finding
The manifest description and main markdown content present the skill exclusively in Chinese, with no indication that users may choose another language or that the skill is intentionally limited to a Chinese-speaking audience. This can violate a language/locale policy when a skill forces a specific language without user opt-in.

Description-Behavior Mismatch

Medium
Confidence
98% confidence
Finding
The manifest description says only 'AI intelligent ai-intelligent-blockchain-platform' and does not match the stated purpose of a blockchain smart-contract/DApp development skill. This mismatch can mislead users and automated routing systems about what the skill actually does, increasing the risk of inappropriate invocation, trust confusion, or concealment of higher-risk blockchain functionality.

Vague Triggers

Low
Confidence
91% confidence
Finding
The description is so vague that it does not define a clear trigger scope or activation context. In an agent ecosystem, ambiguous metadata can cause the skill to be selected in unintended contexts, which is more concerning here because blockchain-related actions may involve sensitive code generation, contract deployment, or transaction workflows.

Static analysis

No suspicious patterns detected.