Security audit

Openclaw Skill

Security checks for vulnerabilities and agentic risk

Overview

This governance skill is coherent in purpose, but it requires review because it can force broad agent actions and raw input through an unbundled Python engine with weak dependency scoping.

Review before installing. This skill is not merely advisory: it is designed to mediate many agent actions and external inputs through cord_engine. Only use it if you trust the exact cord_engine installation path/package, are comfortable with commands and input summaries being evaluated and logged, and understand where intent locks and audit logs are stored.

A.I.G

Vulnerability Patterns

Skill Instruction HijackingAlters the agent's session goals or safety constraints when the skill loads
Insecure Skill Coding PracticesFinds exploitable flaws such as hardcoded secrets or command injection
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 (2)

T01 · Skill Instruction Hijacking

Error

Location: SKILL.md:18
Finding: Mandatory Agent Behavior and Tool-Call Hijacking
Content: View full analysis
Remediation: View remediation

T09 · Insecure Skill Coding Practices

Error

Location: scripts/cord_status.py:15
Finding: Arbitrary Python Module Execution Through Unvalidated Import Path
Content: View full analysis
Remediation: View remediation

SkillSpector

Vulnerability Patterns

Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
MCP Least PrivilegeUnderdeclared Capability, Wildcard Permission, Missing Permission Declaration
Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code

Findings (4)

Undeclared Tool Scope

Medium

Category: MCP Least Privilege
Confidence: 90% confidence
Finding: The skill invokes Python and references local code execution paths, but it does not declare an explicit tool scope or allowed-tools policy. That creates governance ambiguity: an agent may treat the skill as broadly applicable and expose environment-derived data or execute supporting code without clear least-privilege boundaries, increasing the chance of unintended access or misuse.
Content: No source excerpt is available for this finding.

Missing User Warnings

Medium

Category: Not specified by scanner
Confidence: 92% confidence
Finding: The script prints the intent-lock user ID and full intent text directly to stdout, which can expose sensitive operational context, identities, or task descriptions to anyone with terminal access, shell history capture, logging, or redirected output. In a governance/security tool, this is more dangerous than ordinary status output because the intent text may summarize high-value actions, targets, or internal workflows.
Content: No source excerpt is available for this finding.

Missing User Warnings

Medium

Category: Not specified by scanner
Confidence: 94% confidence
Finding: The script prints recent audit-log proposal contents, which may contain sensitive prompts, file paths, network targets, secrets accidentally logged, or other operational details. Because audit logs in this skill are specifically tied to blocked or evaluated tool actions, exposing proposal text increases the chance of leaking security-relevant context through console output or collected logs.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Low

Category: Not specified by scanner
Confidence: 82% confidence
Finding: The skill mandates that every significant action be evaluated through CORD and includes identity-specific state such as user_id, passphrase, and intent locks, but it does not provide user opt-in or a consent boundary. In practice this can force agent workflows through an external policy layer that may process user/task data or establish persistent session controls without explicit authorization, which is a privacy and autonomy concern.
Content: No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.