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Security audit

Skill Forge

Security checks for vulnerabilities and agentic risk

Overview

The skill describes a real automation workflow, but it asks users to run unaudited local scripts that can integrate skills and post publicly to X/Twitter without clear confirmation boundaries.

Install only if you trust and have separately reviewed the external `evolution-engine` project at the specified path. Before running the pipeline, confirm what its `package.json` scripts do, what repositories it can clone or modify, what credentials it can read, and whether `announce` can post publicly. Prefer running discovery/evaluation separately from integration and social posting until explicit confirmation controls are documented.

Vulnerability Patterns
  • 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
  • Embedded Malicious CodeShips malicious scripts inside the skill and executes them locally
Findings (1)

T09 · Insecure Skill Coding Practices

Warning
Location
SKILL.md:25
Finding

Execution of Unverifiable Scripts from a Hard-Coded External Directory

Content
View full analysis

Vulnerability Details

File Location: SKILL.md, lines 25-36
Vulnerability Type: Insecure external script execution
Risk Level: Medium

Vulnerable Code

bash
cd /Volumes/data/openclaw/evolution-engine

# Full pipeline (scout → evaluate → integrate → verify → benchmark → announce)
pnpm pipeline

# Individual operations
pnpm scout
pnpm evaluate
pnpm integrate
pnpm verify
pnpm announce

Technical Analysis

The quick-start instructions change into the hard-coded, machine-specific directory /Volumes/data/openclaw/evolution-engine and execute package-manager scripts defined by the Node.js project at that location. That directory is outside the audited Skill package.

The supplied artifact contains only SKILL.md; it does not include the external project's package.json, implementation, dependency lockfile, or integrity metadata. Consequently, the behavior of pipeline, scout, evaluate, integrate, verify, and announce cannot be verified from the audited package. Whoever controls the external directory can control the commands executed under these script names. Package installation or execution may also trigger lifecycle scripts if the external project uses them.

This is an insecure Skill design because the documented entry point is neither self-contained nor bound to a reviewed source revision. It creates a trust-boundary violation between the reviewed documentation and the code that users or agents are instructed to execute.

Attack Path

  1. An attacker, compromised installer, or another local process creates or modifies the project at /Volumes/data/openclaw/evolution-engine.
  2. The attacker defines a malicious pipeline, scout, evaluate, integrate, verify, or announce script in that project's package.json, or compromises code or dependencies loaded by one of those scripts.
  3. A user or AI agent follows the instructions in SKILL.md and changes into the exte ...[truncated 1181 chars]
Remediation
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Remediation Suggestions

  1. Bundle the executable implementation, package.json, and dependency lockfile within the Skill package so the documented commands correspond to auditable code.
  2. Replace the hard-coded absolute directory with a path resolved relative to the Skill's own root directory.
  3. Pin third-party dependencies and the upstream source to reviewed, immutable versions or commit hashes.
  4. Verify downloaded or installed artifacts using cryptographic hashes or signed provenance before execution.
  5. Document the exact behavior and security requirements of every invoked package script.
  6. Separate discovery, cloning, integration, verification, and publication into independently reviewable operations.
  7. Require explicit user confirmation before repository cloning, dependency installation, credential access, network publication, or social-media posting.
  8. Run external evaluation and integration tasks with least privilege in an isolated container or sandbox, using restricted filesystem and network access.
  9. Avoid exposing credentials globally to the process. Provide narrowly scoped, short-lived tokens only to the specific operation that requires them.
  10. Fail safely when the expected project manifest, lockfile, source revision, or integrity metadata does not match the reviewed version.
Vulnerability Patterns
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
  • Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code
  • Excessive AgencyUnrestricted Tool Access, Autonomous Decision Making, Scope Creep
Findings (4)

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
5. **ClawHub 标准输出** — 集成结果直接生成 `skill.json` + `SKILL.md`,可 `clawhub publish`

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
84% confidence
Finding

The natural-language description and operational guidance are entirely 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 language or locale policy when no opt-in or justification is provided.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
92% confidence
Finding

The skill explicitly advertises automatic posting to X/Twitter, which creates a real risk of unintended external publication, data leakage, and reputational harm if a user runs the workflow without realizing it will post publicly. In this context, the skill is an automation engine that chains discovery, integration, and announcement steps, so silent or poorly disclosed outbound posting is more dangerous than in a purely local utility.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
95% confidence
Finding

The quick-start command encourages running the full pipeline, and the documented pipeline includes announce/social functions, but there is no nearby warning that execution may trigger network activity and public posting. That omission is dangerous because users often copy-paste startup commands, which could cause unintended outbound requests, token use, and public disclosure before the user understands the consequences.

Content

No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.