Skill flagged — suspicious patterns detected

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Airdrop Participation Filter

v1.0.0

A decision helper that helps users decide whether to participate in an airdrop campaign. Use when the user considers joining an airdrop. Prompt-only.

0· 64·0 current·0 all-time
byhaidong@harrylabsj

Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for harrylabsj/airdrop-participation-filter.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Airdrop Participation Filter" (harrylabsj/airdrop-participation-filter) from ClawHub.
Skill page: https://clawhub.ai/harrylabsj/airdrop-participation-filter
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install airdrop-participation-filter

ClawHub CLI

Package manager switcher

npx clawhub@latest install airdrop-participation-filter
Security Scan
Capability signals
CryptoRequires walletRequires sensitive credentials
These labels describe what authority the skill may exercise. They are separate from suspicious or malicious moderation verdicts.
VirusTotalVirusTotal
Suspicious
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OpenClawOpenClaw
Suspicious
medium confidence
!
Purpose & Capability
The skill is described as prompt-only and declares no required config paths or credentials, yet handler.py attempts to read a SKILL.md from a hard-coded local path (/Users/jianghaidong/.openclaw/skills/{skill_name}/SKILL.md). That local filesystem access is not justified by the stated purpose and is incoherent with the declared requirements.
!
Instruction Scope
SKILL.md contains only prompt guidance (no file/system access). The runtime code (handler.py) contradicts this by reading a local file. The README/instructions do not mention reading local files or using skill_name to load local content, so the instructions and the implementation are out of sync.
Install Mechanism
No install spec, no external downloads, and no required binaries — low install risk. The only code is small and included in the package.
!
Credentials
The package declares no environment/credential needs, but the code accesses a specific user home path. Accessing arbitrary files in a user's home directory is disproportionate to the stated function and could expose local data. The code also takes a skill_name input and interpolates it into a filesystem path without sanitization (possible directory traversal).
Persistence & Privilege
The skill is not always-enabled and does not request elevated privileges. It also does not declare persistence. However, local file reads still increase its blast radius compared to an instruction-only skill.
What to consider before installing
This skill's documentation says it's prompt-only and needs nothing, but the included handler.py tries to read /Users/jianghaidong/.openclaw/skills/{skill_name}/SKILL.md using an unsanitized skill_name. That mismatch is suspicious — it may be an accidental leftover from development, but it also allows local file reads (and potentially directory traversal) which could leak sensitive files. Before installing or enabling: 1) Ask the publisher why the code reads a hard-coded home path and request removal of any local-file reads unless explicitly needed. 2) If you or a reviewer will run the code, inspect/modify handler.py to (a) avoid hard-coded paths, (b) sanitize/validate skill_name (reject path separators), or (c) remove _load_skill_meta entirely and use the packaged SKILL.md via safe APIs. 3) Run the skill in a sandboxed environment if you must test it, and verify there are no network calls and it doesn't read sensitive files. 4) If you can't get a satisfactory explanation or patch, treat the skill as untrusted and avoid installing it in environments with sensitive data. The current state is likely a coding oversight but is not justified by the skill's description, so proceed with caution.

Like a lobster shell, security has layers — review code before you run it.

latestvk97bhh0299xb16pxjphn97eat184zcwt
64downloads
0stars
1versions
Updated 1w ago
v1.0.0
MIT-0

airdrop-participation-filter

A decision helper that helps users decide whether to participate in an airdrop campaign.

Workflow

  1. Ask what the airdrop is: which protocol, what the qualification criteria are, and what the potential value might be.
  2. Assess time commitment, risk of exposure to unknown protocols, and opportunity cost.
  3. Check whether the user has the technical setup to participate safely.
  4. Flag disguised data collection, VPN restrictions, and regulatory gray areas.
  5. Give a recommendation: worth it, conditional, or skip.

Output Format

  • Airdrop summary
  • Participation recommendation
  • Time and risk assessment
  • Safety checklist before joining
  • What to watch for during participation

Quality Bar

  • Does not over-promise potential airdrop value.
  • Focuses on whether participation is worth the user's time and risk.
  • Flags security risks of interacting with early-stage or unknown protocols.

Edge Cases

  • If the user needs to connect a wallet or deposit funds, flag this as a red flag.
  • If the qualification criteria require significant personal data, flag regulatory risk.

Compatibility

  • Prompt-only, no wallet connection required.
  • Works from user-described or pasted campaign details.

Comments

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