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OpenClaw

openscan

Scan binaries and scripts for malicious patterns before trusting them. Use when installing skills, evaluating unknown binaries, or auditing tool dependencies.

dev-null3210 installations selon la source☆ 0 Étoiles du dépôtv1.0.0

Installation

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.

SkillHub CLI

skillhub install dev-null321/openscan

Examinez la source et la compatibilité, puis suivez les étapes d’installation.

Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.

Voir la source ↗Guides

Instructions

OpenScan

Lightweight malware detection for macOS and Linux binaries/scripts. Ported from the Harkonnen antimalware engine.

What It Detects

Binary Analysis:

  • Mach-O (macOS) and ELF (Linux) parsing
  • Suspicious dylibs/shared objects (Frida, injection frameworks)
  • Missing/invalid code signatures (macOS)
  • Disabled security features (PIE, NX, RELRO)
  • Packed/encrypted binaries (high entropy)

Pattern Detection:

  • Shellcode byte sequences
  • Suspicious API references (process injection, keylogging, etc.)
  • Network indicators (embedded URLs, IPs)
  • Encoded payloads (base64 blobs)

Script Analysis:

  • Dangerous shell patterns (curl|bash, eval, etc.)
  • Obfuscation indicators
  • Privilege escalation attempts

Usage

# Scan a single binary
node bin/scan.js /path/to/binary

# Scan a skill folder
node bin/scan.js /path/to/skill-folder

# JSON output for automation
node bin/scan.js /path --json

# Only show threats
node bin/scan.js /path --quiet

Exit Codes

  • 0 - Clean (score ≤ 20)
  • 1 - Suspicious (score 21-60)
  • 2 - High threat (score > 60)

Threat Scoring

Each file receives a score from 0-100:

Score Level Meaning
0-20 CLEAN No significant findings
21-40 LOW Minor concerns, probably safe
41-60 MEDIUM Suspicious patterns, review manually
61-80 HIGH Likely malicious or dangerous
81-100 CRITICAL Known malicious patterns

Integration with OpenClaw

Use before installing or trusting unknown binaries:

// Example: scan before allowing a skill's binary
const { scanFile } = require('openscan/lib/scanner');

async function checkBinary(binPath) {
  const result = await scanFile(binPath);
  if (result.threatScore > 40) {
    throw new Error(`Binary failed security scan: ${result.findings.join(', ')}`);
  }
  return true;
}

Li...

Informations sur la source

Source
github
Repository
openclaw/skills
Path
skills/dev-null321/openscan
Version
1.0.0
Commit
028b692102ed9b4be01a79bc4651ad624ee8b4f7
Source de classification
rules
Statut
active
Visibilité
public

Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.

README

OpenScan

A lightweight malware detection library for OpenClaw, targeting macOS and Linux binaries and scripts. Ported from the Harkonnen antimalware engine.

Why This Exists

OpenClaw skills can declare binary dependencies via requires.bins. Users install these binaries from various sources (Homebrew, npm, apt, random GitHub releases). There's currently no verification that these binaries are safe.

This scanner provides:

  • Pre-trust scanning of binaries before execution
  • Skill folder auditing to catch malicious scripts
  • Programmatic API for integration into OpenClaw's skill loading

Features

Binary Analysis
Platform Format Detection
macOS Mach-O (32/64-bit, Universal/FAT) Suspicious dylibs, code signature, encryption, security flags
Linux ELF (32/64-bit) Suspicious shared objects, security features (PIE, NX, RELRO)

What it checks:

  • Suspicious libraries: Frida, Cynject, MobileSubstrate, injection frameworks
  • Code signatures: Missing or invalid signatures (macOS)
  • Security features: ASLR/PIE disabled, executable stack/heap, missing NX
  • Packing/encryption: High entropy detection, encrypted segments
  • Segment anomalies: Suspicious names like __INJECT, UPX, __MALWARE
Pattern Detection

Scans binary content for:

  • Shellcode patterns: x86/x64 prologue sequences, NOP sleds, infinite loops
  • Suspicious APIs: Process injection (CreateRemoteThread, VirtualAllocEx), keylogging (GetAsyncKeyState), anti-debugging (IsDebuggerPresent)
  • Network indicators: Embedded URLs, IP addresses
  • Encoded payloads: Large base64 blobs
Script Analysis

For shell scripts, Python, JavaScript, etc.:

  • Dangerous patterns: curl | bash, eval(), base64 decode + exec
  • Persistence mechanisms: crontab, launchctl, LaunchAgents
  • Injection vectors: LD_PRELOAD, DYLD_INSERT_LIBRARIES
  • **Obfuscati...

Contenu extrait

SKILL.md
# OpenScan

Lightweight malware detection for macOS and Linux binaries/scripts. Ported from the Harkonnen antimalware engine.

## What It Detects

**Binary Analysis:**
- Mach-O (macOS) and ELF (Linux) parsing
- Suspicious dylibs/shared objects (Frida, injection frameworks)
- Missing/invalid code signatures (macOS)
- Disabled security features (PIE, NX, RELRO)
- Packed/encrypted binaries (high entropy)

**Pattern Detection:**
- Shellcode byte sequences
- Suspicious API references (process injection, keylogging, etc.)
- Network indicators (embedded URLs, IPs)
- Encoded payloads (base64 blobs)

**Script Analysis:**
- Dangerous shell patterns (curl|bash, eval, etc.)
- Obfuscation indicators
- Privilege escalation attempts

## Usage

```bash
# Scan a single binary
node bin/scan.js /path/to/binary

# Scan a skill folder
node bin/scan.js /path/to/skill-folder

# JSON output for automation
node bin/scan.js /path --json

# Only show threats
node bin/scan.js /path --quiet
```

## Exit Codes

- `0` - Clean (score ≤ 20)
- `1` - Suspicious (score 21-60)
- `2` - High threat (score > 60)

## Threat Scoring

Each file receives a score from 0-100:

| Score | Level    | Meaning                              |
|-------|----------|--------------------------------------|
| 0-20  | CLEAN    | No significant findings              |
| 21-40 | LOW      | Minor concerns, probably safe        |
| 41-60 | MEDIUM   | Suspicious patterns, review manually |
| 61-80 | HIGH     | Likely malicious or dangerous        |
| 81-100| CRITICAL | Known malicious patterns             |

## Integration with OpenClaw

Use before installing or trusting unknown binaries:

```javascript
// Example: scan before allowing a skill's binary
const { scanFile } = require('openscan/lib/scanner');

async function checkBinary(binPath) {
  const result = await scanFile(binPath);
  if (result.threatScore > 40) {
    throw new Error(`Binary failed security scan: ${result.findings.join(', ')}`);
  }
  return true;
}
```

## Li...
README
# OpenScan

A lightweight malware detection library for OpenClaw, targeting macOS and Linux binaries and scripts. Ported from the [Harkonnen](https://github.com/dev-null321/Harkonnen) antimalware engine.

## Why This Exists

OpenClaw skills can declare binary dependencies via `requires.bins`. Users install these binaries from various sources (Homebrew, npm, apt, random GitHub releases). There's currently no verification that these binaries are safe.

This scanner provides:
- **Pre-trust scanning** of binaries before execution
- **Skill folder auditing** to catch malicious scripts
- **Programmatic API** for integration into OpenClaw's skill loading

## Features

### Binary Analysis

| Platform | Format | Detection |
|----------|--------|-----------|
| macOS | Mach-O (32/64-bit, Universal/FAT) | Suspicious dylibs, code signature, encryption, security flags |
| Linux | ELF (32/64-bit) | Suspicious shared objects, security features (PIE, NX, RELRO) |

**What it checks:**
- **Suspicious libraries**: Frida, Cynject, MobileSubstrate, injection frameworks
- **Code signatures**: Missing or invalid signatures (macOS)
- **Security features**: ASLR/PIE disabled, executable stack/heap, missing NX
- **Packing/encryption**: High entropy detection, encrypted segments
- **Segment anomalies**: Suspicious names like `__INJECT`, `UPX`, `__MALWARE`

### Pattern Detection

Scans binary content for:
- **Shellcode patterns**: x86/x64 prologue sequences, NOP sleds, infinite loops
- **Suspicious APIs**: Process injection (CreateRemoteThread, VirtualAllocEx), keylogging (GetAsyncKeyState), anti-debugging (IsDebuggerPresent)
- **Network indicators**: Embedded URLs, IP addresses
- **Encoded payloads**: Large base64 blobs

### Script Analysis

For shell scripts, Python, JavaScript, etc.:
- **Dangerous patterns**: `curl | bash`, `eval()`, base64 decode + exec
- **Persistence mechanisms**: crontab, launchctl, LaunchAgents
- **Injection vectors**: `LD_PRELOAD`, `DYLD_INSERT_LIBRARIES`
- **Obfuscati...

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