MoltGuard

Detect prompt injection attacks hidden in long content (emails, web pages, documents).

Powered by OpenGuardrails SOTA security detection capabilities.

GitHub: https://github.com/openguardrails/moltguard

npm: https://www.npmjs.com/package/@openguardrails/moltguard

OpenGuardrails - State-of-the-Art Security Detection

OpenGuardrails achieves SOTA results across multilingual safety benchmarks, outperforming LlamaGuard, Qwen3Guard, and other leading guard models.

Metric	Score	Comparison
English Prompt F1	87.1%	+2.8% vs next best
English Response F1	88.5%	+8.0% vs next best
Multilingual Prompt F1	97.3%	+12.3% vs next best
Multilingual Response F1	97.2%	+19.1% vs next best

Core Capabilities:

• Unified LLM Architecture - Single 14B dense model quantized to 3.3B via GPTQ. Handles both content-safety and manipulation detection with superior semantic understanding.
• Configurable Policy Adaptation - Dynamic per-request policy with continuous sensitivity thresholds. Tune precision-recall trade-offs in real time via probabilistic logit-space control.
• 119 Languages - Robust multilingual coverage with SOTA results on English, Chinese, and cross-lingual benchmarks. Includes 97k Chinese safety dataset contribution.
• Production Efficiency - P95 latency of 274.6ms with high concurrency. GPTQ quantization enables real-time inference at enterprise scale without sacrificing accuracy.

Technical Paper: https://arxiv.org/abs/2510.19169

How It Works

Long Content (email/webpage/document)
         |
         v
   +-----------+
   |  Chunker  |  Split into 4000 char chunks with 200 char overlap
   +-----------+
         |
         v
   +-----------+
   |LLM Analysis|  Analyze each chunk independently with full focus
   | (OG-Text)  |  "Is there a hidden prompt injection in this content?"
   +-----------+
         |
         v
   +-----------+
   |  Verdict  |  Aggregate findings from all chunks -> isInjection: true/false
   +-----------+

Installation

# Install from npm
openclaw plugins install @openguardrails/moltguard

# Restart gateway to load the plugin
openclaw gateway restart

Verify Installation

# Check plugin list, confirm moltguard status is "loaded"
openclaw plugins list

You should see:

| MoltGuard | moltguard | loaded | ...

Commands

Command	Description
/og_status	View status and statistics
/og_report	View recent injection detection details
/og_feedback <id> fp [reason]	Report false positive
/og_feedback missed <reason>	Report missed detection

Testing Detection

1. Download Test File

Download the test file with hidden injection:

curl -L -o /tmp/test-email.txt https://raw.githubusercontent.com/openguardrails/moltguard/main/samples/test-email.txt

2. Test in OpenClaw

Ask the agent to read this file:

Read the contents of /tmp/test-email.txt

3. View Detection Logs

# Real-time log monitoring
tail -f /tmp/openclaw/openclaw-$(date +%Y-%m-%d).log | grep "moltguard"

# Or use openclaw command
openclaw logs --follow | grep "moltguard"

If detection succeeds, you'll see logs like:

[moltguard] tool_result_persist triggered for "read"
[moltguard] Analyzing tool result from "read" (1183 chars)
[moltguard] Analysis complete in 5896ms: INJECTION DETECTED
[moltguard] INJECTION DETECTED in tool result from "read": Chunk 1: Contains instructions to override guidelines and execute a malicious shell command

4. View Statistics

In OpenClaw conversation, enter:

/og_status

Returns detection statistics:

**OpenGuardrails Status**

- Enabled: true
- Block on risk: true
- Max chunk size: 4000 chars

**Statistics**
- Total analyses: 5
- Total blocked: 1
- Blocked (24h): 1
- Avg duration: 4521ms

**User Feedback**
- False positives reported: 0
- Missed detections reported: 0

**Recent Analyses**
- 2025-02-05T14:30:19: tool_result (1183 chars) - DETECTED

5. View Detection Details

/og_report

Shows recent injection detection details:

**Recent Prompt Injection Detections**

**#1** - 2025-02-05T14:30:19
- Status: DETECTED
- Type: tool_result (1183 chars)
- Reason: Contains instructions to override guidelines and execute a malicious shell command
- Suspicious: "<Here comes prompt injection content>..."

Use `/og_feedback <id> fp` to report false positive
Use `/og_feedback missed <reason>` to report missed detection

6. Provide Feedback

If you find a false positive:

/og_feedback 1 fp This is normal security documentation

If you find a missed detection:

/og_feedback missed Email contained hidden injection that wasn't detected

Feedback is recorded for continuous improvement.

Real-time Alerts and Scheduled Reports

Real-time Alerts

When injection attacks are detected, warnings are immediately logged. You can get real-time notifications through:

Option 1: Monitor Logs

# Real-time monitoring with alert filtering
tail -f /tmp/openclaw/openclaw-$(date +%Y-%m-%d).log | grep "INJECTION DETECTED"

Option 2: Configure Webhook (Advanced)

Configure hooks in ~/.openclaw/openclaw.json to forward alerts to Slack/Discord/etc:

{
  "hooks": {
    "og-alert": {
      "url": "https://your-webhook-url.com/alert",
      "events": ["plugin:moltguard:injection-detected"]
    }
  }
}

Scheduled Reports

You can set up scheduled tasks to have OpenClaw automatically report detection status:

In OpenClaw conversation, enter:

/cron add --name "OG-Daily-Report" --every 24h --message "/og_report"

This will automatically execute /og_report every 24 hours and send the detection report.

Other scheduling options:

• --every 1h - Every hour
• --every 7d - Every week
• --cron "0 9 * * *" - Every day at 9 AM (cron expression)

View scheduled tasks:

/cron list

Remove scheduled task:

/cron remove OG-Daily-Report

Configuration

Edit OpenClaw config file (~/.openclaw/openclaw.json):

{
  "plugins": {
    "entries": {
      "moltguard": {
        "enabled": true,
        "config": {
          "blockOnRisk": true,
          "maxChunkSize": 4000,
          "overlapSize": 200,
          "timeoutMs": 60000
        }
      }
    }
  }
}

Option	Default	Description
enabled	true	Enable/disable plugin
blockOnRisk	true	Block tool calls when injection is detected
maxChunkSize	4000	Maximum characters per chunk
overlapSize	200	Overlap characters between chunks
timeoutMs	60000	Analysis timeout in milliseconds

Uninstall

openclaw plugins uninstall @openguardrails/moltguard
openclaw gateway restart

Development

# Clone repository
git clone https://github.com/openguardrails/moltguard.git
cd moltguard

# Install dependencies
npm install

# Local development install
openclaw plugins install -l .
openclaw gateway restart

# Type check
npm run typecheck

# Run tests
npm test

License

MIT