Community AI Audit

Overview

Community AI Audit is a plugin-driven framework for auditing AI model behavior across providers and deployment targets. Run the same backdoor scan against OpenAI, Anthropic, local PyTorch models, or HuggingFace — without changing the scanner. Push findings to Splunk, Elastic, Datadog, or Sentinel.

Key Capabilities:

• Provider-Agnostic Scanning — Same audit plugins work across OpenAI, Anthropic, local models
• Plugin Architecture — Community-contributed audit checks, easily extensible
• Multi-Target Output — Push findings to SIEM platforms (Splunk, Elastic, Datadog, Sentinel)
• Backdoor Detection — Scan for embedded backdoors, prompt injection, and model tampering
• Behavioral Analysis — Test model responses against expected behavior patterns

Architecture

┌─────────────────────────────────────────────┐
│           Community AI Audit                │
├─────────────┬──────────────┬────────────────┤
│  Scanner    │  Plugins     │  Outputs       │
│  Engine     │  - Backdoor  │  - Splunk      │
│  - OpenAI   │  - Injection │  - Elastic     │
│  - Anthropic│  - Behavior  │  - Datadog     │
│  - PyTorch  │  - Bias      │  - Sentinel   │
│  - HF       │  - Hallucin. │  - Custom      │
└─────────────┴──────────────┴────────────────┘

Plugin System

Each audit is a self-contained plugin that can be shared across the community:

from community_ai_audit import Plugin

class BackdoorDetector(Plugin):
    name = "backdoor_scan"
    description = "Scans for embedded backdoors in model outputs"

    def scan(self, model_response, context):
        # Your detection logic here
        findings = []
        if self.detect_trigger_phrase(model_response):
            findings.append(Finding(
                severity="critical",
                description="Potential backdoor trigger detected"
            ))
        return findings

Getting Started

# Install the framework
pip install community-ai-audit

# Run an audit against OpenAI
audit run --provider openai --model gpt-4 --plugins backdoor_scan,behavior_check

# Run against a local PyTorch model
audit run --provider pytorch --model ./my_model.pt --plugins all

# Push findings to Splunk
audit run --provider openai --model gpt-4 --output splunk --splunk-host your-splunk

Use Cases

• Red Team Operations — Audit models before deployment
• Compliance Reporting — Generate audit trails for regulatory requirements
• Community Defense — Share plugins to protect against emerging threats
• Blue Team Ops — Continuous monitoring of deployed model behavior