almoiz/Energy-Guard-OS-Security-Benchmark

🛡️ Energy-Guard OS: Sovereign AI Security Gateway

The world's first on-premise AI security gateway delivering real-time protection for Large Language Models (LLMs) with performance that far surpasses cloud and traditional solutions.

Energy-Guard OS is a CPU-native, sovereign AI security gateway that protects enterprise LLM deployments in real time. Operating at under 13 milliseconds per request without a GPU, fitting entirely within 411 MB, and processing over 9,500 words per second, it occupies a category that no competitor currently addresses: lightweight, sovereign, and comprehensively intelligent AI security.

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Key Capabilities and Features

Ultra-Fast Performance

• Internal kernel latency: 4.1 to 13 milliseconds
• Single-request mode: ~13ms processing time
• Batch processing mode: ~4.1ms per request (at 100-250 batch size)
• Real-world API throughput: 427.77 requests/second
• The system becomes more efficient under load through full tensor utilization

Minimal System Footprint

• Entire system operates at only 411 MB
• Smallest known intelligent security gateway
• CPU-only operation — no GPU required
• No Kubernetes orchestration needed
• Zero external dependencies

Complete Sovereignty (Air-Gapped)

• No GPU or cloud connection required
• Fully compliant with GDPR, EU AI Act, HIPAA, and SOX
• All processing occurs in RAM — zero disk writes of content
• Perfect for government, defense, and regulated industries
• Deploy on any bare-metal fleet without routing data through third-party clouds

Comprehensive Threat Coverage

Energy-Guard OS is the only system that integrates threat intelligence for IT, AI, and OT/SCADA into a single processing line:

Category	Frameworks	Coverage
AI Threats	MITRE ATLAS	Model extraction, adversarial inputs, supply chain poisoning
IT Threats	MITRE ATT&CK	APT groups, lateral movement, Kerberoasting, pass-the-hash
LLM Security	OWASP LLM Top 10	Prompt injection, insecure output, sensitive disclosure, XSS
OT/SCADA	Triton, Stuxnet, PIPEDREAM	Modbus/DNP3/Triconex patterns in AI conversations
Evasion	8-Layer Decoding	Base64, URL, HTML, Hex, ROT13, Zero-width, Unicode, Double-encode
Multilingual	Arabic RTL + Unicode	Full semantic Arabic detection; Chinese, Russian, German support

Full Arabic Language Support

• Deep semantic processing of right-to-left (RTL) text
• Full Arabic attack detection at inference level
• Not surface-level filtering — true semantic understanding

Session Intelligence

• Cumulative threat scoring across entire conversation sessions
• Multi-turn escalation detection
• Per-user risk accumulation with exponential decay
• Role-based adaptive thresholds
• Detects social engineering attacks spanning multiple conversation turns

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Benchmarks

Performance Metrics

Metric	Value	Notes
Capacity	9,541 words/second	7.5× above industry benchmark
Single Request Latency	13 ms	Kernel processing time
Batch Latency	4.1 ms/request	At 100-250 batch size
Real-World RPS	427.77 req/sec	Live endpoint under load
Peak Throughput	345 req/sec	Kernel stress test
Stress Test	0 dropped batches	2,500 requests, 10 threads
System Footprint	411 MB	CPU-only, no GPU

Detection Accuracy

Attack Category	Accuracy	Status
Financial Data Leaks (IBAN, SWIFT, wire transfers)	100%	Production Ready
PII/Private Data (SSN, passport, API keys, credentials)	100%	Production Ready
Strategic Leaks (M&A documents, roadmaps)	100%	Production Ready
Technical Code (malware, injection)	72.8%	Active Improvement

Independent Security Benchmark (JailbreakBench)

System	F1-Score	Attack Success Rate ↓	AUROC
Energy-Guard OS	0.722	0.292	0.651
LlamaGuard-2	0.529	0.640	0.680
Keyword Filter	0.246	0.860	0.570

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Architecture: Three-Path Sovereign Decision Engine

Every input passes through three analytical paths in sequence. The first path to reach a definitive conclusion terminates the pipeline — enabling sub-13ms total latency without sacrificing coverage depth.

┌─────────────────────────────────────────────────────────────────┐
│                    ENERGY-GUARD OS V27                          │
├─────────────────────────────────────────────────────────────────┤
│  ┌──────────────┐   ┌──────────────┐   ┌──────────────────┐   │
│  │  Path ①      │   │  Path ②      │   │  Path ③          │   │
│  │  Sovereign   │──▶│  Rule Engine │──▶│  Neural Engine   │   │
│  │  Energy Map  │   │  (600+ regex)│   │  (15.4M params)  │   │
│  │  < 1ms       │   │  < 2ms       │   │  4-13ms          │   │
│  └──────────────┘   └──────────────┘   └──────────────────┘   │
│         │                  │                    │               │
│         ▼                  ▼                    ▼               │
│  Known signatures    Deterministic threats   Novel & semantic   │
│  Safe-category       8-layer decode          Adaptive scoring   │
│  fast-pass           pre-scan                                   │
└─────────────────────────────────────────────────────────────────┘

8-Layer Evasion Decoding Engine

Before any security analysis, every input is recursively decoded through 8 layers:

Layer	Encoding Defeated	Example
1	Base64 (Standard + URL-safe)	aWdub3Jl... → "ignore all previous instructions"
2	URL Percent Encoding	%69%67%6e... → "ignore"
3	HTML Entities	ig... → "ignore"
4	Hex Escape Sequences	\x69\x67... → "ignore"
5	ROT13 Cipher	vtzber nyy... → "ignore all..."
6	Zero-Width Characters	i​g​n​o​r​e (hidden chars stripped)
7	Unicode Normalization	ｉｇｎｏｒｅ / Cyrillic homoglyphs → "ignore"
8	Double-Encoding	%2569%6e... decoded twice → plain text

⚠️ Key Differentiator: Without multi-layer recursive decoding, a single Base64 wrapper bypasses 100% of pattern-matching defenses in competing products.

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Testing Tools

This repository includes official testing tools to independently verify all performance and security claims:

Tool A: Sovereign Master Test Suite (v10.2)

# File: EnergyGuard_OS_Sovereign_Master_Test_Suite_v10.2.py

Property	Value
Test Volume	10,000+ test cases
Coverage	OWASP LLM Top 10, MITRE ATLAS, MITRE ATT&CK
Performance Mode	AsyncIO pipeline — 1,000+ cases/second
Stress Testing	Up to 1,000 concurrent users
Language Coverage	Arabic + English attack vectors
Output	JSON report + per-category accuracy + latency histogram

What it validates:

• Detection accuracy across all 8 attack taxonomy categories
• System stability under maximum concurrent load
• Sub-13ms latency validation across all test conditions
• Arabic vs. English detection parity

Tool B: EBMSovereign Independent Security Benchmark

# File: EBMSovereign_Independent_Security_Benchmark.py

Property	Value
Datasets	JailbreakBench + HarmBench + Alpaca (public, reproducible)
Detection Method	Dual-signal: verdict string + risk_score threshold
Metrics	ASR, F1-Score, Precision, Recall, AUROC, FPR
Baseline Comparison	vs. LlamaGuard-2 proxy and keyword filter
Output	benchmark_results.json + benchmark_report.txt + 6 PNG figures

What it validates:

• Attack Success Rate against 500 real-world jailbreak prompts
• False Positive Rate against 500 benign prompts
• API latency distribution (P50, P95, P99)
• Statistical significance via Mann-Whitney U test

Running the Evaluation Tools

# Prerequisites
pip install aiohttp datasets scikit-learn matplotlib seaborn numpy tqdm scipy

# Configure API endpoint
BASE_URL = 'http://ebmsovereign.com/v1/process'

# Run Sovereign Master Test Suite
python EnergyGuard_OS_Sovereign_Master_Test_Suite_v10.2.py

# Run Independent Security Benchmark
python EBMSovereign_Independent_Security_Benchmark.py

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Public API Reference

Test the system directly via the live endpoint (no registration required for initial testing):

Property	Value
Base URL	http://ebmsovereign.com/v1/
Authentication	X-API-Key header (contact for production key)
Response Format	JSON with verdict, risk_score, and performance metadata
Uptime SLA	99.9% under enterprise partnership

Endpoint 1: Single Request Analysis

POST /v1/process
Content-Type: application/json

Request:

{
  "text": "Your prompt or LLM response to inspect",
  "uid": "user_session_id_optional"
}

Response:

{
  "verdict": "✅ SAFE",
  "risk_score": 0.1234,
  "label": "unknown",
  "processing_time_ms": 12.87,
  "uid": "user_session_id_optional",
  "timestamp": 1775416327.208
}

Response Fields:

Field	Type	Range	Interpretation
verdict	string	"✅ SAFE" or "🚨 BLOCKED"	Primary binary decision
risk_score	float	0.0 – 1.0	< 0.50: safe | 0.50–0.85: borderline | > 0.85: block
processing_time_ms	float	0.39 – 15.0 ms	Internal engine time only
label	string	threat type or 'unknown'	Threat category for logging
uid	string	Echo of request uid	For request correlation

Endpoint 2: Batch Processing

POST /v1/process_batch
Content-Type: application/json

Request:

{
  "queries": [
    { "uid": "req_001", "text": "First text to inspect" },
    { "uid": "req_002", "text": "Second text to inspect" },
    ... up to 250 items per batch
  ]
}

Response:

{
  "results": [
    {
      "uid": "req_001",
      "verdict": "✅ SAFE",
      "risk_score": 0.1234,
      "label": "unknown"
    }
  ],
  "performance": {
    "batch_size": 250,
    "total_time_ms": 1040.12,
    "avg_latency_ms": 4.16,
    "throughput_rps": 240.35
  }
}

Risk Score Decision Logic (V27 Parser)

Implement this dual-signal logic to minimize false negatives:

def parse_v27_response(body: dict) -> tuple[bool, float]:
    """
    Parse Energy-Guard OS V27 response.
    Returns: (is_blocked: bool, risk_score: float)
    """
    verdict = str(body.get('verdict', '')).upper()
    risk_score = float(body.get('risk_score', 0.0))
    
    # Signal 1: explicit verdict string
    if 'BLOCKED' in verdict or 'WARNING' in verdict:
        return True, risk_score  # is_blocked = True
    
    # Signal 2: risk score threshold fallback
    if 'SAFE' in verdict and risk_score <= 0.85:
        return False, risk_score  # is_blocked = False
    
    # Fallback: score-only decision
    return risk_score > 0.85, risk_score

HTTP Status Codes

Code	Meaning	Action
200 OK	Request processed successfully	Read verdict and risk_score
422	Validation error in payload	Ensure 'queries' array with 'uid' and 'text'
429	Rate limit exceeded	Implement exponential backoff
500	Kernel processing error	Retry once; report if persistent
504	Gateway timeout	Reduce batch size to 100–150

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Competitive Comparison

System	Deployment	CPU Latency	Size	GPU Required	On-Premise	ICS/SCADA	Arabic
Azure Prompt Shield	SaaS Only	~349 ms	Cloud	Yes	❌	❌	❌
AWS Bedrock Guardrails	SaaS Only	~200+ ms	Cloud	Yes	❌	❌	❌
Lakera Guard	SaaS/Hosted	~61 ms	Unknown	Optional	Partial	❌	❌
LlamaGuard-86M	Self-hosted	~304 ms	Large	Yes	✅	❌	❌
NeuralTrust-118M	Self-hosted	~39 ms	Large	Optional	✅	❌	❌
CalypsoAI	Enterprise	~250 ms	Large	Yes	✅	❌	❌
Energy-Guard OS	Air-gapped/Any	4.1–13 ms	411 MB	No	✅	✅	✅

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Use Cases

Deployment Patterns

Pattern	Description	Best For
Inline API Proxy	Energy-Guard sits in front of OpenAI, Claude, Gemini	SaaS hosting, multi-tenant AI platforms
Edge Sidecar	Deployed alongside customer's LLM as container	Dedicated servers, private cloud, K8s
Air-Gapped Gateway	Fully isolated, no external dependencies	Government, defense, regulated industries
Marketplace Add-On	One-click activation from control panel	Self-serve cloud providers

Target Segments

Segment	Key Pain Point	Energy-Guard Value
Banking & Finance	Regulatory exposure (SOX, GDPR)	100% financial leak detection; air-gapped
Healthcare	HIPAA compliance	PII/PHI filtering; on-premise; audit trail
Government & Defense	Classified data sovereignty	Air-gapped; Arabic + multilingual; ICS-aware
Energy & Utilities	OT/SCADA AI-enabled	Only product with native ICS/SCADA patterns
SaaS/AI Builders	Customer data protection	$0.001/req; 427 RPS; zero infrastructure

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Partnership Opportunities

Partnership Tier	Model	Revenue Structure
Technology OEM	Embed engine in your platform	Negotiated royalty per activation
Marketplace Reseller	One-click add-on in marketplace	30–40% margin
White-Label Partner	Deploy under your brand	40–50% margin
Referral Partner	Refer enterprise customers	20% commission

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Contact & Support

• Website: ebmsovereign.com
• Email: arrangements@ebmsovereign.com
• Live API: http://ebmsovereign.com/v1/
• Partnership: arrangements@ebmsovereign.com

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License

Energy-Guard OS is commercial software. Contact EBMSovereign for licensing terms.

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EBMSovereign · Sovereign AI Security
CPU-native. 411 MB. 4.1–13ms. Air-gapped. Covers IT + AI + OT/SCADA. Speaks Arabic.