perfecXion.ai
Enterprise-Ready AI Security Testing

ADAPT-AI

Advanced AI Attack Testing Framework - A comprehensive security testing platform implementing state-of-the-art adversarial AI research techniques with machine learning capabilities for continuous improvement and adaptation.

10+ Attack CategoriesMulti-Modal SupportML-Powered LearningEnterprise Ready
# Initialize ADAPT-AI
from adapt_ai import AdaptClient

client = AdaptClient(api_key="your-api-key")

# Run comprehensive attack suite
result = await client.attack.comprehensive({
    target="https://api.example.com/chat",
    techniques=["gradient", "multimodal", "social_engineering"],
    evasion=True,
    ml_analysis=True
})

# ML-powered analysis
analysis = await client.ml.analyze_patterns(result)
print(f"Success rate: {analysis.success_rate}")
print(f"Vulnerabilities: {analysis.vulnerabilities}")
print(f"Recommended defenses: {analysis.defenses}")

Advanced Security Testing Capabilities

Comprehensive AI security testing with state-of-the-art attack techniques and adaptive learning

Advanced Gradient Optimization

State-of-the-art gradient-based attacks with Adam optimizer, momentum, and adaptive learning rates for maximum effectiveness

Comprehensive Multi-Modal Attacks

Cross-modal attack synchronization across text, image, audio, video, and file uploads with steganographic techniques

Sophisticated Social Engineering

10+ psychological manipulation techniques including authority impersonation, emotional manipulation, and trust-building sequences

Advanced Evasion Techniques

9 evasion categories including dynamic obfuscation, fingerprint randomization, and real-time strategy adaptation

ML-Powered Learning System

Ensemble learning with reinforcement learning, genetic optimization, and real-time pattern evolution

Enterprise-Grade Architecture

Production-ready microservices with PostgreSQL, Redis, Docker, and comprehensive monitoring

State-of-the-Art Attack Techniques

10+ advanced attack categories implementing cutting-edge adversarial AI research

Gradient-Based Attacks

  • • Adam optimizer with momentum
  • • Gradient clipping & adaptive learning
  • • Adversarial suffix generation
  • • Token-level manipulation

Multi-Modal Attacks

  • • Image + text prompt injection
  • • Audio manipulation & steganography
  • • Video content attacks
  • • File upload exploitation

Social Engineering

  • • Authority figure impersonation
  • • Emotional manipulation techniques
  • • Trust building sequences
  • • Consensus pressure tactics

Evasion Techniques

  • • Dynamic obfuscation
  • • Fingerprint randomization
  • • Real-time strategy adaptation
  • • Defense mechanism detection

ML Learning System

  • • Ensemble learning algorithms
  • • Reinforcement learning
  • • Genetic optimization
  • • Real-time pattern evolution

Enterprise Features

  • • Docker & Kubernetes support
  • • PostgreSQL & Redis
  • • Comprehensive monitoring
  • • Production-ready architecture

Multi-Layered Architecture

Enterprise-grade architecture designed for scalability and performance

API Gateway Layer

FastAPI-based microservices with authentication, rate limiting, and comprehensive request routing

Service discoveryAttack orchestrationReal-time monitoringWebSocket updatesLoad balancing

Core Attack Engine

Advanced attack engine with 10+ attack categories, ML algorithms, and adaptive strategies

Gradient attacksMulti-modal attacksSocial engineeringEvasion techniquesReal-time adaptation

ML Learning System

Comprehensive ML system with ensemble learning, reinforcement learning, and genetic optimization

Pattern evolutionStrategy optimizationReal-time adaptationModel improvementA/B testing

Enterprise Infrastructure

Production-ready infrastructure with PostgreSQL, Redis, Docker, and comprehensive monitoring

Database managementCaching optimizationContainer orchestrationPerformance monitoringSecurity controls

Technical Specifications

Enterprise-grade performance and capabilities for production environments

Performance

Response Time: < 500ms attack generation
Throughput: 1000+ concurrent tests
Latency: Real-time adaptation

Reliability

Availability: 99.9% uptime SLA
Attack Categories: 10+ advanced techniques
Multi-Modal: Text, Image, Audio, Video, Files

ML Capabilities

Learning: Ensemble learning, RL, Genetic optimization
Real-time: Pattern evolution
Adaptation: Strategy optimization

Enterprise

Infrastructure: Docker, Kubernetes, PostgreSQL, Redis
Monitoring: Comprehensive
Security: Production-ready

Why Choose ADAPT-AI?

Industry-leading capabilities for comprehensive AI security testing

State-of-the-Art Techniques

Implements 10+ cutting-edge adversarial AI research techniques with continuous updates as new attack vectors emerge

Comprehensive Multi-Modal Coverage

Tests across all modalities including text, image, audio, video, and file uploads with cross-modal synchronization

Advanced ML Learning System

Ensemble learning with reinforcement learning, genetic optimization, and real-time pattern evolution

Enterprise-Grade Architecture

Production-ready microservices with PostgreSQL, Redis, Docker, and comprehensive monitoring

Comprehensive Use Cases

ADAPT-AI serves diverse security testing needs across industries

AI Security Assessments

Red Team Operations

Compliance Testing

ML Model Validation

Vulnerability Research

Multi-Modal Security Testing

Social Engineering Simulation

Evasion Technique Testing

Enterprise Security Audits

AI System Hardening

Quick Integration

Get started with ADAPT-AI in minutes using our SDKs and REST API

Python SDK

from adapt_ai import AdaptClient

# Initialize ADAPT-AI client
client = AdaptClient(api_key="your-api-key")

# Run advanced gradient optimization attack
result = await client.attack.gradient_optimize(
    target="https://api.example.com/chat",
    objective="test_jailbreak",
    iterations=100,
    learning_rate=0.01,
    momentum=0.9
)

# Execute multi-modal attack
multimodal_result = await client.attack.multimodal({
    target: "https://api.example.com/vision",
    modes: ['text', 'image', 'audio'],
    strategy: 'adaptive'
})

# Analyze results with ML
analysis = await client.ml.analyze_patterns(result)
print(f"Success rate: {analysis.success_rate}")
print(f"Detected vulnerabilities: {analysis.vulnerabilities}")
print(f"Recommended defenses: {analysis.defenses}")

JavaScript SDK

import { AdaptAI } from '@adapt-ai/sdk';

const adapt = new AdaptAI({ apiKey: 'your-api-key' });

// Discover AI endpoints
const targets = await adapt.discovery.scan({
  domain: 'example.com',
  depth: 3
});

// Execute comprehensive attack suite
const result = await adapt.attack.comprehensive({
  target: targets[0],
  techniques: ['gradient', 'multimodal', 'social_engineering'],
  evasion: true,
  ml_analysis: true
});

REST API

curl -X POST "https://api.adapt-ai.com/v1/attack" \
  -H "Authorization: Bearer your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "target": "https://api.example.com/chat",
    "attack_type": "comprehensive",
    "techniques": ["gradient_optimization", "multimodal", "social_engineering"],
    "parameters": {
      "iterations": 100,
      "learning_rate": 0.01,
      "momentum": 0.9,
      "evasion": true,
      "ml_analysis": true
    }
  }'

Ready to Secure Your AI Systems?

Start testing your AI systems with the most advanced security framework available