SecScan AI Enterprise：支持 GPT-5、Claude Sonnet 5 等 26+ 模型的企业级 AI 渗透测试平台

SecScan AI Enterprise is a production-ready, cloud-native AI-powered penetration testing platform designed for enterprise security teams. It combines advanced AI, machine learning, microservices architecture, and comprehensive security frameworks to deliver professional-grade cybersecurity assessments.

Created by Yashab Alam

💰 Support the Project: Donate to SecScan AI Development | Help us build the future of AI-powered penetration testing!

🏢 Enterprise Features

🤖 Advanced AI Engine — Multi-Provider Support & Threat Intelligence

• 8 AI Providers: OpenAI, Anthropic (Claude), Google (Gemini), DeepSeek, GLM (Zhipu), Local LLMs (Ollama), OpenRouter, OrcaRouter Cyber Inference
• 26+ AI Models: GPT-5, GPT-5.6, o3, o4-mini, Claude Sonnet 5, Opus 4.8, Gemini 3.5 Flash, 3.1 Pro, DeepSeek R1, and more
• Runtime Model Switching: Change AI models on-the-fly with automatic provider fallback
• Automated Attack Graph Chaining: Multi-stage exploit sequence synthesis, MITRE ATT&CK mapping, critical defensive chokepoints, and Mermaid diagram generation
• CVE Threat Intelligence & EPSS Scoring: Real-time CVE metadata, EPSS exploit probability prediction, CISA KEV active exploitation tracking, and CVSS v3.1 vector analysis
• Machine Learning: Pattern recognition, anomaly detection, behavioral analysis
• Zero-Day Detection: ML-powered vulnerability discovery and correlation
• Risk Intelligence: CVSS scoring, compound risk calculation, exploit prioritization
• MITRE D3FEND Countermeasure Defense Matrix: Bi-directional mapping of synthesized attack paths directly to official MITRE D3FEND defensive countermeasures (WAF, Inbound Filtering, System Call Analysis, Least Privilege, Memory Hardening)
• Detection-as-Code & Sigma Rules Export: Automated export of production-ready Sigma Rules (YAML) and Splunk SPL queries for detected adversary techniques
• Automated Remediation Playbooks: Instant generation of Ansible Playbooks (YAML) and Bash Hardening scripts tailored to sever critical defensive chokepoints
• Automated Reporting: Executive summaries, technical details, remediation roadmaps, compliance mapping

🎯 AI Red Teaming & LLM Security Assessment (OWASP LLM Top 10)

• OWASP Top 10 for LLMs (2025/2026): Full coverage of Prompt Injection (Direct, Indirect, Delimiter Smuggling), Insecure Output Handling, Sensitive Information Disclosure (PII, API keys), Model DoS, and Excessive Agency
• Adversarial Evaluation Probes: Library of 25+ real-world probe tests evaluating jailbreaks, roleplay escapes, and meta-prompt extraction
• Robustness Scoring & Risk Grading: Automated calculation of robustness percentage (0-100%) and letter grades (A+, A, B, C, F)
• System Prompt Defensive Guardrails: Automated compilation of customized defensive system prompts neutralizing identified injection vectors

🛡️ Enterprise API Security & OpenAPI Auditor (OWASP API Top 10)

• OWASP API Security Top 10 (2023-2026): Deep contract and schema inspection covering BOLA/IDOR (API1), Broken Authentication (API2), Mass Assignment/BOPLA (API3), Unrestricted Resource Consumption (API4), BFLA (API5), Sensitive Business Flows (API6), SSRF (API7), Misconfigurations (API8), and Shadow/Deprecated APIs (API9)
• OpenAPI & Swagger Support: Seamless ingestion and analysis of OpenAPI v2, v3, and v3.1 definitions in JSON and YAML
• API Risk Scorecard & Remediation: Detailed vulnerability findings with CVSS scores, remediation code snippets, and DTO whitelist recommendations

☁️ Cloud Security Posture Management (CSPM) & Kubernetes Auditor (KSPM)

• Multi-Cloud Infrastructure Auditing: Deep inspection of AWS (S3, IAM, Security Groups, CloudTrail), Azure (Storage Accounts, Key Vaults, NSGs), GCP (Cloud Storage, IAM, Compute), and Kubernetes clusters
• CIS Benchmarks Compliance: Pre-configured compliance checks mapped to CIS AWS Foundations Benchmark v3.0, CIS Kubernetes Benchmark v1.8, and NIST SP 800-53
• Kubernetes Pod Security Standards (PSS) & RBAC: Automated auditing of container privileged mode, sensitive hostPath mounts (/var/run/docker.sock), runAsRoot execution, hostNetwork/hostPID namespace sharing, and excessive ClusterRoleBindings
• Infrastructure-as-Code (IaC) Scanning: Static evaluation of Terraform (.tf) and Kubernetes manifests (.yaml) to eliminate vulnerabilities before production deployment
• Automated Remediation Generation: One-click generation of executable Bash CLI scripts (AWS CLI, Azure CLI, gcloud, kubectl) and Terraform HCL remediation patches
• AI Threat Modeling & Blast Radius: Automatic correlation of cloud misconfigurations into full-tenant takeover attack paths and blast radius predictions

🛡️ Advanced SOC Analysis & SIEM Integration

• Advanced SOC Engine: Multi-format log parser/normalizer, IOC extraction, MITRE ATT&CK technique mapping
• Sliding-Window Correlation: Real-time event grouping, deduplication, and multi-stage attack timeline reconstruction
• Statistical Anomalies: Z-score volume profiling, off-hours execution, and IP/host diversity tracking
• Incident Response Playbooks: AI-driven IR response guidelines customized per attack vector
• SIEM Connectors: Native connectors for Splunk (HEC & searches), IBM QRadar (Ariel AQL), Elasticsearch, and customizable Webhooks

🛡️ Enterprise Security & Compliance

• Authentication: RBAC + LDAP/Active Directory integration
• Authorization: Role-based permissions (Admin, Lead, Senior, Pentester, Analyst)
• Compliance: OWASP, NIST, ISO27001, SOC2, PCI-DSS frameworks
• Audit Logging: Comprehensive activity tracking and forensics
• Data Protection: AES-256-GCM encryption, JWT tokens, secure sessions

🏗️ Cloud-Native Architecture

• Microservices: Docker containers with Kubernetes orchestration
• Service Discovery: Consul-based service registry
• Load Balancing: Nginx reverse proxy with auto-scaling
• Multi-Cloud: AWS, Azure, GCP deployment support
• High Availability: Circuit breakers, health checks, failover

⚡ Performance & Scalability

• Parallel Processing: Celery-based distributed task execution
• Multi-Layer Caching: Redis + memory caching with TTL management
• Database: PostgreSQL with connection pooling and replication
• Real-Time: WebSocket dashboards with live updates
• Auto-Scaling: Worker pools adapt to workload demands

📊 Enterprise Reporting & Analytics

• Dynamic Reports: HTML, PDF, JSON, XML, CSV export formats
• Real-Time Dashboards: Prometheus + Grafana monitoring stack
• Log Analytics: ELK stack (Elasticsearch + Kibana) integration
• Executive Summaries: AI-generated business impact assessments
• Compliance Reports: Framework-specific compliance documentation

🚀 Quick Start

Prerequisites

• Operating System: Linux (Ubuntu/Debian/RHEL/CentOS), macOS, or Windows WSL2
• Python: 3.8+ with pip and virtual environment support
• Docker: For containerized deployment (recommended)
• Resources: Minimum 4GB RAM, 20GB disk space

Enterprise Installation

# Clone the repository
git clone https://github.com/najafdev/secscan_ai.git
cd secscan_ai

# Run enterprise installer (sets up all services)
chmod +x install.sh
./install.sh

# Configure environment
cp .env.example .env
# Edit .env with your API keys and settings
nano .env

# Verify installation
python3 test_installation.py

Deployment Options

1. Standalone Enterprise Mode

# Activate virtual environment
source venv/bin/activate

# Run enterprise application
python3 advance_secscan_ai.py

2. API Server Mode

# Start REST API server
python3 advance_secscan_ai.py --api

# API available at: http://localhost:8000
# Health check: http://localhost:8000/api/health

3. Web Dashboard Mode

# Start web dashboard
python3 advance_secscan_ai.py --web

# Dashboard available at: http://localhost:8080

4. Full Enterprise Stack (Recommended)

# Deploy complete microservices stack
docker-compose up -d

# Services:
# - API Server: http://localhost:8000
# - Web Dashboard: http://localhost:8080  
# - Monitoring: http://localhost:9090 (Prometheus)
# - Analytics: http://localhost:3000 (Grafana)
# - Logs: http://localhost:5601 (Kibana)

5. Direct Assessment Mode

# Run immediate assessment
python3 advance_secscan_ai.py \
  --target example.com \
  --scope "Web application and API" \
  --auth-key "ENTERPRISE-2025-AUTH" \
  --assessment-type black-box \
  --compliance OWASP

🏗️ Enterprise Architecture

Core Components

graph TD
    A[Load Balancer/Nginx] --> B[SecScan AI API Gateway]
    B --> C[Authentication Service]
    B --> D[AI Engine Service] 
    B --> E[Exploitation Service]
    B --> F[Reporting Service]
    B --> SOC[SOC Analysis Service]
    
    C --> G[LDAP/AD]
    D --> H[OpenAI API]
    D --> H2[Anthropic API]
    D --> H3[Google Gemini API]
    D --> H4[DeepSeek API]
    D --> H5[GLM / Zhipu API]
    D --> H6[OpenRouter API]
    D --> I[Local LLM / Ollama]
    D --> J[ML Models]
    
    E --> K[Parallel Processor]
    F --> L[Report Generator]
    
    SOC --> S1[Splunk HEC/Search API]
    SOC --> S2[IBM QRadar Ariel API]
    SOC --> S3[Elasticsearch Query DSL]
    SOC --> S4[Webhook Alerts]
    
    K --> M[Celery Workers]
    M --> N[Redis Queue]
    
    B --> O[PostgreSQL]
    B --> P[Redis Cache]
    
    Q[Prometheus] --> R[Grafana]
    S[Elasticsearch] --> T[Kibana]

Loading

Service Stack

🔧 Configuration

Enterprise Configuration (config.ini)

The configuration file supports 200+ options across multiple categories:

[app]
debug = false
environment = production
max_sessions = 100

[database]
url = postgresql://secscan_ai:secscan_ai123@localhost:5432/secscan_ai
pool_size = 20
backup_enabled = true

[ai]
default_model = gpt-5
default_provider = 
openai_api_key = your_key_here
anthropic_api_key = your_key_here
google_api_key = your_key_here
enable_local_fallback = true
confidence_threshold = 0.8

[security]
secret_key = your_secret_here
jwt_algorithm = HS256
rate_limit_enabled = true

[ldap]
server = ldaps://your-ldap-server.com:636
bind_dn = cn=admin,dc=example,dc=com

[compliance]
frameworks = OWASP,NIST,ISO27001,SOC2,PCI-DSS
auto_compliance_check = true

[cloud]
docker_host = unix:///var/run/docker.sock
service_registry_backend = consul

Environment Variables (.env)

Over 100 environment variables for enterprise deployment:

# Core Services
DATABASE_URL=postgresql://secscan_ai:secscan_ai123@localhost:5432/secscan_ai
REDIS_URL=redis://localhost:6379/0

# AI Configuration — Multi-Provider
SECSCAN_AI_MODEL=gpt-5              # (SECSCAN_AI_MODEL also supported)               # Any model from ai_engine/model_registry.py
OPENAI_API_KEY=your_openai_api_key
ANTHROPIC_API_KEY=your_anthropic_api_key
GOOGLE_API_KEY=your_google_api_key
DEEPSEEK_API_KEY=your_deepseek_api_key
GLM_API_KEY=your_glm_api_key
OPENROUTER_API_KEY=your_openrouter_api_key
ORCAROUTER_API_KEY=your_orcarouter_api_key
LOCAL_LLM_ENDPOINT=http://localhost:11434

# Security
SECRET_KEY=your_secret_key
JWT_SECRET_KEY=your_jwt_secret
LDAP_SERVER=ldaps://your-ldap.com:636

# Cloud Providers
AWS_ACCESS_KEY_ID=your_aws_key
AZURE_SUBSCRIPTION_ID=your_azure_id
GCP_PROJECT_ID=your_gcp_project

# Monitoring
PROMETHEUS_ENDPOINT=http://localhost:9090
GRAFANA_API_KEY=your_grafana_key
ELASTICSEARCH_ENDPOINT=http://localhost:9200

🎯 Enterprise Penetration Testing

Enhanced 6-Phase Methodology

Phase 1: Intelligence Gathering & Reconnaissance

Enterprise Features:

• AI-powered OSINT automation
• Multi-source data aggregation
• Threat intelligence correlation
• Cloud asset discovery (AWS, Azure, GCP)
• Tools: theHarvester, Amass, Subfinder, Shodan API

Phase 2: Advanced Scanning & Enumeration

Enterprise Features:

• Parallel distributed scanning
• Service fingerprinting with ML classification
• Vulnerability correlation across assets
• Zero-day pattern detection
• Tools: Nmap, Masscan, Nuclei, HTTPx, Naabu

Phase 3: Vulnerability Assessment

Enterprise Features:

• CVSS v3.1 automated scoring
• Business impact analysis
• Exploit availability assessment
• Compliance framework mapping
• Tools: OpenVAS, Nexpose integration, custom scanners

Phase 4: Exploitation & Post-Exploitation

Enterprise Features:

• Safe-mode exploitation with approval workflows
• Privilege escalation enumeration
• Lateral movement mapping
• Data exfiltration simulation
• Tools: Metasploit, CrackMapExec, BloodHound, custom exploits

Phase 5: Enterprise Reporting & Analytics

Enterprise Features:

• Executive dashboard with KPIs
• Technical vulnerability details
• Compliance gap analysis
• Risk prioritization matrix
• Outputs: HTML, PDF, JSON, XML, compliance reports

Phase 6: Verification & Retesting

Enterprise Features:

• Automated remediation verification
• Regression testing for fixes
• Continuous security monitoring
• Trend analysis and metrics
• Features: Scheduled retests, delta reporting

📊 Enterprise Interfaces

1. Command Line Interface (CLI)

# Interactive enterprise mode
python3 advance_secscan_ai.py

# Available options:
# 1. Full Enterprise Pentest (All 6 Phases)
# 2. Run Specific Phase
# 3. Custom Assessment Workflow
# 4. View Reports & Analytics
# 5. Real-time Dashboard
# 6. User & Permission Management
# 7. System Configuration
# 8. Compliance Management
# 9. Cloud & Container Management
# 10. AI Engine Configuration

2. REST API Server

# Start API server
python3 advance_secscan_ai.py --api

# Available endpoints:
# GET  /api/health - Health check
# POST /api/pentest/start - Start assessment
# GET  /api/sessions - List sessions
# GET  /api/reports/{id} - Get report
# POST /api/users - User management
# GET  /api/compliance - Compliance status

3. Web Dashboard

# Start web dashboard
python3 advance_secscan_ai.py --web

# Features:
# - Real-time assessment monitoring
# - Interactive vulnerability management
# - Executive summary dashboard
# - User and role management
# - System configuration
# - Compliance reporting

4. Voice Commands (Enterprise)

# Voice command mode
python3 advance_secscan_ai.py --voice

# Supported commands:
# "Start enterprise assessment of example.com"
# "Show compliance dashboard"
# "Generate executive report"
# "Scale worker pool to 10"

5. Threat Intelligence & Automated Attack Graph Chaining

# Look up CVE threat intelligence & EPSS exploit probability
python3 advance_secscan_ai.py --cve-lookup CVE-2021-44228

# Synthesize automated multi-stage attack graph and identify defensive chokepoints
python3 advance_secscan_ai.py --attack-chain

# Export Mermaid flowchart syntax for visualization in documentation & PRs
python3 advance_secscan_ai.py --mermaid

# Display MITRE D3FEND defensive countermeasure matrix
python3 advance_secscan_ai.py --d3fend-matrix

# Export Detection-as-Code (Sigma Rules YAML & Splunk SPL queries)
python3 advance_secscan_ai.py --export-sigma

# Generate automated Ansible & Bash hardening playbooks
python3 advance_secscan_ai.py --export-ansible

6. AI Red Teaming & LLM Security Assessment (OWASP LLM Top 10)

# Execute automated adversarial red team probes against configured LLM model
python3 advance_secscan_ai.py --llm-redteam

# Test specific model endpoint with custom route
python3 advance_secscan_ai.py --llm-redteam --model gpt-4o --custom-route http://localhost:8080/v1

7. API Security Assessment & OpenAPI Audit (OWASP API Top 10)

# Execute API Security scan using benchmark microservice spec
python3 advance_secscan_ai.py --api-scan

# Audit custom OpenAPI / Swagger spec file (JSON or YAML)
python3 advance_secscan_ai.py --api-scan path/to/openapi.yaml

8. Cloud & Kubernetes Security Posture Management (CSPM / KSPM / IaC Audit)

# Execute benchmark multi-cloud CSPM & KSPM assessment (AWS, Azure, GCP, Kubernetes)
python3 advance_secscan_ai.py --cspm-scan

# Audit specific Terraform IaC directory or Kubernetes manifest path
python3 advance_secscan_ai.py --cspm-scan path/to/terraform/

# Execute dedicated Kubernetes Security Posture Management (KSPM) audit
python3 advance_secscan_ai.py --k8s-audit

# Export automated CLI and IaC hardening remediation script
python3 advance_secscan_ai.py --cspm-scan --export-cloud-fix cloud_hardening.sh

🔐 Enterprise Security

Authentication & Authorization

• Multi-Factor Authentication: LDAP/AD + JWT tokens
• Role-Based Access Control: Granular permissions matrix
• Session Management: Secure session handling with timeout
• API Security: Rate limiting, CORS, input validation

Data Protection

• Encryption: AES-256-GCM for data at rest
• Transport Security: TLS 1.3 for data in transit
• Key Management: Automated key rotation
• Audit Logging: Comprehensive activity tracking

Compliance Frameworks

📈 Monitoring & Analytics

Real-Time Monitoring

• System Metrics: CPU, memory, disk, network utilization
• Application Metrics: Request rates, response times, error rates
• Security Metrics: Vulnerability counts, risk scores, remediation rates
• Business Metrics: Assessment coverage, compliance scores

Alerting

• Email Alerts: Critical vulnerabilities, system issues
• Slack Integration: Real-time notifications to security teams
• Webhook Support: Custom integrations with SIEM systems
• Dashboard Alerts: Visual indicators and notifications

Analytics Dashboard

# Access Grafana dashboard
http://localhost:3000
# Login: admin / secscan_ai123

# Pre-configured dashboards:
# - SecScan AI System Overview
# - Assessment Performance Metrics  
# - Vulnerability Trend Analysis
# - User Activity Dashboard
# - Compliance Status Overview

🛠️ Advanced Usage

Multi-Provider AI Models

from ai_engine import get_advanced_ai_engine, list_all_models, get_available_providers
# Initialize with a specific model
engine = get_advanced_ai_engine(model_id='claude-sonnet-5')

# Switch models at runtime
engine.set_model('gemini-3.5-flash')

# List all 26+ available models
for model in engine.list_available_models():
    status = "✅" if model['available'] else "❌"
    print(f"{status} {model['display_name']} ({model['provider']})")

# Check available providers
for provider in get_available_providers():
    print(f"{provider['name']}: {provider['model_count']} models")

OrcaRouter Cyber Inference

OrcaRouter is an OpenAI-compatible gateway for authorized security teams. It routes scoped security reasoning to the OrcaCyber models and carries the gateway's blue-team controls on the same endpoint. Select the orcarouter provider (base URL https://api.orcarouter.ai/v1) and set ORCAROUTER_API_KEY, or [ai] orcarouter_api_key in config.ini.

• Recommended default: orca/orcacyber-ultra-1.0 (OrcaCyber Ultra); orca/orcacyber-zero-1.5 is the harness-driven alternative. Both require the cyber tier to be unlocked for your workspace during business verification.
• When the cyber tier is not unlocked, use orcarouter/fusion.
• Provider page: https://www.orcarouter.ai/cyber
• Cyber model catalog: https://www.orcarouter.ai/models?tier=cyber

The dashboard's AI Providers view accepts the key and loads models from the live GET https://api.orcarouter.ai/v1/models?capability=chat catalog.

Custom Compliance Frameworks

# Add custom compliance framework
from security.compliance import ComplianceFrameworkMapper

mapper = ComplianceFrameworkMapper()
mapper.add_framework('CUSTOM', {
    'sql_injection': 'SEC-01',
    'xss': 'SEC-02',
    # ... custom mappings
})

Kubernetes Deployment

# Deploy to Kubernetes cluster
kubectl apply -f k8s/

Multi-Cloud Deployment

# Deploy to AWS
python3 advance_secscan_ai.py --deploy aws

# Deploy to Azure  
python3 advance_secscan_ai.py --deploy azure

# Deploy to GCP
python3 advance_secscan_ai.py --deploy gcp

🧪 Testing & Development

Running Tests

# Unit tests
pytest tests/unit/

# Integration tests  
pytest tests/integration/

# End-to-end tests
pytest tests/e2e/

# Security tests
bandit -r .
safety check

Development Setup

# Install development dependencies
pip install -r requirements-dev.txt

# Pre-commit hooks
pre-commit install

# Code formatting
black .
flake8 .
mypy .

📦 Enterprise Deployment

Docker Swarm

# Initialize swarm
docker swarm init

# Deploy stack
docker stack deploy -c docker-compose.yml secscan_ai

Kubernetes

# Create namespace
kubectl create namespace secscan_ai

# Deploy applications
kubectl apply -f k8s/

# Scale workers
kubectl scale deployment secscan_ai-worker --replicas=10

Cloud Platforms

AWS Deployment

# ECS deployment
aws ecs create-cluster --cluster-name secscan_ai
aws ecs create-service --service-name secscan_ai-api

Azure Deployment

# ACI deployment
az container create --resource-group secscan_ai --name secscan_ai-api

GCP Deployment

# GKE deployment
gcloud container clusters create secscan_ai-cluster
kubectl apply -f k8s/

🔧 Troubleshooting

Common Enterprise Issues

Database Connection Issues

# Check PostgreSQL status
systemctl status postgresql
docker logs secscan_ai-database

# Test connection
python3 -c "from database import get_db_manager; print(get_db_manager().test_connection())"

Redis Cache Issues

# Check Redis status
redis-cli ping
docker logs secscan_ai-redis

# Clear cache
redis-cli FLUSHALL

AI Engine Issues

# List available AI models and providers
python3 -c "from ai_engine import list_all_models; [print(m.display_name, m.provider.value) for m in list_all_models()]"

# Test provider connectivity
python3 -c "from ai_engine.providers import ProviderFactory; print(ProviderFactory.get_available_providers())"

# Check local LLM (Ollama)
ollama list
ollama run llama3.3:70b

Worker Pool Issues

# Check Celery workers
celery -A performance.parallel_processor inspect active

# Restart workers
docker-compose restart secscan_ai-worker

Performance Optimization

# Database optimization
python3 -c "from database import optimize_database; optimize_database()"

# Cache warming
python3 -c "from performance.cache_manager import warm_cache; warm_cache()"

# Worker scaling
docker-compose up --scale secscan_ai-worker=10

📄 Enterprise License

This project is licensed under the MIT License with additional enterprise terms:

• Commercial Use: Permitted with attribution
• Enterprise Support: Available through support channels
• Compliance: Tool usage must comply with applicable laws
• Liability: Limited liability for enterprise deployments

🆘 Enterprise Support

Support Channels

• Enterprise Support: yashabalam707@gmail.com
• Technical Issues: https://github.com/najafdev/secscan_ai/issues
• Feature Requests: https://github.com/najafdev/secscan_ai/discussions
• Security Issues: yashabalam707@gmail.com
• WhatsApp Business: Join Channel

Professional Services

• Implementation: Custom deployment and configuration
• Training: Security team training and certification
• Custom Development: Feature development and integration
• 24/7 Support: Enterprise support packages available

Connect with the Team

• Yashab Alam: GitHub | Instagram | LinkedIn

📊 Project Statistics

🗺️ Roadmap

Version 2.1 (Q3 2025)

• Multi-provider AI support (OpenAI, Anthropic, Google, DeepSeek, GLM, Local, OpenRouter)
• 26+ model catalog with runtime switching
• Provider fallback chain and automatic detection
• ML-based false positive reduction
• Integration with popular SIEM systems

Version 2.2 (Q4 2025)

• Streaming responses from all providers
• Automated penetration testing workflows
• Advanced cloud security assessments
• Integration with CI/CD pipelines

Version 3.0 (Q1 2026)

• Fully autonomous security assessments
• Advanced AI attack simulation
• Quantum-safe cryptography
• Next-generation threat detection

🙏 Contributors

Core Development Team

• Lead Developer & Founder: Yashab Alam - @yashab.alam | LinkedIn

• AI/ML Engineer: Enterprise AI Team

• Security Engineer: Enterprise Security Team

• DevOps Engineer: Enterprise Infrastructure Team

• 💬 WhatsApp: Business Channel

Acknowledgments

• OpenAI for GPT-5 and o-series API access
• Anthropic for the Claude model family
• Google DeepMind for Gemini models
• DeepSeek, Zhipu AI (GLM), and OpenRouter
• Ollama team for local LLM support
• Docker & Kubernetes communities
• Security research community
• Open source tool developers

💰 Support SecScan AI Development

Your support accelerates development, research infrastructure, and frontier AI model integrations:

• 🪙 Cryptocurrency Donations: For transfers (Solana, Bitcoin, Ethereum, USDT, etc.), please email sai466769@gmail.com
• 📄 Full Sponsorship & Donation Guide: See DONATE.md for tier perks, transparency reports, and roadmap goals

⚖️ Legal & Compliance

⚠️ IMPORTANT LEGAL NOTICE

SecScan AI Enterprise is designed for authorized security testing only:

• ✅ Authorized Use: Only use against systems you own or have explicit written permission
• ✅ Compliance: Follow all applicable laws, regulations, and industry standards
• ✅ Responsible Disclosure: Report vulnerabilities through proper channels
• ✅ Documentation: Maintain audit trails and documentation
• ❌ Unauthorized Use: Never use against systems without permission
• ❌ Malicious Activity: Not for criminal or malicious purposes

The developers and contributors are not liable for misuse of this platform.

🔗 Connect with Yashab Alam