Cybersecurity Analytics

Cybersecurity Analytics Services

Expert in Cyber Defense, Risk Management, and AI Implementation

Risk assessment and management

  • Identification and assessment of technological risks
  • Development of risk mitigation strategies
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Compliance and regulatory services

  • Assistance with regulatory compliance (e.g., GDPR, DORA, ISO, HIPAA)
  • Internal audits and assessments
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IT management

  • Development of an IT management framework
  • Development of policies and procedures
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Business continuity and disaster recovery planning

  • Impact analysis on operations
  • Development of recovery strategies and plans
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Third-party risk management

  • Supplier risk assessment
  • Continuous monitoring of relationships with third parties
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Access Governance and Compliance

  • Identity & access risk assessment (IAM)
  • Defining IAM policies within IT governance
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Governance and policy

  • Data protection framework, roles (DPO, data owners) and approval workflows
  • Privacy KPIs and regular governance reviews
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Data inventory and classification

  • Automated discovery of PII and business data across systems
  • Classification labels and data flow mapping (storage, processors, transfers)
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Technical safeguards

  • Encryption at rest and in transit with centralized key management
  • Access controls (RBAC, MFA) and DLP for endpoints, email and cloud
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Privacy by design and lifecycle

  • DPIAs for high-risk processing and privacy controls in development
  • Retention schedules, archival procedures and secure deletion
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Third party and contracts

  • Standardized DPAs/SCCs and records of processing
  • Vendor risk assessments and audit tracking
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Monitoring, training and incident readiness

  • Logging, anomaly alerts and audit trails for sensitive data access
  • Role-based privacy training and breach response playbooks
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Developing an AI strategy

  • Assessing business needs and AI capabilities
  • Creating a roadmap for AI adoption
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Data strategy and management

  • Data collection, cleaning, and preparation
  • Data management and quality assurance
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Development and implementation of models

  • Building machine learning models
  • Implementation and integration of AI solutions
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AI ethics and compliance

  • Ensuring ethical AI practices
  • Compliance with AI regulations and standards
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Training and support

  • Staff training in AI tools and technologies
  • Ongoing support and maintenance of AI systems
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Intelligent IAM Services

  • Access policies for AI models
  • Data access control (RBAC/ABAC)
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Strategy

  • Mapping business value with approval criteria
  • Acceptable use policies and decision-making processes
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Data

  • Data provenance and pattern identification
  • PII removal, synthetic data
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Model selection

  • Vendor/model due diligence: licenses, security
  • Decision criteria for on-prem vs cloud deployment, cost considerations
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Safety and ethics

  • Noncompliance tests with documented remediation steps
  • Content safety filters, ethically aligned standards
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MLOps and monitoring

  • Definition of models, CI/CD, tests and deployment gates
  • Performance monitoring, drift detection and rollback procedures
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Security and incident response

  • Protection against prompt injection, model inversion, and data poisoning
  • Access controls, comprehensive logging, and an incident response playbook for models
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Risk analysis

  • Monitoring and analysis of threat landscapes
  • Vulnerability assessments
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Safety awareness training

  • Employee training programs on cybersecurity best practices
  • Phishing simulations
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Security Operations Center (SOC) Services

  • 24/7 security event monitoring and management
  • Security information and event management (SIEM)
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Response to incidents

  • Incident detection and analysis
  • Containment, elimination, and recovery
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Penetration tests

  • External and internal penetration testing
  • Web application security testing
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Secure Identity Lifecycle Management

  • Identity & access risk analysis
  • SOC monitoring of IAM events
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Scoping and asset discovery

  • Inventory of hosts, applications, containers, and cloud resources
  • Attack surface mapping: public IPs, exposed APIs, and third-party integrations
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Automated scanning

  • Regular authenticated and unauthenticated network and host scans
  • CSPM controls and vulnerability scanning of images and containers
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Penetration testing

  • External and internal pentests with proof-of-concept and remediation guidance
  • Web application and API testing for OWASP Top 10, business logic, and authentication flaws
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Risk scoring and prioritization

  • Contextual risk scoring combining CVSS with business impact
  • Remediation lists and standard remediation playbooks
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Verification and validation

  • Retesting after fixes and validation of closure
  • Integration of scanning into CI/CD pipelines for shift‑left validation
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Reporting and metrics

  • Executive summaries for the board and technical appendices with KPIs (remediation time, open‑vulnerability trend)
  • Patch management scheme, quarterly asset reviews
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