AI-Driven Cybersecurity Services
Secneural delivers end-to-end AI-driven cybersecurity services to help enterprises adopt and defend AI responsibly. Our offerings span AI security strategy, governance, threat simulations, SOC automation, deepfake risk management, and data privacy compliance
AI Security Strategy & Readiness
Most organizations adopt AI without formal governance. This leads to regulatory exposure, shadow AI usage, and unmanaged data risks. Secneural provides a structured strategy to align AI with enterprise goals, compliance, and security frameworks.
Challenges Addressed
- Lack of visibility over AI projects (shadow AI)
- Absence of acceptable-use and risk policies for AI
- No alignment of AI initiatives with cybersecurity and business objectives
- Inability to quantify AI risk at an executive level
Methodology
- Phase 1 : Discovery & Assessment: Stakeholder workshops, inventory of AI initiatives, mapping data flows and regulations.
- Phase 2 : AI Governance Framework Design: Policies aligned to ISO/NIST, accountability model, incident response.
- Phase 3 : Roadmap & Implementation Playbook: Prioritize initiatives, phased roadmap, dashboards and metrics.
Deliverables
- AI security policy suite and governance handbook
- AI risk register with scoring methodology
- 12–24 month roadmap for secure AI adoption
- Board-level reporting template
AI Risk & Governance (AIGRC)
Challenges Addressed
- AI security policy suite and governance handbook
- AI risk register with scoring methodology
- 12–24 month roadmap for secure AI adoption
- Board-level reporting template
Methodology
- Phase 1 : Discovery & Assessment: Stakeholder workshops, inventory of AI initiatives, mapping data flows and regulations.
- Phase 2 : AI Governance Framework Design: Policies aligned to ISO/NIST, accountability model, incident response.
- Phase 3 : Roadmap & Implementation Playbook: Prioritize initiatives, phased roadmap, dashboards and metrics.
Deliverables
- AI control library with mapped frameworks
- Continuous AI risk dashboard integrated with GRC
- Audit-ready evidence packs
- Governance committee playbooks
AI Threat Simulation & Red Teaming
Threat actors increasingly weaponize AI. Organizations need proactive testing against AI-enabled attack
vectors to validate defenses.
Challenges Addressed
- Lack of awareness of AI-specific attack scenarios
- Inability to test defenses against prompt injection, model theft, or AI-driven phishing
- No framework to measure readiness for AI-based threats
Methodology
- Phase 1 : Threat Modeling & Attack Surface Mapping: Identify AI components, analyze attack surfaces.
- Phase 2 : Adversarial Testing & Simulation: Prompt injection, jailbreaks, deepfake scenarios.
- Phase 3 : Remediation & Retest: Mitigation strategies, validation, updated IR plans.
Deliverables
- Red team report with technical findings
- Deepfake and AI-phishing resilience scorecard
- Updated SOC and IR playbooks for AI threats
AI-Powered SOC & Threat Intelligence
Challenges Addressed
- High false positives and slow incident triage
- Lack of threat intel on AI-driven TTPs
- No AI playbooks for SOC workflows
Methodology
- Phase 1 :SOC Workflow Assessment: Identify pain points, review detection coverage.
- Phase 2 : AI Integration & Playbooks: Deploy AI copilots for automation, enrichment.
- Phase 3 :AI-Specific Threat Intelligence: Monitor and ingest AI-enabled attack TTPs.
Deliverables
- AI-powered SOC automation runbooks
- False positive reduction KPIs
- Threat intel reports for AI adversary tactics
Deepfake & Synthetic Media Risk Management
Overview & Business ContextDeepfake fraud and misinformation campaigns threaten brands, executives, and critical infrastructure.
Challenges Addressed
- Lack of detection capabilities for AI-generated audio/video/image content
- No executive protection from impersonation
- No incident response playbooks for synthetic media
Methodology
- Phase 1 :Risk Assessment & Threat Monitoring: Evaluate exposure, deploy monitoring.
- Phase 2 : Detection & Response Pipeline: Deploy forensic detection tools, liveness checks.
- Phase 3 :Awareness & Legal Support: Awareness campaigns, takedown coordination.
Deliverables
- Synthetic media detection dashboards
- Executive protection protocols
- Fraud reduction and improved brand trust
AI Data Privacy & Compliance
Challenges Addressed
- No privacy impact assessments for AI projects
- Poor data minimization and retention policies
- Cross-border data transfer risks
Methodology
- Phase 1 :Cross-border data transfer risks
- Phase 2 : Technical & Organizational Measures: Encryption, anonymization, retention.
- Phase 3 :Technical & Organizational Measures: Encryption, anonymization, retention.
Deliverables
- Audit-ready privacy reports for AI projects
- Reduced regulatory exposure
- Ongoing compliance monitoring
Why Secneural?
Holistic AI Security Expertise: Deep specialization in AI risk, compliance, and cyber defense; beyond generic IT security services.
For further details,
contact our team
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Secneural Cyber Security Consulting company. Secneural helps organizations reduce their attack exposure by providing an effortless cybersecurity services.
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