Web Application
Testing
Identify OWASP Top 10 and business logic flaws.
Home › Solutions › AI Cybersecurity
AI CYBERSECURITY SERVICES
Traditional security tools were built for traditional software.
EXPLOIT BEFORE ATTACKERSREAL-WORLD ATTACK SIMULATIONAI-POWERED ANALYSISDEEP VULNERABILITY INSIGHTS
Site Information
Real-World Attack SimulationSimulate advanced threats across your entire environment.
AI-Driven Threat DetectionLeverage AI to detect and predict attack paths.
Certified Security ExpertsWork with industry-leading ethical hackers.
Detailed Reports & RemediationClear findings with actionable steps to fix vulnerabilities.
Why Choose Our
AI Cybersecurity Services?
Modern attacks move quickly and generate complex signals. We combine expert security testing with AI-assisted analysis to identify meaningful risks, validate findings and improve defensive readiness.
✓Identify real-world security risks
✓Leverage AI for advanced threat detection
✓Test networks, applications, cloud and APIs
✓Receive clear, actionable reports
✓Keep your business compliant and secure
Our AI Cybersecurity Testing Process
A comprehensive, AI-enhanced approach to discover, validate, prioritize and remediate security risks.
01Planning &
ReconnaissanceUnderstand your environment and define the scope.
ReconnaissanceUnderstand your environment and define the scope.
02Vulnerability
ScanningUse AI-powered tools to detect security gaps across all systems.
ScanningUse AI-powered tools to detect security gaps across all systems.
03Exploitation &
Attack SimulationSimulate real-world attacks to validate vulnerabilities.
Attack SimulationSimulate real-world attacks to validate vulnerabilities.
04Analysis &
ReportingProvide detailed findings with risk prioritization.
ReportingProvide detailed findings with risk prioritization.
05Remediation
SupportGuide your team with step-by-step fix recommendations.
SupportGuide your team with step-by-step fix recommendations.
Comprehensive AI Cybersecurity Services
We assess your digital environment using expert-led testing, intelligent analysis and proven security methodologies.
Web Application
Network Infrastructure
Testing
Find vulnerabilities in internal and external networks.
Mobile Application
Testing
Secure your iOS and Android applications.
Cloud Security
Testing
Assess AWS, Azure, Google Cloud and hybrid environments.
API Security
Testing
Detect and exploit API vulnerabilities.
Wireless Security
Testing
Identify risks in Wi-Fi networks and access points.
Social Engineering
Testing
Test human defenses against phishing and manipulation.
IoT & Embedded
Testing
Secure connected devices and embedded systems.
Site Information
500+Clients Protected
100M+Threats Analyzed Monthly
99.9%Vulnerability Detection Rate
24/7Security Expertise
Benefits of AI-Powered
Cybersecurity Testing
✓Proactive risk identification and mitigation
✓AI-enhanced accuracy and deeper insights
✓Reduced risk of data breaches and downtime
✓Compliance with industry standards (ISO 27001, SOC 2, HIPAA, GDPR)
✓Protection for your customers, brand and revenue
✓Peace of mind with continuous security improvement
OUR SERVICES AREA
AI Cybersecurity
Explore All Services →LLM Penetration Testing — OWASP LLM Top 10
Our expert ai cyber security engineers test all ten vectors adversarially — mapping every finding to a CVSS score, a risk tier, and sprint-ready remediation.
01
Prompt Injection & Jailbreaking
Adversarial input validation and HITL bypass testing
02
Sensitive Information Disclosure
PII exposure, API key leakage, model output data detection
03
Supply Chain Risk
Third-party model, plugin, and library dependency scanning
04
Data & Model Poisoning
Training data integrity verification and provenance tracking
05
Improper Output Handling
Sandbox escape simulation and guardrail bypass testing
06
Excessive Agency
Agentic workflow scope testing and least-privilege validation
07
System Prompt Leakage
Server-side prompt isolation and confidentiality verification
08
Model Theft Detection
Rate limiting, watermarking, anomaly detection
AI API Security Assessment
Your LLM may be solid in isolation. The APIs surrounding it often aren’t. REST endpoints, GraphQL layers, model-serving APIs, and inference gateways carry authorization flaws, injection vectors, and data exposure risks that standard DAST tools weren’t built to find.
01
Authentication & Authorization Testing
OAuth 2.0, API key management, mTLS validation
02
Prompt Injection via API
All external input channels that reach the model
03
Rate Limiting & Throttling
Model extraction defense, abuse prevention, DDoS resilience
04
Output Filtering Verification
Confirming guardrails hold at the API response layer
05
Third-Party Integration Risk
External data sources and vendor APIs feeding AI inference
Agentic AI Red Teaming
Agentic AI systems browse, execute code, query databases, and call external APIs — at machine speed, across your entire environment. A single misconfigured or compromised agent can cascade damage across every system it touches. Cyber Radar Systems is one of the only ai cybersecurity companies offering dedicated agentic AI red teaming.
01
Agent Privilege Escalation
RBAC and scoped access testing within agentic workflows
02
Tool Invocation Abuse
Simulating malicious or unintended API, tool, and database calls
03
Cross-Agent Communication Security
Lateral movement testing in multi-agent orchestration
04
Human-in-the-Loop Bypass
Verifying approval gates hold under adversarial pressure
05
Autonomous Action Scope
Confirming agents cannot exceed defined operational boundaries
RAG Pipeline Security
RAG systems connect your LLM to internal knowledge bases, document stores, and vector databases. That connection is an attack surface most teams haven’t mapped. Malicious documents inject instructions. Sensitive data leaks across sessions.
01
RAG Prompt Injection
Malicious document injection and instruction override testing
02
Unauthorized Knowledge Retrieval
Access control testing across vector database queries
03
Cross-Query Contamination
Session isolation and sensitive data bleed detection
04
Embedding Poisoning
Tampered vector data detection and retrieval manipulation testing
05
Data Leakage via RAG Output
PII and proprietary data exposure through generative output
Model Supply Chain Review
A compromised checkpoint, a malicious plugin, or an unvetted vendor integration can introduce backdoors and biases that survive into production undetected. Our ai cybersecurity certification consulting ensures your supply chain meets the compliance bar your auditors demand.
01
Model Provenance Assessment
Model origin and integrity assessment
02
Dependency Scanning
Review of model, plugin, and library dependencies
03
Vendor Security Assessment
Security review of third-party AI vendors
04
Behavioral Integrity Testing
Validation of model behavior and integrity
05
Data Provenance Tracking
Traceability of training and reference data
06
AI SBOM
AI-native software bill of materials documentation for audit and procurement
AI GOVERNANCE SERVICES
AI Governance
Most organizations treat AI governance as a documentation exercise. A policy binder in SharePoint isn’t governance — it’s a filing system. Real governance controls how AI gets approved, deployed, monitored, and retired across every team and system in your organization, and it produces audit evidence that satisfies regulators when they come asking.
EU AI Act penalties reach €35 million or 7% of global annual turnover. The SEC elevated AI governance to a 2026 examination priority. Cyber insurance underwriters now require documented AI controls before they’ll quote. Hire our experienced ai governance professional team before the inquiry lands, not after it does.
Compliance & Standards
AI governance requirements and audit readiness across leading standards.
ISO/IEC 42001
AI Management System audit readiness and certification consulting, Annex A control domains
NIST AI RMF
Govern, Map, Measure, Manage lifecycle implementation with deliverables at each phase
EU AI Act
High-risk AI system classification, prohibited use assessment, conformity preparation
SOC 2 AI Control Coverage
AI-specific control design for Type II attestation
GDPR & HIPAA AI Requirements
Lawful basis for AI processing, data minimisation, explainability, and patient data protection controls within AI-powered clinical systems
What AI Governance Looks Like in Practice
AI Governance Committee
Committee structure, charter, operating cadence, and RACI design
AI Use Case Registry
Inventory and risk-tier classification of all AI deployments
Model Approval Workflow
Intake, risk-gating, documentation, and sign-off process
AI Acceptable Use Policy
Sanctioned AI use, prohibited applications, Shadow AI controls
Governance Dashboard
Real-time visibility into governance compliance status
Frameworks, Bias Auditing & Vendor Governance
Our cyber threat intelligence services aligned with MITRE ATT&CK integrate directly into your governance risk controls. We work with NIST AI RMF 1.0, ISO/IEC 42001, the EU AI Act, MITRE ATLAS, OECD AI Principles, and ISO 27001 Integration.
Responsible AI Principles
Fairness, accountability, transparency, explainability policy design
AI Ethics Review Board
Charter, composition, decision authority, escalation process
Demographic Fairness Testing
Disparate impact analysis across protected groups
Output Bias Monitoring
Continuous production monitoring for model drift and bias creep
Contractual AI Protections
AI-specific SLA terms, data handling obligations, indemnification
AI Incident Response & AI Cybersecurity Certification (ISO 42001)
AI Incident Response Playbook
Scenario-specific plans for prompt injection, model failure, data exposure, and agent misbehaviour
Tabletop Simulation Exercises
Practice AI incident scenarios and response coordination
SIEM / SOC Integration
Connect AI incident response to security operations
ISO/IEC 42001 Gap Assessment
Evaluate readiness for AI management system certification
Certification Roadmap
30/60/90-day path to ai security certification audit readiness
Real-World Success Stories
See how we've helped businesses strengthen their security and prevent cyber threats.
Financial Services Company
Identified critical vulnerabilities in their web application, preventing a potential data breach.
Result: 90% reduction in critical risks
Healthcare Provider
Discovered exposed patient data in cloud storage and helped secure their environment.
Result: Full HIPAA compliance
E-Commerce Business
Detected API vulnerabilities and prevented unauthorized access to customer data.
Result: Stronger API security & customer trust
OUR AI RISK MANAGEMENT SERVICES
AI Risk Management
Most organisations discover their AI risk the wrong way. During a regulatory inquiry. After a model failure that made headlines. Cyber Radar Systems implements structured AI risk management programs built on NIST AI RMF 1.0 and ISO/IEC 42001, giving you continuous visibility across model risk, data risk, operational risk, regulatory risk, security risk, and third-party AI risk.
AI RISK MANAGEMENT
Our AI Risk Management Process
Identify AI Use Cases → Assess Threats & Vulnerabilities → Determine Likelihood & Impact → Calculate Risk Score (CVSS-aligned) → Evaluate Existing Controls → Mitigate Identified Risks → Monitor & Review.
Identify AI Use Cases
Catalog AI deployments and uses.
Assess Threats & Vulnerabilities
Evaluate threats and vulnerabilities.
Determine Likelihood & Impact
Assess likelihood and business impact.
Calculate Risk Score
CVSS-aligned risk scoring.
Evaluate Existing Controls
Review safeguards and controls.
Mitigate Identified Risks
Plan and apply risk treatment.
Monitor & Review
Continuously monitor and reassess.
Risk categories assessed in every cycle: Security · Privacy · Compliance · Ethical · Operational · Financial · Legal · Reputational.
MODEL & DATA ASSURANCE
Model Risk, Data Risk & Regulatory Risk
Continuous assessment of model quality, data provenance and regulatory obligations.
Model Performance Validation
Accuracy, precision, recall, F1, and reliability benchmarking
Hallucination Rate Assessment
Output fabrication frequency testing and mitigation design
Model Drift Detection
Production monitoring for performance degradation and concept drift
SR 11-7 / MRMG Alignment
Model risk management alignment for regulated financial institutions
Training Data Provenance
Origin, consent, integrity, and lineage verification
Regulatory Mapping & Audit Evidence Packages
Jurisdiction and sector-specific AI obligation identification, with documentation bundles aligned to each framework
CONTINUOUS THIRD-PARTY ASSURANCE
Third-Party AI Risk, Risk Register & Continuous Monitoring
20-Point Vendor Risk Assessment (NIST AI RMF and ISO 42001 aligned) · Model Transparency Review · Continuous Vendor Monitoring · AI Risk Register Design — structured risk catalog with likelihood, impact, ownership, and status · Continuous AI Monitoring — SIEM integration, model drift detection, bias monitoring · Quarterly Risk Register Reviews.
Talk to an AI Security Engineer Now → 30 Minutes. One Call. No Commitment.Frequently Asked Questions
What is penetration testing?
Penetration testing is a simulated cyber attack against your systems, networks, applications or cloud environment to identify security vulnerabilities before real attackers can exploit them.
How does AI improve penetration testing?
AI-assisted analysis helps correlate findings, identify attack paths and prioritize risks while expert testers validate meaningful weaknesses.
How often should we conduct penetration testing?
Frequency depends on your risk, compliance needs and rate of change. Many organizations test annually and after major changes.
Do you provide remediation support?
Yes. Findings include prioritized remediation guidance, with retesting available to validate fixes.
Which compliance standards do you cover?
Testing can support objectives associated with ISO 27001, SOC 2, HIPAA, PCI DSS and other security requirements.