AI Security
Solutions
AI is now embedded in core business operations, reshaping how organisations serve customers, make decisions, and compete. This shift introduces security exposures that traditional controls were not built to address. Risks cut across applications, identity, and data at once, and a single compromise can affect model integrity, customer trust, and compliance in one event.
Securing AI is complicated by pace. New models, agent frameworks, and integrations arrive faster than security teams can assess them, while shadow AI usage spreads ahead of governance. Adversaries now exploit weaknesses above Layer 7, including prompt injection, model poisoning, data leakage through vector stores, and misuse of agent tools. In parallel, the UAE AI Governance Policy, EU AI Act, ISO/IEC 42001, and NIST AI RMF are raising the bar boards and regulators expect organisations to meet.
GBM Shield secures AI across the full lifecycle through six connected practices, from strategy to runtime. Aligned with OWASP LLM and Agentic Top 10, ISO/IEC 42001, NIST AI RMF, and the UAE AI Governance Policy, we help organisations move from ad-hoc AI adoption to a governed, defensible posture, backed by regional expertise across the GCC.
AI SECURITY
AI INTERFACE SHIELD
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API Discovery
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API Protection
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MCP Protection
AI IDENTITY AND ACCESS MANAGEMENT
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Human and Agent Identity
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Fine Grained Authorization
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Traceability & Zero Trust
RUN TIME SECURITY & MONITORING
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AI Guardrail
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AI Detection and Response
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AI Automated Red Teaming
AI STRATEGY, RISK & GOVERNANCE
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Secure AI Architecture & Engineering
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AI Risk & Security Assurance
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Responsible AI Readiness & Compliance
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Enterprise AI Governance Framework
DATA SECURITY & PRIVACY
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DSPM
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Data Encryption
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Data Masking and Tokenization
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Data Classification
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Privacy Enhancing Technologies
MODEL SECURITY
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Model Scanner
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Adversarial Testing & Validation
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Model Lifecycle Governance
AI Strategy, Risk & Governance
Ungoverned AI exposes organisations to risks they cannot see or explain. AI Strategy, Risk & Governance sets the policies, ownership, and lifecycle controls that keep AI initiatives accountable and audit-ready. It covers lifecycle governance, AI risk management, and compliance mapping to ISO/IEC 42001, NIST AI RMF, the EU AI Act, and the UAE AI Governance Policy, giving leadership the confidence to approve, scale, or retire AI use cases.
AI Interface Shield
Traditional network and application security stops at Layer 7, while AI risk lives at the semantic layer where prompts, responses, and tool calls carry the payload. AI Interface Shield inspects and controls AI traffic in real time, blocking prompt injection, data leakage, malicious tool invocation, and Model Context Protocol (MCP) abuse. It covers API discovery across sanctioned and shadow AI, API security for LLM and agent traffic, and MCP protection for agentic tool-calling.
AI Identity & Access Management
Legacy IAM was built for human users and static applications. It struggles when AI agents outnumber employees and act at machine speed. AI Identity & Access Management extends identity to non-human actors, assigning each agent a governed identity with fine-grained authorization and zero-trust enforcement. It covers human and agent identity, tool-level authorization, and full traceability, so every autonomous action can be attributed, reviewed, and, where needed, reversed.
Data Security & Privacy
AI systems are only as trustworthy as the data behind them, and that data is also their primary attack surface. Data Security & Privacy protects sensitive information across the AI lifecycle, from training data to prompts and vector store access. It covers DSPM, encryption, masking and tokenization, classification, and privacy-enhancing technologies, supporting compliance with GDPR, UAE PDPL, and sector-specific data obligations across the GCC.
Model Security
Models are software artefacts with their own supply chain, carrying risks that traditional application security tools were not built to detect. Model Security protects model integrity from development through deployment, addressing backdoored public models, adversarial input manipulation, and model theft or extraction. It covers model scanning, watermarking for provenance, adversarial testing before release, and lifecycle governance across model versions.
Runtime Security & Monitoring
AI systems behave differently every time they run, so static controls are not enough. Runtime Security & Monitoring provides continuous protection in production, with inline guardrails on prompts and responses, behavioural detection and response on model and agent activity, and automated red-teaming against evolving OWASP LLM and Agentic AI threats. It keeps AI systems inside their intended operating envelope and gives SOC teams the telemetry to investigate and contain incidents.
Key Features of AI Security
Six connected practices secure AI from strategy and governance through to runtime, covering models, agents, data, and identities.
Full-Lifecycle AI Protection
Inspect prompts, responses, and agent tool calls in real time, where traditional network and application controls stop.
Defense at the Semantic Layer
Controls mapped to ISO/IEC 42001, NIST AI RMF, the EU AI Act, and the UAE AI Governance Policy.
Regulation-Ready Controls
Automated red-teaming and continuous updates keep defenses current against the OWASP LLM and Agentic AI Top 10.
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