AI Security & Privacy

Making AI a Competitive Advantage where Innovation meets Risk Discipline

Industry Challenges

Sensitive Data Exposure & Privacy Leakage

AI systems frequently interact with PII, PHI, financial records, and proprietary data. Without strict controls, this can result in inadvertent exposure, shadow AI usage, and privacy non-compliance.

Lack of AI Visibility, Inventory, and Risk Ownership

Organizations often lack a complete view of where AI and GenAI are being used, what data they access, and who owns the associated risks. Shadow AI, unmanaged GenAI tools, and undocumented models create blind spots that undermine security, governance, and compliance efforts.

AI Supply Chain & Model Provenance Risks

Organizations increasingly rely on third-party AI models, datasets, embeddings, and open-source components. Without full visibility into how these assets were trained, businesses face hidden risks creating both security and legal exposures.

Immature AI Governance & Lack of Guardrails

Organizations deploy AI faster than policies, monitoring, or risk controls can keep up leading to inconsistent oversight and unclear accountability.

Rapid AI Expansion Without Proper Risk Management

As AI adoption spreads across business units, organizations struggle to scale safely while maintaining transparency, compliance, and security.

AI Model Security Threats

LLMs and ML models are exposed to adversarial attacks including prompt injection, data extraction, model manipulation, poisoning, and evasion. Most AI applications are not hardened against these vectors.

Solutions

Propelex provides a comprehensive AI and GenAI Security and Privacy assessment and governance program that safeguards every layer of the AI ecosystem across its lifecycle. We secure traditional AI and GenAI systems, leveraging intelligent AI security tools combined with compliance-aligned controls, advanced technical assurance, secure architecture design, and AI-specific governance. Aligned with NIST AI Risk Management Framework (AI RMF) and ISO/IEC 42001, our approach helps organizations mitigate emerging AI risks, protect sensitive data, and meet evolving regulatory obligations with confidence. The result is secure, compliant, and scalable AI adoption enabling innovation at speed without compromising security, trust, or regulatory posture.

Comprehensive Solution Highlights

A thorough evaluation of your AI systems, governance maturity, and compliance readiness tailored for regulated industries.

AI Discovery, Inventory & Lifecycle Mapping

We identify every component of your AI ecosystem and document how data and models move through your environment.

Catalog AI models, datasets, labeling workflows, and pipelines
Map lineage, lifecycle stages, and model documentation
Review vendors, APIs, endpoints, and LLM integrations
Evaluate existing AI policies, standards, and operational processes

Policy & Procedures Review

We ensure your governance structure supports safe, transparent AI operations.

Validate AI use policies and data handling rules
Review access control logic and identity management
Assess retention, model change procedures, and approval workflows
Introduce AI-specific SOPs (risk review, change control, escalation)

Compliance Mapping & Control Effectiveness

We test your technical and procedural controls against industry-leading frameworks.

Map alignment with NIST AI RMF (Govern/Map/Measure/Manage)
Assess readiness for ISO/IEC 42001
Test IAM, encryption, secrets management, and secure ML SDLC
Validate logging, monitoring, drift detection, and rollback processes
Review IR response playbooks

LLM & GenAI Application Security Review

We assess and harden GenAI and LLM-enabled applications.

Evaluate systems against OWASP LLM Top 10
Strengthen prompts, output handling, sandboxing, and filtering
Add data exfiltration guardrails for GenAI interactions
Create approval workflows for external GenAI/SaaS tools
Use intelligent AI security tools to continuously analyze prompts, responses, and GenAI workflows for abuse patterns, leakage risks, and control bypass attempts

Host Application & Infrastructure Penetration Testing

We perform both traditional and AI-specific security testing.

Full application & infrastructure penetration testing
AI red teaming: prompt injection, jailbreak attempts
Model poisoning, evasion, and inference manipulation attacks
Security validation for plugins, extensions, and LLM pipelines
Apply intelligent AI-driven testing tools to dynamically generate attack scenarios, prioritize high-impact findings, and stress-test AI-enabled infrastructure

Gap Prioritization, Remediation Roadmap & KPIs

We convert findings into a measurable improvement plan.

Prioritize risks (Critical → Low)
Map gaps to required controls and regulations
Provide a 90-day remediation roadmap
Establish KPIs for drift detection, bias reporting, and incident MTTR

Results and Outcomes

NIST AI RMF and ISO/IEC 42001 alignment and readiness assessment

Risk-prioritized findings with regulatory traceability

Validated security posture across models, pipelines, infrastructure, and GenAI applications

Executable remediation roadmap

FAQs

Let us help you with any inquiry you might have.

What is AI and GenAI security, and why is it important?

AI and GenAI security focuses on protecting artificial intelligence systems, including machine learning models and large language models (LLMs), from security, privacy, and misuse risks. As AI systems process sensitive data and influence business decisions, weaknesses can lead to data leakage, regulatory violations, model manipulation, and loss of trust. A comprehensive AI security program ensures AI adoption is secure, compliant, and resilient across its lifecycle.

How is AI security different from traditional application security?

AI security goes beyond traditional application security by addressing risks unique to AI systems, such as model poisoning, prompt injection, hallucinations, data leakage through outputs, and misuse of GenAI tools. Unlike standard applications, AI systems learn from data, rely on probabilistic outputs, and often integrate third-party models, requiring specialized testing, governance, and controls.

What does Propelex’s AI and GenAI security assessment cover?

Propelex provides an end-to-end AI and GenAI security and privacy assessment that covers data, models, applications, infrastructure, and governance. This includes AI discovery and lifecycle mapping, policy and governance review, compliance alignment, GenAI application security reviews, penetration testing, and continuous improvement planning.

How does Propelex secure GenAI and LLM-enabled applications?

We assess and harden GenAI and LLM-enabled applications by evaluating them against risks such as prompt injection, insecure output handling, data exfiltration, and unsafe integrations. Our approach includes alignment with OWASP LLM Top 10, strengthening guardrails, validating approval workflows for external GenAI tools, and applying intelligent AI security tooling to enhance detection of misuse and leakage risks.

What frameworks does Propelex align with for AI governance and compliance?

Our approach is aligned with leading global frameworks, including the NIST AI Risk Management Framework (AI RMF) and ISO/IEC 42001. This ensures organizations can manage AI risks systematically, demonstrate responsible AI governance, and meet evolving regulatory and audit expectations.

Do you support both traditional AI and Generative AI systems?

Yes. Propelex secures both traditional AI systems (such as predictive models and machine learning pipelines) and modern GenAI systems, including LLMs and AI-powered applications. Our services are designed to adapt to different AI architectures, use cases, and maturity levels.

What is AI red teaming and why is it included?

AI red teaming simulates real-world attacks against AI systems to identify weaknesses before they can be exploited. This includes testing for prompt injection, jailbreaks, model evasion, inference manipulation, and unsafe integrations. AI red teaming helps validate that security controls work in practice, not just in theory.

How does Propelex use intelligent AI security tools?

We apply intelligent AI security tools to enhance visibility, testing depth, and scalability across AI security activities. These tools support advanced attack simulation, misuse detection, and validation of AI-specific and traditional security controls, complementing expert-led assessments and technical testing.

How does this service help with regulatory and privacy requirements?

Our AI security and privacy program helps organizations identify and mitigate risks related to personal data, sensitive information, and regulatory obligations. By aligning technical controls with governance and compliance requirements, organizations can demonstrate accountability, reduce regulatory exposure, and prepare for audits related to AI usage.

Is this a one-time assessment or an ongoing program?

Propelex’s AI security offering is designed as a lifecycle-based program. While organizations may start with an assessment, the approach supports continuous improvement through gap prioritization, roadmaps, KPIs, and ongoing governance to keep pace with evolving AI risks and regulations.

Who should engage in an AI security and privacy assessment?

AI security assessments are relevant for organizations developing, deploying, or using AI and GenAI systems, including those in regulated industries such as finance, healthcare, technology, and SaaS. Security leaders, risk teams, compliance stakeholders, and engineering teams all benefit from a structured, defensible AI security approach.

How does Propelex enable innovation without slowing AI adoption?

By integrating security, privacy, and governance into the AI lifecycle, Propelex helps organizations move faster with confidence. Our approach reduces uncertainty, clarifies risk ownership, and embeds guardrails early, enabling secure, compliant, and scalable AI adoption without compromising innovation speed or trust.