AI & LLM Security Services

AI & LLM security protects your AI and Large Language Model applications from threats unique to them — prompt injection, jailbreaks, training-data poisoning, sensitive-information disclosure and insecure model supply chains. CyberSigma delivers LLM penetration testing and red-teaming, AI/ML security assessments, and AI governance aligned to the OWASP Top 10 for LLM Applications, NIST AI RMF, ISO/IEC 42001 and MITRE ATLAS. We are CERT-In empanelled and PCI QSA (CEMEA) authorised.

Securing AI and LLM Applications Against a New Class of Threats

Organisations are racing to embed Generative AI, LLMs and ML models into products, customer support, code and decision-making. But these systems introduce risks traditional security testing was never designed to catch: a chatbot can be tricked into leaking confidential data, an AI agent can be manipulated into taking unauthorised actions, and a poisoned dataset or compromised model from a public hub can backdoor your entire pipeline.

CyberSigma secures the full AI lifecycle — from the model and training data to the application, prompts, plugins and agentic workflows around it. Our testing and governance map directly to the recognised AI security frameworks so your board, customers and regulators get defensible, independent assurance that your AI is safe to ship.

• LLM & GenAI application penetration testing and red-teaming.
• AI/ML model, pipeline and MLOps security assessment.
• AI governance and compliance (ISO/IEC 42001, NIST AI RMF).
• AI risk assessment and threat modelling (Google SAIF, MITRE ATLAS).
• Secure AI adoption — GenAI usage policy, shadow-AI and data-leak controls.
• EU AI Act, DPDP and GDPR readiness for AI and training data.

LLM Penetration Testing & Red-Teaming (OWASP Top 10 for LLMs)

We adversarially test your LLM and GenAI applications the way a real attacker would, covering the OWASP Top 10 for LLM Applications and the MITRE ATLAS adversarial-ML tactics:

• Prompt injection — direct and indirect (via documents, web pages, tools).
• Sensitive information disclosure — leaking PII, secrets or system prompts.
• Insecure output handling — XSS, SSRF and code execution from model output.
• Excessive agency — agents/plugins performing unauthorised or destructive actions.
• Training-data poisoning and model/data supply-chain risks.
• Jailbreaks, guardrail bypass, denial-of-wallet and model-extraction attacks.

AI Governance & Compliance

Security testing proves your AI is robust; governance proves you manage it responsibly. We help you stand up an AI management system and meet emerging AI regulation:

1. **ISO/IEC 42001:2023** — implement and ready your AI Management System (AIMS) for certification.

2. **NIST AI RMF 1.0** — Govern, Map, Measure and Manage AI risk with a working risk register and model cards.

3. **EU AI Act** — classify your AI systems by risk tier and close the gaps for high-risk obligations.

4. **Data protection for AI** — lawful basis and safeguards for training data under India's DPDP Act and GDPR.

5. **Responsible-AI policy** — acceptable-use, human-oversight and incident-handling policies for staff and products.

Our AI Security Engagement Process

1. **Scoping & AI Inventory**: We map your models, data flows, prompts, plugins, agents and the obligations that apply.

2. **Threat Modelling**: Using Google SAIF and MITRE ATLAS, we model how your specific AI system can be abused.

3. **Testing & Assessment**: Manual red-teaming and tool-assisted testing across the OWASP LLM Top 10 and the ML pipeline.

4. **Reporting**: A clear, audit-ready report with risk-rated findings, proof-of-concept and prioritised remediation.

5. **Governance & Retest**: We help implement controls (ISO 42001 / NIST AI RMF) and retest to confirm closure.

Key Benefits

1. **Ship AI Safely**: Find and fix exploitable AI weaknesses before attackers — or your customers — do.

2. **Regulatory Confidence**: Evidence aligned to ISO/IEC 42001, NIST AI RMF and the EU AI Act.

3. **Customer Trust**: Pass enterprise AI security questionnaires and due diligence.

4. **Protect Data**: Stop your LLMs leaking PII, secrets and intellectual property.

5. **Independent Assurance**: Reports from a CERT-In empanelled, PCI QSA authorised firm.

What is AI / LLM security?

AI/LLM security is the practice of protecting artificial-intelligence and Large Language Model systems from threats specific to them — such as prompt injection, jailbreaks, sensitive-data leakage, insecure output handling, excessive agency, and training-data or model supply-chain poisoning — across the model, data, application and the agents and plugins around it.

What is the OWASP Top 10 for LLM Applications?

It is the industry-standard list of the most critical security risks in LLM applications — including prompt injection, sensitive information disclosure, insecure output handling, excessive agency, and supply-chain vulnerabilities. We test your AI applications against all of them and report findings mapped to each category.

How is LLM penetration testing different from normal pen testing?

Traditional pen testing targets code, networks and infrastructure. LLM red-teaming additionally targets the model's behaviour — manipulating it through natural-language prompts, poisoned context, and connected tools to make it leak data or take unauthorised actions. Mature programmes need both; we provide each and can combine them.

Can you help us comply with the EU AI Act and ISO/IEC 42001?

Yes. We classify your AI systems by EU AI Act risk tier and close the gaps for high-risk obligations, and we implement and ready an ISO/IEC 42001 AI Management System for certification, alongside NIST AI RMF risk management.

We use ChatGPT, Copilot and other GenAI tools internally — can you help secure that?

Yes. Our secure AI-adoption advisory covers GenAI acceptable-use policy, human-oversight controls, data-leakage prevention for tools like ChatGPT and Copilot, and detection of shadow-AI usage across your organisation.