AI Security & Governance
Helping enterprises adopt AI without inheriting its failure modes — securing what you build, governing what you buy, and staying ahead of AI regulation. We test LLM and GenAI applications like an attacker, stand up governance aligned to ISO 42001 and NIST AI RMF, and set guardrails your board can stand behind. Built for CISOs, CIOs, data and AI leaders shipping or adopting AI at scale.
Why this matters to the business
- Unmanaged AI adoption Teams and vendors embed AI faster than security or governance can keep up.
- A new, unfamiliar attack surface Prompt injection, data leakage and agent abuse don't map cleanly to existing controls.
- Model & data governance gaps No inventory, ownership or review of the models making business decisions.
- Regulatory uncertainty ISO 42001, the EU AI Act and evolving Indian guidance raise the bar with little precedent.
Capabilities
LLM application security testing
Prompt injection, jailbreaks, data exfiltration, insecure output handling and agent/tool abuse — tested against OWASP LLM Top 10.
AI governance & ISO 42001
AI management systems, acceptable-use policy, model inventory and review boards sized to your organization.
NIST AI RMF alignment
Risk mapping and controls for AI systems using the framework enterprises and regulators reference.
Model & data-pipeline risk reviews
Training-data provenance, access to model artifacts, fine-tuning and RAG pipeline security.
Third-party AI risk
Assessment of vendor AI features and copilots before they touch your data.
Secure AI adoption advisory
Guardrails for internal GenAI use that enable teams instead of banning tools they'll use anyway.
The CyberScales approach
- Treat AI as a new attack surface on existing systems — identity, data and application security still decide most outcomes.
- Test AI features like an attacker: with tooling and creativity, not a compliance checklist.
- Govern by risk tier — a support-chat summarizer and a credit-decision model don't need the same controls.
- Track the regulatory horizon (EU AI Act, India's evolving guidance) so you're ready before it's mandatory.
Frameworks & references
Ideal for
- Companies building AI/GenAI into products
- Enterprises adopting AI copilots at scale
- Regulated businesses using AI in decisions
- Boards asking about AI risk & governance
- Teams preparing for ISO 42001 / EU AI Act
Deliverables
- AI system and model inventory
- LLM / GenAI application security test
- AI governance framework (ISO 42001-aligned)
- NIST AI RMF risk mapping
- Model and data-pipeline risk review
- Third-party AI risk assessment
- Secure AI adoption policy and guardrails
- Executive summary
Outcomes
- AI adopted without inheriting its risks
- A defensible AI governance posture
- Guardrails leadership can stand behind
- Regulatory readiness ahead of mandates
- Confidence to ship AI features safely
Engagement model
- 01 Discover & inventory
- 02 Risk & security assessment
- 03 Governance design
- 04 Testing & guardrails
- 05 Roadmap & policy
- 06 Ongoing advisory
Common questions
We use GenAI via APIs — is that our risk or the provider's?
Yours. Providers secure the model infrastructure; prompt injection, data leakage through context, and what your app does with outputs remain your problem.
Is ISO 42001 worth pursuing now?
If AI is core to your product or your customers are asking about AI governance, yes — early adopters are using it as a differentiator the way SOC 2 was used a decade ago.
Can you test our LLM application specifically?
Yes — we test against the OWASP LLM Top 10 and MITRE ATLAS: prompt injection, data exfiltration, insecure output handling, jailbreaks and agent/tool abuse.
Do we need AI governance if we only buy AI, not build it?
Yes. Vendor AI features touch your data and make decisions on your behalf; third-party AI risk and an acceptable-use policy still apply.
Will governance slow our AI teams down?
Done right, no. We govern by risk tier, so low-risk use stays fast and high-consequence systems get the controls they warrant.
Discuss your AI Security challenges
A focused 30-minute scoping call — useful, and pressure-free. We'll tell you honestly what's worth doing, and what isn't.