AI Security & Vulnerability Advisory
Find the AI attack surface before someone else does.
Why this matters now.
AI introduces failure modes traditional security never tested for: prompt injection, training-data leakage, and confidential data flowing into public models. Meanwhile shadow AI spreads through teams unmonitored, quietly widening the attack surface.
Our approach
We treat AI as an adversary would, red-teaming your models and agents for prompt injection, jailbreaks, and data exfiltration, and auditing where sensitive data is leaking into external tools. Findings come with prioritized, engineerable fixes — guardrails, DLP, and monitoring our build team can implement directly so the assessment ends in a hardened system, not a list of risks.
What you get
- LLM red-team and prompt-injection threat assessment
- Shadow-AI usage audit and data-leakage (DLP) review
- Model risk and data-exfiltration findings, prioritized by severity
- Remediation plan with guardrail and monitoring recommendations
Outcomes
- A clear map of your real AI attack surface and its highest risks
- Sensitive data kept out of public models and external tools
- AI deployed with defenses matched to how it actually gets attacked
Proof, on the way.
We hold this space for verified, client-approved outcomes rather than fill it with claims we cannot stand behind. Ask us for relevant references and a tailored walkthrough for your context.
How we engage
Scope
We map your AI systems, agents, and the data each one can touch.
Red-team
We attack your models for prompt injection, jailbreaks, and data exfiltration.
Audit
We surface shadow-AI usage and trace where sensitive data leaks into external tools.
Harden
We deliver prioritized fixes — guardrails, DLP, and monitoring — ready to build.
Questions leaders ask us.
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Learn moreReady to move on AI Security & Vulnerability Advisory?
Start with one conversation. We will frame the thesis, scope the system, and show you exactly how this engagement would run for your organization.