AI Security
Shadow AI policy enforcement, AI pentesting, and agentic-AI governance — for how the business is actually using AI today, not what the policy document pretends.
Your team is already using ChatGPT, Claude, Lovable, Copilot, and every AI tool that lands in the Slack channel. Every blanket ban becomes a workaround within a week. PII, customer data, source code, and confidential strategy already leave the organisation through prompts. The choice is not whether AI is used — it is whether you can see and govern it.
There are three distinct AI security problems and they need three operational answers. Shadow AI — unsanctioned LLM use. Vibe-coded applications — AI-generated code carrying embedded vulnerabilities. Agentic AI — autonomous agents acting inside your environment. We handle each as a discrete operational practice, not a single 'AI strategy'.
- Falcon AIDR for Shadow AI
Browser extension plus Falcon sensor inspect prompts in real time and either redact sensitive content (PII, secrets, customer data) or block the submission. We default to redact so people keep working — friction-free policy beats blanket bans that get worked around.
- Falcon AIDR for agentic AI
Detection of prompt injection, jailbreaks, data leakage, and unsafe agent actions before they execute. Coverage for internal copilots, autonomous agents, and AI features shipping in your own product.
- AI pentesting for AI features
Aikido's AI-driven pentest approach applied to your AI surface area — the chatbot, the agent, the LLM-backed API. Not a compliance theatre exercise; an actual probe of the prompt-injection and exfiltration paths.
- AI policy that survives contact
Acceptable-use policy, data-handling rules, vendor approval flow, and employee guidance — written so the policy matches the technical enforcement, not so it lives in a binder while the technical reality goes the other way.
- Vibe-coded application review
AI-generated code carrying inherited vulnerabilities — common attack patterns the model has seen and reproduced verbatim. Continuous AppSec via Aikido catches them on every push; manual review for the high-risk flows.
- AI advisory at executive level
Where AI fits, where it does not, what the realistic Shadow AI exposure looks like, and the questions to ask the board about AI investment. Honest read, not a vendor pitch.
- 01 Map exposure
What AI tools are actually in use across the organisation. Browser-extension telemetry plus a candid conversation with engineering and operations. Most organisations are surprised by the answer.
- 02 Deploy controls
Falcon AIDR rolled out across the workforce — browser extension plus Falcon sensor — in redact-default mode. We tune sensitivity per data class so the friction is targeted, not blanket.
- 03 Govern agentic systems
For internal copilots, customer-facing chatbots, and autonomous agents shipping in your product: prompt-injection testing, output monitoring, and runtime governance via Falcon AIDR.
- 04 Operate and report
Monthly review of detected sensitive prompts, blocked submissions, agent incidents, and the policy adjustments that follow. AI security is operational, not a one-time deployment.
- A real picture of how AI is used in your organisation — and a redact-or-block policy that survives the day-to-day.
- Agentic-AI features in your product that have been probed for prompt injection, jailbreaks, and data leakage before they ship.
- An executive narrative on AI security that does not depend on hand-waving.
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CrowdStrike Falcon platformThe platform we run our 24/7 SOC on — endpoint, identity, cloud, and agentic AI in one stack.
✓ Certified partner -
Tenable Exposure ManagementVulnerability management across environments — from cloud to OT.
✓ Certified partner -
Aikido AppSec & AI-pentestContinuous application security and AI-driven pentesting.
✓ Certified partner
What exactly is Shadow AI?
Employees pasting sensitive data into AI tools — ChatGPT, Claude, Lovable, Copilot, and the long tail — without explicit organisational approval. PII, customer data, source code, financial figures, and strategy documents are the most common categories. The data is not necessarily mishandled by the AI vendor, but it has now left your perimeter, your DLP scope, and your audit trail.
Why redact instead of block?
Because blanket blocks get worked around within a week. The team that needs to use AI to do their job will find a way — a personal account, a phone, a different browser. Redaction sits between 'forbidden' and 'allowed' — sensitive content is removed at the prompt boundary; the rest of the prompt goes through. People keep working. Policy survives. The blocked-submission option is still there for the categories that genuinely should not leave at all.
What is agentic AI and why is it different?
Agentic AI is a system that takes actions on your behalf — booking meetings, querying databases, sending messages, deploying code. Unlike a chatbot that just answers, an agent has tools and consequences. Prompt injection against an agent is not a curiosity; it is a remote code execution path with a friendly UI. Falcon AIDR detects the manipulation patterns — prompt injection, jailbreaks, unsafe tool calls — before the action happens.
How do you test our customer-facing AI feature?
Aikido's AI pentest agents probe the live AI feature the way an attacker would — prompt injection, jailbreak attempts, data-exfiltration through the model's responses, abuse of any connected tools or APIs. Reports list what the agent actually managed to extract or trigger, not theoretical findings. We also do manual review of the high-risk flows where AI agents are still weak.
Does Falcon AIDR work without the rest of CrowdStrike?
AIDR is most useful as part of the Falcon platform, where the sensor extends governance from the browser to the endpoint to the agentic process. Standalone deployment of just the AIDR browser extension is possible but covers a narrower threat model. If you are already on Falcon, AIDR is an add-on; if you are not, the conversation is about whether to deploy the platform end-to-end.
What about open-source LLMs running on our own infrastructure?
Different threat model, different controls. Falcon AIDR covers the SaaS LLM and agentic-AI cases. For self-hosted models — say a Llama deployment behind your own RAG pipeline — we run a different set of controls: prompt-injection testing via Aikido, output filtering at the application layer, and monitoring at the host level via Falcon. We will scope it as a discrete engagement rather than pretending one product solves everything.