Aurascape AI Security

What do you like best about the product?

My team was tasked with adding an internal GenAI chatbot to our fulfillment dashboard so warehouse managers could query inventory using natural language. We used the Model Context Protocol (MCP) to let the LLM call our Java 21 / Spring Boot backend endpoints. However, I absolutely did not want to trust an LLM to govern its own API calls against our production PostgreSQL database. I routed the agent's traffic through Aurascape's Zero-Bypass MCP Gateway, and what I loved most was the cryptographic signing feature. Aurascape inspects the prompt, ensures the tool call is authorized, and signs the payload. On my end, I just wrote a quick interceptor in Spring Security to validate that signature. If a compromised agent or a hallucination tries to bypass the proxy and hit our backend directly, my code immediately drops the unsigned request. It took the anxiety out of connecting AI to our core database.

What do you dislike about the product?

The inline anomaly detection is way too paranoid out of the box. Whenever our agent needed to pass a massive JSON array-like a bulk list of 50 different SKU numbers-into our backend endpoint as an argument, Aurascape's proxy would frequently flag the dense payload as an injection attempt or an obfuscation attack and block the request. I spent way too much time staring at their dashboard, writing custom exception policies, and tweaking thresholds just to get legitimate, heavy JSON blobs to pass through the proxy without timing out the chat interface.

What problems is the product solving and how is that benefiting you?

It solves the nightmare of LLMs hallucinating destructive API calls. We wanted to give ops teams the power of generative AI, but we were terrified the model might hallucinate a malformed POST request or leak customer PII into the prompt. By putting Aurascape in the middle, we established a hard, deterministic firewall. It guaranteed that the LLM could only execute the specific, approved read-only or mutation tools we defined, keeping our backend state perfectly safe from non-deterministic AI behavior.

What do you like best about the product?

Automatically inspect and blocks company data from being leaked online

What do you dislike about the product?

Implementing with third party requires skill

What problems is the product solving and how is that benefiting you?

Securing company data

What do you like best about the product?

I find Aurascape’s AI discovery and contextual risk analysis most useful. They give my security team visibility into AI applications employees may be using and more context about whether prompts and responses involve sensitive information or fall within our policies, rather than just showing website access or relying on keywords. I value the contextual policy controls because they distinguish acceptable use from activity that could expose sensitive data. The goal is to reduce risk without preventing employees from using AI productively. Real-time risk scoring also helps me prioritize which activities need attention and makes alerts more relevant than a simple list of blocked or allowed websites.

What do you dislike about the product?

I find it takes attention to keep investigations and policy decisions consistent across the different systems. The initial configuration also requires a clear understanding of which applications and data types to protect, and what to monitor or enforce.

What problems is the product solving and how is that benefiting you?

Employees can start using new AI applications without my security team knowing, and traditional web monitoring doesn’t show what information is being shared. Aurascape identifies AI usage and evaluates risk based on application behavior and data sensitivity, giving us more context to decide what to restrict or investigate.

What do you like best about the product?

We deployed AI task automation agents to help us speed up and improve the execution of our building engineering tasks and we use Aurascape to monitor the interactions that these AI Agents are having with our data to ensure we keep our sensitive and private data very well safeguarded. Aurascape makes easy for us to have real-time oversight over all data interactions that our AI Agents are having and to verify the intents behind every data access that our AI Agents have, making it possible to ensure that the AI Agents are accessing only the data that they are authorized to access without compromising the privacy and safety of our confidential information. Aurascape also help us to analyze all data access activities from our AI Agents making it possible to detect any malicious activities like unauthorized prompts that might lead to data loss and leakages.

What do you dislike about the product?

Since we implemented Aurascape some months back, we have never come across any challenges or technical issues. It has always worked flawlessly for us and we have not seen any weaknesses in its performance. There has been genuinely nothing to dislike about it.

What problems is the product solving and how is that benefiting you?

After we deployed AI Agents to automate our building engineering tasks, we brought in Aurascape to help us monitor these AI Agents and how they interact with our data in order to ensure that we keep our sensitive data and information always secure. Aurascape provides us with very advanced AI security visibility functions which makes it possible for us to monitor in real-time all data interactions that our AI Agents are having, allowing us to detect any authorized data access attempts that might put our data at any security risks. With Aurascape, we have had an easy time ensuring that all our Agents are accessing our data securely and within our access control guardrails in order to prevent any data loses and ensure we are always compliant with our data privacy and security regulations.

What do you like best about the product?

What I like best is the visibility. Within the first days we could see which AI tools our employees were actually using, including AI features built into SaaS apps and personal accounts we didn’t know about. The intent-based controls are another strong point. Instead of simply blocking AI tools, we can allow them and still stop sensitive data from leaking in prompts. The user coaching is also helpful, because people learn the right behavior without feeling blocked.

What do you dislike about the product?

Reporting could be more flexible, and fine tuning policies to reduce false positives took some time at the beginning.

What problems is the product solving and how is that benefiting you?

Aurascape solves the shadow AI problem for us. Employees were using many AI tools without control, and we had no visibility into what data was shared in prompts. Now we can see AI usage across the company, allow approved tools and prevent sensitive data from leaking. This lets us support AI adoption safely instead of simply blocking it.