RapidResponse

Inspiration

We're both interested in Cybersecurity. Many Cybersecurity businesses state they leverage AI to its fullest but often only use it by a technicality. This inspired us to take it to the next level and go beyond alerting to offer RapidResponse to incidents. We wanted to do more than to let you know you've been breached.

What it does

RapidResponse offers proactive Azure login monitoring and response. Using AI, it detects suspicious activities like VPN usage or unusual logins, swiftly securing compromised accounts. It engages users via SMS for verification, will scan Emails to identify Risk and provides IT teams with concise summaries for RapidResponse, ensuring seamless business operations and data protection.

How we built it

We used the following: Python (Flask Backend), C# w/ Microsoft SQL Express, Vonage for SMS messaging, Open AI API, Microsoft Graph API.

Challenges we ran into

Moe: I'm not experienced with Swift and building with it was a challenge. With this application I there was a lot of data moving around and doing that in Swift was a challenge to me since I was learning the MVVM structure when creating this. I also had a lot of trouble with getting SMS working with certain APIs due to rules and regulations so we had to use different services which ended up me hosting a Web Server listening on the WAN IP to receive SMS and made a custom Flask Web page to handle the requests.

Jacob: Never Built an API or Used Python, had to do both to work around an OSX ODBC issue Never used the Graph API to do anything, now had to leverage it for Reading Logs, Emails and Taking action on accounts Haven't interfaced with SQL from C# or Python in the past Not super familiar with SQL Connection Strings or Auth, This was painful to realize I was over complicating it