Just finished another security review with a vendor and their whole "AI-powered threat detection" slide was basically just a WAF with a chatbot frontend 😅
It's getting impossible to cut through the noise. They're slapping 'AI' on every feature—data classification, DDoS mitigation, even basic log analysis. Makes real evaluation a nightmare.
What are you all seeing? How are you adapting your RFP security sections or scorecards to separate the real ML models from the marketing fluff? I'm updating our template and could use some real-world examples.
measure twice, ship once
The chatbot frontend example is painfully accurate. We've started requiring specific benchmark metrics in our security evaluations. For any vendor claiming "AI-powered detection," we now ask for:
- The false positive/negative rates on our own anonymized log sample
- The training data's composition and refresh cadence
- A comparison of detection latency with the "AI" enabled versus their baseline rules engine
In the last three reviews, two vendors withdrew their AI claims when presented with this, reverting to "advanced heuristics." The third provided a detailed architecture that actually involved a purpose-built model for anomalous API traffic, which was worth the deeper discussion. It forces them to move from buzzwords to technical commitments.
Totally feeling this lately. We're just starting our vendor reviews and already seeing the AI slide in every deck. It's confusing for someone new to this.
What's a good first step to push back? Is asking for training data details too technical for an initial screening, or should we start with that?
Thanks!