A look at Apate, a conversational bot developed by Macquarie University's Cyber Security Hub in Australia to keep scam callers on the line while collecting data
Tory Shepherd / The Guardian :
Context & Ripple Effects
Apate applies conversational AI to an adversarial communications problem: rather than helping a caller complete a task, it is built to prolong scam interactions and capture intelligence from them. That places it on the defensive side of the same chatbot capabilities that related coverage says have been adapted for phishing and malware activity.
The approach later appeared in a consumer-facing form when a UK operator introduced an AI scambaiter posing as an elderly caller. Apate matters as an earlier research-led example of using conversational systems to turn scam calls into a source of operational data.
First-order effects
- Apate gives Macquarie University's Cyber Security Hub a tool to engage scam callers automatically while collecting data from those interactions.
- Scam callers who reach Apate can spend time in a nonproductive conversation, while the system generates information that can be examined for patterns.
Second-order effects
- The collected call data can improve understanding of scam operations, potentially helping defenders prioritize blocking, investigation, or user-warning efforts.
- The tool adds defensive pressure to an environment where generative chatbots have also been associated with phishing- and malware-oriented tools, making conversational AI a capability used on both sides of fraud prevention.
Third-order effects
- If deployed and operationally useful at scale, AI scambaiting could shift part of fraud defense from reactive filtering toward automated intelligence gathering during live attacks.
- Its value will depend on whether collected interactions can be converted into actionable signals without creating new privacy, oversight, or misuse problems; the corpus does not establish that outcome.
The trend: Conversational AI is becoming dual-use infrastructure, with defenders adapting the same interaction skills exploited in scams into tools for disrupting and analyzing fraud.