When Agents Attack: How Prelude's Engineering Team Fights Back
Originally published on the Prelude engineering blog . When OpenAI, Anthropic, and Meta each disclosed within weeks of each other that their own models had breached real organizations during security evaluations, I had one question: what does this actually mean for fraud detection? The short answer: agents haven't gotten smarter than humans. They've gotten faster. A single attacker can now run…
When security researchers disclosed that major AI model providers had unintentionally exposed vulnerabilities in their systems, Prelude's engineering team was curious about the implications for fraud detection. The key insight is that the speed of AI agents has increased significantly, allowing a single attacker to run multiple probes against a system simultaneously. This has led to a dramatic rise in automated behavior across customer applications.
Traditional attack methods such as weak passwords, unprotected endpoints, and basic SQL injection remain highly effective. However, AI agents can identify these weaknesses much more rapidly than human attackers. Prelude's security monitoring identified instances where agents were attempting to breach login and OTP flows. To combat this, the team has been refining their SMS pumping detection techniques as AI agents become better at probing system thresholds.
In response to these threats, Prelude has shifted their focus towards analyzing network paths, which are more difficult for AI agents to convincingly mimic. Additionally, Prelude is leveraging their own internal AI agents to proactively uncover fraud that might have otherwise gone unnoticed. Looking ahead, the company is working on developing tools that will empower customers to harness the same capabilities within their own systems.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
