3 things companies need to do to secure applications in the AI ​​era

Organizations need to move quickly adapt their application security strategies to address emerging threats fueled by AI.

They contain:

  • More advanced bot traffic.
  • More credible phishing attacks.
  • The emergence of legitimate AI agents accessing customer online accounts on behalf of users.

By understanding the implications of AI on Identity Access Management (IAM) and taking proactive measures, companies can stay ahead of the AI ​​curve and protect their digital assets. Here are the top three actions organizations preparing their application security for a post-AI world should consider in their security strategies:

We are already seeing examples of AI powered sites being reverse engineered to get free AI computing.

Defend against reverse engineering

Any app that exposes AI capabilities on the client side is at risk from particularly sophisticated bot attacks bent on “skimming” or spamming those API endpoints – and we’re already seeing examples of AI-powered sites being reverse engineered to get free AI computing.

Take the example of GPT4Free, a GitHub project aimed at reverse engineering sites to piggyback on GPT resources. It amassed an astonishing 15,000+ stars in just a few days in a blatant public example of reverse engineering.

To avoid reverse engineering, organizations should invest in advanced fraud and bot mitigation tools. Standard anti-bot methods such as CAPTCHA, rate limiting, and JA3 (a form of TLS fingerprinting) can be valuable in defeating regular bots, but these standard methods are easily circumvented by more complex bot problems such as AI endpoint problems. Protection against reverse engineering requires more advanced tools such as custom CAPTCHAs or tamper-resistant JavaScript and device fingerprinting tools.

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