Organizations need to quickly adapt their application security strategies to address new AI-powered threats.
They understand:
- More sophisticated bot traffic.
- More credible phishing attacks.
- The increase in the number 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 steps, companies can stay ahead of the AI curve and protect their digital assets. . Here are the top three actions that organizations preparing their application security for a post-AI world should consider in their security strategies:
We are already seeing examples of AI-powered reverse engineering sites to get free AI computing.
Defend against reverse engineering
Any app that exposes client-side AI capabilities is exposed to particularly sophisticated bot attacks that seek to “skimme” or spam those API endpoints – and we’re already seeing examples of reverse-engineering powered sites. by AI to get free AI computing.
Take the example of GPT4Free, a GitHub project dedicated to reverse engineering sites to piggyback on GPT resources. It racked up an astounding 15,000+ stars in just a few days in a blatant public example of reverse engineering.
To prevent reverse engineering, organizations should invest in advanced fraud mitigation tools and bots. Standard anti-bot methods such as CAPTCHA, rate limiting, and JA3 (a form of TLS fingerprinting) can be useful in defeating ordinary bots, but these standard methods are easily defeated by more complex bot problems like those faced by AI terminals. Protection against reverse engineering requires more sophisticated tools like custom CAPTCHAs or tamper-proof JavaScript and device fingerprinting tools.
