Organizations need to be fast adapt their application security strategies to meet the new threats posed by AI.
They include:
- More sophisticated bot traffic.
- More reliable phishing attacks.
- The rise of legitimate artificial intelligence agents that access online customer accounts on behalf of users.
By understanding the impact of AI on identity access management (IAM) and taking proactive measures, enterprises can stay ahead of the AI ​​curve and protect their digital assets. Here are the three key actions that organizations preparing their application security for the backend AI world should consider in their security strategies:
We’re already seeing examples of AI-powered websites being reverse-engineered to get free AI computing.
Protect against reverse engineering
Any application that exposes AI capabilities on the client side is vulnerable to particularly sophisticated bot attacks that attempt to “skim” or spam those API endpoints, and we’re already seeing examples of AI-powered websites being reverse-engineered for free To get AI calculations.
Consider the example of GPT4Free, a GitHub project dedicated to reverse-engineering websites onto GPT resources. It amassed a staggering 15,000+ stars in just a few days, a clear example of reverse engineering.
To prevent reverse engineering, organizations must 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 common bots, but these standard methods are easily overcome by more complex bot problems such as AI endpoints. Protecting against reverse engineering requires more sophisticated tools, such as custom CAPTCHAs or tamper-resistant JavaScript and device fingerprinting tools.