Only 23% of organizations rated the tools they use to detect and prevent API attacks as very effective.

3% of organizations rated the tools they use to detect and prevent API attacks as not effective at all.

6% of organizations do not know how effective their existing security tools are in preventing API attacks.

2% of organizations use other methods to assess the effectiveness of their API security measures.

5% of organizations reported that GenAI is not a concern at all for API security.

13% of organizations reported using GenAI for all API development.

49% of organizations are using GenAI for some API development.

23% of organizations plan to adopt GenAI within the next 6–12 months for API development.

45% of respondents cited the potential for new API vulnerabilities tied to AI-generated code.

47% of respondents cited difficulty understanding and securing AI-generated code.

56% of respondents cited a lack of control over AI model security used for code generation.

2% of respondents expressed other security concerns about using Generative AI to develop APIs.

35% of respondents cited difficulty ensuring quality and reliability of AI-generated code.

15% of organizations are very confident in detecting and responding to attacks leveraging Generative AI.

55% of organizations were somewhat confident in their ability to detect and respond to attacks leveraging Generative AI.

5% of organizations did not know about their ability to detect and respond to attacks leveraging Generative AI.

60% of developers, architects, and executives version their APIs.

For companies earning between $100 million and $300 million, manufacturing accounts for 30% of ransomware victims.

Among companies earning over $1 billion, manufacturing makes up a staggering 38.9% of ransomware victims.

64% of healthcare organizations say their organizations are vulnerable or highly vulnerable to a cloud/account compromise.