The 5 generative AI security threats you need to know about detailed in new e-book

Generative AI is reshaping security work, accelerating threat detection and enabling scalable defence, even as attackers adopt similar tricks to outpace traditional safeguards. In Microsoft’s coverage, the top threats include poisoning attacks that skew AI training data, evasion attacks that bypass safeguards, and prompt injection attacks that override instructions, with broader risks arising as AI scales.

The piece notes that 66% of organisations are developing or planning custom generative AI apps, 88% are concerned about indirect prompt injection, and 80% of business leaders worry about data leakage via AI. A new guide, titled 5 Generative AI Security Threats You Must Know About, builds on these themes and discusses how cloud-native security platforms can unify tools such as CSPM, CIEM and CWPP to protect AI workloads from development to runtime.

Microsoft Security highlights Defender for Cloud as an example of how end-to-end AI security can map attack paths and detect AI-specific threats, backed by more than 100 trillion daily signals from Microsoft Threat Intelligence. According to Microsoft Digital Threats Report, cyberattackers from Russia, China, Iran and North Korea have doubled their use of AI to conduct attacks and spread disinformation.