Explore the intersection of AI and cybersecurity. Stay informed on AI-driven security trends, tools, and threats in the ever-evolving digital landscape.
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Background for this topic.
Artificial intelligence (AI) describes computer systems that perform tasks such as recognizing patterns, making predictions, understanding language, or generating content. In security reporting, the term commonly includes machine-learning models used for detection and analysis, as well as generative AI applications that produce text, code, images, or other outputs.
AI can help analyze security telemetry, prioritize vulnerabilities, and support investigations, but its outputs can be wrong or manipulated. Important attack surfaces include prompt injection that steers an application into unintended actions, sensitive data being exposed through prompts or model outputs, and excessive permissions granted to AI systems that use external tools. Models can also be degraded by poisoned training data or evaded with carefully crafted inputs. Practitioners should protect training and operational data, limit model access and tool permissions, test for adversarial behavior, and require appropriate human validation before high-impact decisions.
BlackBerry president John Giamatteo acknowledged that governments should intervene to mitigate AI risks – and his company is willing to help them
Experts discussed growing utilization of ChatGPT by threat actors and evolving identity-based attacks
APIs have become fundamental to everyone’s digital life, yet API security continues to be overlooked, Contxt’s CEO Mayur Upadhyaya said during Infosecurity Europe
The discovery was made by Singapore-based cybersecurity firm Group-IB.
Netskope’s new solution aims to enable organizations to use generative AI tools without running cybersecurity or data protection risks