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.
Researchers say there's dissent in the ranks. Plus: An AI tool lets you have a go yourself at analysing the data Hundreds of thousands of internal messages from the Black Basta ransomware gang were leaked by a Telegram user, prompting security researchers to bust out their best Russian translations post haste.…
El Reg shows you how to run Zypher's speech-replicating AI on your own box Hands on Palo Alto-based AI startup Zyphra unveiled a pair of open text-to-speech (TTS) models this week said to be capable of cloning your voice with as little as five seconds of sample audio. In our testing, we generated realistic results with less than half a minute of recorded speech.…