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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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.
Fortunately, we're not talking about a robot revolution, or about hospital AI run amuck. But these bugs could lead to ransomware, or worse...
Traditional endpoint security isn't working, says Darktrace Sponsored feature Remember the good old days, when the only devices a company had to worry about were the PCs on its own network? Today, security teams must yearn for those times as they struggle to protect endpoint devices everywhere.…
Traditional endpoint security isn't working, says Darktrace Paid feature Remember the good old days, when the only devices a company had to worry about were the PCs on its own network? Today, security teams must yearn for those times as they struggle to protect endpoint devices everywhere.…