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.
Nvidia doesn't just make the chips that accelerate a lot of AI applications — the company regularly creates and uses its own large language models, too.
A Spanish-speaking cybercrime group named GXC Team has been observed bundling phishing kits with malicious Android applications, taking malware-as-a-service (MaaS) offerings to the next level
Despite bans on AI code generation tools, widespread use and lack of governance are creating significant security risks for organizations
"Peace is the virtue of civilization. War is its crime. Yet it is often in the furnace of war that the sharpest tools of peace are forged." - Victor Hugo
A software engineer hired for an internal IT AI team immediately became an insider threat by loading malware onto his workstation.
Docker is warning of a critical flaw impacting certain versions of Docker Engine that could allow an attacker to sidestep authorization plugins (AuthZ) under specific circumstances
Cybersecurity startup Zest Security emerged from stealth with an AI-powered cloud risk resolution platform to reduce time from discovery to remediation.
If it can happen to folks that run social engineering defence training, what hope for the rest of us? Cybersecurity awareness and training provider KnowBe4 hired a North Korean fake IT worker for a software engineering role on its AI team, and only realized its mistake once the guy started using his company-provided computer for evil.…
Gain insight by joining this AI security webinar on July 31 Webinar As artificial intelligence (AI) continues to transform industries in the Middle East, protecting systems from cyber threats is critical.…
Apps like Tinder, Bumble, Grindr, Badoo, OKCupid, MeetMe, and Hinge all have API vulnerabilities that expose sensitive user data, and six allow a threat actor to pinpoint exactly where someone is.
The opportunities to use AI in workflow automation are many and varied, but one of the simplest ways to use AI to save time and enhance your organization’s security posture is by building an automated SMS analysis service. Workflow automation platform Tines provides a good example of how to do it. The vendor recently released their first native AI features, and security teams have already