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.
GPDP probe is due to allegations that ChatGPT failed to comply with data collection rules
Harvesting API keys and secrets from AWS SES, Microsoft Office 365 and other services
A new "comprehensive toolset" called AlienFox is being distributed on Telegram as a way for threat actors to harvest credentials from API keys and secrets from popular cloud service providers
Musk, Wozniak, and Yang are among more than a thousand tech leaders asking for time to establish human safety parameters around AI.
AI professors and developers have co-signed an open letter to artificial intelligence labs, calling them to pause the development and training of AI systems more powerful than GPT-4 for at least six months. [...]
The emergence of smart mobility services and applications has led to a sharp increase in the use of APIs in the automotive industry. However, this increased reliance on APIs has also made them one of the most common attack vectors. According to Gartner, APIs account for 90% of the web application attack surface areas. With no surprise, similar trends are emerging also in the smart mobility
The breach was caused by a bug in an open-source library
Microsoft's new AI assistant tool helps cybersecurity teams investigate security incidents and hunt for threats.
Microsoft on Tuesday unveiled Security Copilot in preview, marking its continued push to embed AI-oriented features in an attempt to offer "end-to-end defense at machine speed and scale." Powered by OpenAI's GPT-4 generative AI and its own security-specific model, it's billed as a security analysis tool that enables cybersecurity analysts to quickly respond to threats, process signals, and
Microsoft today announced Security Copilot, a new ChatGPT-like assistant powered by artificial intelligence that takes advantage of Microsoft's threat intelligence footprint to make faster decisions during incident response and to help with threat hunting and security reporting. [...]
Malicious actors are constantly adapting their tactics, techniques, and procedures (TTPs) to adapt to political, technological, and regulatory changes quickly. A few emerging threats that organizations of all sizes should be aware of include the following: Increased use of Artificial Intelligence and Machine Learning: Malicious actors are increasingly leveraging AI and machine learning to