Security News
A new research report explores emerging trends that software organizations need to consider as part of their security strategy, and risks associated with the use of existing open source software in application development. In particular, as modern software development increasingly adopts distributed architectures and microservices alongside third party and open source components, the report tracks the astonishing popularity of ChatGPT's API, how current large language model-based AI platforms are unable to accurately classify malware risk in most cases, and how almost half of all applications make no calls at all to security-sensitive APIs in their code base.
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In this Help Net Security interview, Arthur Hu, SVP, Global CIO and Services & Solutions Group CTO at Lenovo, discusses how AI/ML is optimizing tech stacks, the hurdles anticipated in its integration, the role of AI in enterprise resilience and agility, and strategic approaches to innovation despite budget constraints. We'll touch on the evolving role of CIOs and the potential for 'as-a-service' offerings to ease tech stack management.
We and our store and/or access information on a device, such as cookies and process personal data, such as unique identifiers and standard information sent by a device for personalised ads and content, ad and content measurement, and audience insights, as well as to develop and improve products. With your permission we and our partners may use precise geolocation data and identification through device scanning.
According to findings from SlashNext, a new generative AI cybercrime tool called WormGPT has been advertised on underground forums as a way for adversaries to launch sophisticated phishing and business email compromise attacks.In the hands of a bad actor, tools like WormGPT could be a powerful weapon, especially as OpenAI ChatGPT and Google Bard are increasingly taking steps to combat the abuse of large language models to fabricate convincing phishing emails and generate malicious code.
72% of hackers are confident that AI cannot replace human creativity in security research and vulnerability management, according to Bugcrowd. Generative AI was a major theme in the 2023 report, with 55% of respondents saying that it can already outperform hackers or will be able to do so within the next five years.
Find out how Google Cloud approaches AI data, what privacy measures your business should keep in mind when it comes to generative AI and how to make a machine learning application "Unlearn" someone's data. Google Cloud approaches using personal data in AI products by covering such data under the existing Google Cloud Platform Agreement.
When companies utilize public generative AI tools, the models are refined on input data provided by the company. While publicly available generative AI tools permit natural language querying, world wide web data is not always applicable to the use case.
Research and development: Google uses information to improve our services and to develop new products, features and technologies that benefit our users and the public. We use publicly available information to help train Google's AI models and build products and features like Google Translate, Bard, and Cloud AI capabilities.
Spear Phishing with Social Engineering: AI can analyze vast amounts of publicly available data from social media, professional networks, or other sources to gather information about potential targets. Regulation and legal risks associated with AI refer to the potential liabilities and legal consequences that businesses may face when implementing AI technology.