Kaspersky issues guidelines on securing AI agents
Red Hat survey shows blind spots in UAE enterprise software supply chains
CISO news
Kaspersky issues guidelines on securing AI agents
business process automation to high-impact use cases such as supporting software development and IT security functions. The report, titled AI Agent Security Through the Lens of Cyber Immunity, analyses common AI agent use cases, levels of agentic autonomy and real-world incidents involving AI agents that have caused harm. It also systematises known risks and examines existing threat models. aspersky has shared guidelines on mitigating risks associated
K with the use of autonomous AI agents within corporate infrastructure. The document applies the principles of Cyber Immunity, an approach central to building secure-by-design systems. Drawing on known incidents and existing threat models, the new report examines the risks associated with increasingly autonomous agentic systems and outlines how to build trust into their architecture to minimise the potential impact of errors or compromise.
AI agents are increasingly being deployed across corporate environments, from routine
“ While Cyber Immunity was initially conceived outside the realm of AI, its core principles map directly onto advanced LLM based systems. When developers work with fundamentally non deterministic and untrusted components – which large language models should be considered by default – they should embed trust into the solution’ s architecture to limit the potential impact of errors or compromise,” said Vladislav Tushkanov, Head of Kaspersky AI Technology Research Centre.
Red Hat survey shows blind spots in UAE enterprise software supply chains
ed Hat has announced
R the results of a survey examining enterprise AI adoption and risk management across 1,400 CIOs across 14 countries, including the United Arab Emirates( UAE). The research indicates that while autonomous AI agents are rapidly moving into enterprise production, with 94 % of German businesses surveyed already deploying agents in production, a critical gap persists between perceived governance and actual operational visibility.
The majority of UAE CIOs surveyed( 91 %) report high confidence that their AI agents operate securely and in compliance with regulations, supported by guardrails and monitoring. However, the data highlights that this optimism can mask a lack of visibility:
Adrian Pickering, General Manager, Middle East and North Africa, Red Hat, said:“ Effective AI governance does not depend solely on policies and audit processes, but first and foremost requires comprehensive visibility. Companies need to know how data flows, which software components they are using and what risks AI providers pose – and this must be done throughout the entire lifecycle of AI agents. Before scaling up AI and agents, monitoring and governance mechanisms should always be established to identify risks early on, especially since AI makes it easier to discover and exploit vulnerabilities. Trustworthy software supply chains and community projects that quickly develop fixes, test them thoroughly and backport them to older versions reduce both security risks and operational risks.”
Adrian Pickering, General Manager, Middle East and North Africa, Red Hat
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