Beyond the AI arms race: What agents change in cybersecurity
Current evidence points to faster familiar attacks, not routine autonomous campaigns. The harder questions concern agent access, defensive context and accountable control.
Read MoreCurrent evidence points to faster familiar attacks, not routine autonomous campaigns. The harder questions concern agent access, defensive context and accountable control.
Read MoreOpenAI’s dots combine persistent context, shared app permissions and action-taking tools. Its own documentation shows why disconnecting an app is not a complete data reset.
Read MoreGemini 4 Argon is reaching selected Fairwind partners first, while public access, independent testing and details of a claimed healthcare flaw remain pending.
Read MoreOpenAI’s pause covered training, evaluation and tool-using inference for its most capable models, while separate government-site incidents had differing evidence and impacts.
Read MoreCommon Defense reports millions of screened messages, while live integrations, threat definitions, performance evidence and data handling remain unclear.
Read MoreThe exposure of 53 ChatGPT-user images raises a broader question: can frontier AI laboratories track and contain research agents once they reach external systems?
Read MoreA reported Meta Muse vulnerability could have exposed dedicated user environments, but its technical cause, affected scope and remediation status remain undisclosed.
Read MoreMusk set separate timelines for AI parity and leadership, yet the cited material supplies no benchmark or defined success measure.
Read MoreFortune says OpenAI is preparing a new cyber model and deployment tool, but official documentation still stops at GPT-5.6-Cyber and leaves key access questions unanswered.
Read MoreAs AI lowers the labour required for cyber operations, boards must replace assumptions about obscurity with a clearer view of identities, access, suppliers and recovery.
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