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Scooped by
JC Gaillard
onto Artificial Intelligence and Cybersecurity December 6, 2025 1:47 AM
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Technology rethink urged as enterprises still struggle to achieve the full benefits of zero trust access control.
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AI agents AppSec risk is rising as no-code automations bypass SDLC controls, create blind spots, and trigger internal breaches at scale.
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Unlike conventional LLMs that generate text in response to prompts, the independent nature of agentic AI redefines both opportunity and risk.
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AI agents are the fastest-growing and least-governed class of these machine identities — and they don’t just authenticate, they act.
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The 2025 SANS SOC Survey shows AI use is rising, but many SOCs lack integration, customization, and clear validation processes.
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Security researchers uncovered a range of cyber issues targeting AI systems that users and developers should be aware of — some as demo attacks and others already a threat in the wild.
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Every frontier model breaks under sustained attack. Red teaming reveals the gap between offensive capability and defensive readiness has never been wider.
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The best defense against prompt injection and other AI attacks is to do some basic engineering, test more, and not rely on AI to protect you.
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You don't need to rebuild your entire metrics framework overnight. Start with one attack path that keeps your executive team up at night.
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Enterprise AI defense is reshaping how CISOs manage risk as AI spreads across core systems, agents, and infrastructure.
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NVIDIA and Lakera AI built a framework that introduces ways to simulate threats inside workflows, watch behavior, and apply safeguards.
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LLMs are moving deeper into enterprise products and workflows, and that shift is creating new pressure on security leaders.
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By modernizing defenses and embracing phishing‑resistant identity protection, organizations hope to outpace the next wave of AI‑driven threats.
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One malicious prompt gets blocked, while ten prompts get through.
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From
hackernoon
Production AI agents fail from prompt injection, tool poisoning, credential leaks, and more. Learn 5 attack patterns and defensive code for each.
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Autonomous AI agents present a new world of opportunity—and an array of novel and complex risks and vulnerabilities that require attention and action now.
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From
www
Every CEO I meet thinks their AI strategy is simple: implement tools, boost productivity, and stay competitive. The reality is far riskier.
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AI-driven attacks leaked 23.77 million secrets in 2024, revealing that NIST, ISO, and CIS frameworks lack coverage for AI-specific threats.
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New guidelines can help an organization determine ways to incorporate AI into its operations while mitigating cybersecurity risks.
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By embracing specialized clouds and distributing workloads intelligently, companies can build the flexibility to adapt when — not if — things go wrong.
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Understand the impact of AI on security operations, improving insights and response times in the face of evolving threats.
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The AI shift to the edge promises faster insights and more resilient operations, but it also transforms the demands placed on the network.
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As the flurry of excitement over fresh AI innovation begins to fade, risk leaders, heads of GRC and CISOs have a new challenge to tackle. Regulators, customers, and boards are all asking harder questions about how AI is used, secured, and audited. For CISOs, AI governance is now a board-level expectation.
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AI governance, done properly, is not about slowing down or banning innovation. It is about putting enough structure around AI use that you can explain it, defend it and scale it.
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While some researchers dismiss reports of AI-driven cyberattacks as merely marketing messages, threat intel experts counter that CISOs ignore mounting evidence of AI use in the threat chain at their own peril.
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Dr Vrizlynn Thing, SVP, Head of Cybersecurity Strategic Technology Centre at ST Engineering, shared how cyber-resilience principles can help organizations build AI that is secure, trustworthy, and robust
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