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Scooped by
JC Gaillard
onto Artificial Intelligence and Cybersecurity February 12, 12:56 AM
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Resilience requires first securing AI foundations and then scaling AI-driven defence capabilities.
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From
www
Agentic AI brings a new set of security risks that go beyond those introduced by more straightforward large language models (LLMs), generative AI (gen AI) chatbots or other forms of artificial intelligence.
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Enterprises rush to deploy autonomous systems as securing AI agents lags, exposing gaps in identity, governance, visibility, and control.
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Most security leaders believe they know where their sensitive data lives and how it is protected. That confidence is increasingly misplaced.
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Exponential expansion of autonomous agents in the enterprise may expand enterprise threat surfaces to an almost unmanageable degree — especially given poor foundations for non-human identity oversight.
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AI can strengthen cyber defenses, but only when paired with human oversight, transparent data, and strong governance, not blind trust in autonomous systems.
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Emerging NIST guidance suggests that the long-standing practice of treating AI as “just software” for cybersecurity purposes is giving way to more novel approaches to managing AI risks.
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In the coming year, organizations will no longer measure cyber resilience by whether a breach occurred. They will measure it by how quickly it was detected, how precisely it was isolated, and how confidently systems were restored.
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Security execs increasingly see AI as the means to supercharge their security operations, but the rush to embed AI in security tools can create myriad pitfalls, experts warn.
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AI adoption depends on application modernization, security alignment, and disciplined foundations that support scalable AI programs.
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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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Scoop.it!
Resilience requires first securing AI foundations and then scaling AI-driven defence capabilities.
Scoop.it!
From
fortune
Why OpenAI’s latest coding breakthrough is forcing the company to rethink how—and how fast—it can deploy its most powerful models.
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Abandoned AI projects and pilots also create unforeseen and often undetectable vulnerabilities.
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AI agents are now executing regulated actions, reshaping how compliance controls actually work.
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From
www
Analysis by Sonatype found that AI is giving attackers new opportunities to target victims
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From
dzone
AI-driven development is outpacing security. This piece shows where AI security tools help, where they fail, and how teams can use them responsibly.
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AI is evolving at a rapid pace, and the uptake of Generative AI (GenAI) is revolutionising the way humans interact and leverage this technology.
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Misaligned agents are just one layer of the AI security challenge that startup Witness AI is trying to solve. It detects employee use of unapproved tools, blocks attacks, and ensures compliance.
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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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