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Scooped by
JC Gaillard
onto Artificial Intelligence and Cybersecurity March 8, 2018 11:17 AM
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Artificial intelligence (AI) and machine learning are just two types of technology that are fighting cyber breaches on the front line
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Agentic AI makes security part of a wider operating shift. AI is a workload that must be secured and a worker whose actions must be governed.
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The attack exploited exposed credentials and trust relationships spanning development and cloud environments, showing how access in one system can enable more privileged actions in another.
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Agents are forcing a rethink of cloud security architecture. Here’s what CISOs should do to prepare for what’s next.
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CrowdStrike’s 2026 Global Threat Report puts average eCrime breakout time at 29 minutes, down from 48 minutes a year earlier, with AI-augmented attacks up 89 percent year over year. If your incident response plan still assumes hours between initial access and lateral movement, that assumption is now off by roughly two orders of magnitude.
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Technology leaders should prioritize building a centralized governance layer today that can manage agent identities, tool permissions, and token budgets in real time, because that control point is what builds the operational muscle to scale safely.
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Use safeguards, sandboxing and active oversight to realise the benefits of autonomous systems while limiting the unintended activity.
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AI-generated vulnerability patches fixed the bug cleanly about a quarter of the time across 6,080 attempts on six recent CVEs.
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AI can make SOC teams faster, but only if it fits existing workflows, connects their tools and earns analysts’ trust.
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From
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A cluster of recent stories about rogue AI evading control may just be cases of running a task in a room with a bad lock.
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It's far easier to find security holes than to fix them, and leaving it to AI can introduce 9 times as many new vulnerabilities as developers do.
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From
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Behind the rogue agent's attack on Hugging Face was a particular sequence of human decisions. We all need to pay better attention - because threat actors are learning, too.
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Anthropic’s Mythos AI model has helped discover two new cryptanalytic attacks, one against the NIST post-quantum digital signature candidate Hawk, and one against a weakened version of AES — but neither threatens deployed technology.
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From
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SANS Institute notes that companies are reworking security teams and salaries are going up
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Organizations need a safe place to evaluate whether their controls, detection, containment, and teams can withstand it.
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Zero trust assumes everyone is an attacker until proven otherwise. But when your enterprise is swarming with unknown autonomous agents, that is tricky if not impossible.
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Proposed legislation could mandate that companies be able to "throttle, suspend, or shut ... down" AI agents, but how and when to do that remain open questions.
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AI agents can scale an attack faster than humans can respond, making traditional incident response dangerously slow.
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Too much is never enough when it comes to strengthening enterprise security. Fortunately, AI is ready to help you drive security to its maximum potential.
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Enterprises are facing a critical cyber asymmetry issue as AI models’ offensive and defensive capability gaps grow.
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The goal here is not to block agentic AI but to build the foundation that makes it worth deploying.
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From
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AI agents are flooding cybersecurity. The Agentic SOC Alliance wants to define which ones can be trusted before hype outruns security.
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Reports from Cisco Talos and CrowdStrike provide real-world insights into how AI is evolving attackers’ tradecraft and becoming part of their day-to-day operations.
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The enterprise AI nightmare is not a killer robot, but an erosion of our ability to see and control what’s running in our own environments at the same tim our velocity is exploding.
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Traditional IAM assumes humans with finite sessions, consistent behavior, and natural lifecycle events. AI agents run continuously, behave according to code rather than habit, and have no built-in triggers for credential review or rotation.
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We are about to hear one of the most dangerous phrases of the agentic AI era: The agent did it. It will become the successor to “the algorithm did it,” which itself was little more than a technological update to “mistakes were made.” All three expressions perform the same useful function. They describe an event without identifying the humans responsible for causing it.
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