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Scooped by
JC Gaillard
onto Artificial Intelligence and Cybersecurity July 6, 1:07 AM
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AI-generated code risks are slowing deployment, as most companies write code with AI but hesitate to ship it to customers.
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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
www
SANS Institute notes that companies are reworking security teams and salaries are going up
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From
www
Shadow AI is often framed as a cybersecurity challenge, but that view misses what is really driving adoption.
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Having a spreadsheet of AI risks is fine, but it won't tell your team what to do or who can hit the kill switch when a model actually breaks.
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From
www
The flaw, which impacted Amazon, Anthropic, Google, Cursor and others, let the agent give the human false information on which to make decisions.
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From
www
Left ungoverned, an organization ends up with dozens of agents hitting production systems directly, and no single place to see the traffic or stop it.
Diamondstone's curator insight,
July 7, 2:27 AM
The future of cybersecurity will depend on innovation, collaboration, and continuous vigilance. In an increasingly connected world, staying secure online is not an option; it is a responsibility shared by all.read more...https://pressearn.it.com/blog/?s=Technology+
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As cybersecurity platforms embrace agentic AI, organizations must balance detection performance against the escalating costs of token consumption, deployment architecture, and AI credits.
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From
medium
A lot of “robotic horse pulls a buggy” kind of operations — where everything is kept exactly the same as it was in 2003, but “AI SOC” tools are simply tacked on to perform some of the tasks.
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AI pentesting finds high-risk flaws at 2.7x the rate of other systems, and two of every three serious AI findings stay open and unfixed.
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Don't panic about new AI threats; hackers are still using the same old security gaps to get in, so use AI to help your team finally fix the basics.
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From
www
Organizations today must determine whether an autonomous system should be trusted to execute a specific transaction at a specific moment under defined conditions.
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For years, security teams had to choose between cheap, consistent or high-quality operations, but AI is finally letting us have all three at once.
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Alert triage and basic investigation Tier 1 analyst tasks are disappearing, but other roles will boom. Here are the prime candidates — whether you’re reshaping your career or reskilling your SOC.
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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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From
www
Organizations and people who embrace innovation without sacrificing security will own the future. Cyber hygiene is now more than just good practice in the era of artificial intelligence. It's called digital citizenship.
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If we view shadow AI only through a security lens, we risk treating the symptom rather than the cause.
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From
www
Knowing who an agent is and what it may access tells you nothing about whether what it just did was supposed to happen.
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As agentic AI and autonomous agents trend in 2026, enterprises face a major new hurdle: standard IAM stacks aren't built to govern these non-human actors.
Diamondstone's curator insight,
July 11, 3:48 PM
As organizations increasingly adopt autonomous AI agents, managing non-human identities has become a critical cybersecurity priority. The "Agentic AI Identity: A 6-Stage Maturity Model for Non-Human Identities" outlines a structured framework that helps organizations securely manage AI agents throughout their lifecycle. The model progresses from basic identification and authentication to advanced governance, continuous monitoring, automated policy enforcement, and adaptive trust. By following these six stages, organizations can reduce security risks, improve compliance, and ensure AI systems operate responsibly. The framework highlights that AI agents should be treated as trusted digital identities with clearly defined permissions, accountability, and ongoing oversight, making it an essential guide for organizations embracing AI-driven automation.read more.https://pressearn.it.com/blog/?s=Technology+
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AI-generated code risks are slowing deployment, as most companies write code with AI but hesitate to ship it to customers.
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Teams are dealing with a truly dangerous problem — automation that works, but that no one understands.
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From
thenewstack
As AI agents outnumber humans 144:1, legacy security is cracking. Discover how to secure your infrastructure with Agent IAM.
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From
www
The industry just has to face that vulnerability management has been broken for years.
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From
www
Today’s intruders rarely smash through the front entrance. They slip in through a neglected API, a stolen login, an overpowered service account or an AI workload nobody fully owns. After that, they move sideways fast, and they move far.
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The Attack Surface Your Security Team Isn't Governing Yet
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AI's unpredictable, dynamic nature is breaking traditional cybersecurity models, requiring leaders to shift focus from prevention to real-time runtime visibility.
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