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Most security tools work like a smoke alarm that goes off every time you burn a piece of toast. You get so many alerts that you eventually start to ignore them.
The real danger? While
Security teams have never had better visibility into their environments and never been worse at confirming what they fix stays fixed.
Mandiant's M-Trends 2026 report puts the mean time to exploit at an estimated negative seven days. The Verizon 2025 DBIR puts median time to remediate edge device vulnerabilities at 32 days. These numbers have understandably driven the industry toward a clear
Why do the Riskiest SOC Alerts Go Unanswered?
Security operations teams are drowning in alerts. But the real problem isn't always alert volume; it's the blind spots. The most dangerous alerts are the ones no one is investigating.
A recent report from The Hacker News examined why certain high-risk alert categories - WAF, DLP, OT/IoT, dark web intelligence, and supply chain signals- consistently
Agentic AI is already running in production environments across many organizations today. It is executing tasks, consuming data, and taking actions — most likely without meaningful involvement from the security team. The industry conversation has largely framed this as a question of policy: allow it, restrict it, or monitor it? However, that framing misses the point.
The more urgent
Defending a network at 2 am looks a lot like this: an analyst copy-pasting a hash from a PDF into a SIEM query. A red team script is being rewritten by hand so the blue team can use it. A patch waiting on a change-approval window that's longer than the exploitation window itself.
Nobody in that chain is incompetent. Every human is doing their job correctly. The problem is the system, its
The traditional vulnerability disclosure timeline relies on a fundamental assumption: exploit development and vulnerability discovery take time. Over the last 12 months the integration of LLMs into offensive tooling has demonstrably broken this assumption. I recently published a technical write-up arguing that the 90-day disclosure window is effectively dead backed by three specific observations from recent incidents:
Automated Diff Analysis (30-minute n-days) : The safety net between a patch release and an in-the-wild exploit is gone. Taking a recent React security patch (CVE-2026-23870), I used an LLM to analyze the diff, identify the vulnerable path, and write a working DoS PoC in roughly 30 minutes. The human reverse-engineering bottleneck has been bypassed.
Vulnerability Convergence : I recently reported a critical P0 to a vendor and was told I was the 11th reporter in 6 weeks. LLM assisted scanners are causing independent researchers to converge on the same bugs simultaneously. An embargo no longer contains the vulnerability; it simply provides a head start to whichever threat actor also found it.
The Linux Kernel (Copy Fail & Dirty Frag) : The recent kernel exploits highlight this perfectly. Copy Fail (CVE-2026-31431) went from an automated AI scan to a public PoC to nation state weaponization in days. Shortly after the embargo for Dirty Frag (CVE-2026-43284 / CVE-2026-43500) was broken in hours because an unrelated third party independently discovered the same bug class using similar tooling.
The defense cannot operate on monthly cycles when the offense is operating in hours. The focus needs to shift to real-time, PR-level AI scanning to match the pace. can read the full technical breakdown and case studies on my blog:https://blog.himanshuanand.com/2026/05/the-90-day-disclosure-policy-is-dead/
I am curious if the researchers here are experiencing similar convergence rates or if you view this as a temporary anomaly while legacy codebases are scanned with new tools.
The dark secret of enterprise security operations is that defenders have quietly institutionalized the practice of not looking. This is not just anecdotal, but rather backed by a recent report investigating more than 25 million security alerts, including informational and low-severity, across live enterprise environments.
The dataset behind these findings includes 10 million monitored
The hardest part of cybersecurity isn't the technology, it’s the people.
Every major breach you’ve read about lately usually starts the same way: one employee, one clever email, and one "Patient Zero" infection.
In 2026, hackers are using AI to make these "first clicks" nearly impossible to spot. If a single laptop gets compromised on your watch, do you have a plan to stop it from taking down
Having an incident response retainer, or even a pre-approved external incident response firm, is not the same as being ready for an incident. A retainer means someone will answer the phone. Operational readiness determines whether that team can do meaningful work the moment they do.
That distinction matters far more than many organizations realize. In the first hours of a security incident
For nearly 20 years, we at The Hacker News have mostly told scary stories about cyberspace — big hacks, broken systems, and new threats.
But behind every headline, there’s a quieter, better story.
It’s the story of leaders making tough calls under pressure, teams building smarter defenses, and security products that keep hunting threats 24/7 — even when it’s hard.
Most of the time, this work is
Every AI tool, workflow automation, and productivity app your employees connected to Google or Microsoft this year left something behind: a persistent OAuth token with no expiration date, no automatic cleanup, and in most organizations, no one watching it. Your perimeter controls don't see it. Your MFA doesn't stop it. And when an attacker gets hold of one, they don't need a password.
OAuth
While the software industry has made genuine strides over the past few decades to deliver products securely, the furious pace of AI adoption is putting that progress at risk. Businesses are moving fast to self-host LLM infrastructure, drawn by the promise of AI as a force multiplier and the pressure to deliver more value faster. But speed is coming at the expense of security.
In the wake of the
On December 4, 2025, a 17-year-old was arrested in Osaka under Japan’s Unauthorized Access Prohibition Act. The young man had run malicious code to extract the personal data of over 7 million users of Kaikatsu Club, Japan's largest internet cafe chain. When asked, the young man shared his motivation for the hack: he wanted to buy Pokémon cards.
In a sense, this is a fairly conventional story.
The managed security services market is projected to grow from $38.31 billion in 2025 to $69.16 billion by 2030[1], with cybersecurity being the fastest-growing sector[2]. Despite this opportunity, many MSPs leave revenue on the table because their go-to-market strategy fails to connect technical expertise with business needs.
This execution gap is where most deals stall. MSPs often focus on
Intro
A sophisticated, high-resilience malicious campaign was identified by Atos Threat Research Center (TRC) in March 2026. This operation specifically targets the high-privilege professional accounts of enterprise administrators, DevOps engineers, and security analysts by impersonating administrative utilities they rely on for daily operations. By integrating Search Engine Order (SEO)
In February 2026, researchers uncovered a shift that completely changed the game: threat actors are now using custom AI setups to automate attacks directly into the kill chain.
We aren't just talking about AI writing better phishing emails anymore. We’re talking about autonomous agents mapping Active Directory and seizing Domain Admin credentials in minutes.
The problem? Most defensive workflows
Every security program is betting on the same assumption: once a system is connected, the problem is solved. Open a ticket, stand up a gateway, push the data through. Done.
That assumption is wrong. It is also a major reason Zero Trust programs stall.
New research my team just published puts numbers on it. The Cyber360: Defending the Digital Battlespace report, based on a survey of 500 security
When patching isn’t fast enough, NDR helps contain the next era of threats.
If you’ve been tracking advancements in AI, you know the exploit window, the short buffer that organizations relied on to patch and protect after a vulnerability disclosure, is closing fast.
Anthropic’s new model, Claude Mythos, and its Project Glasswing, showed that finding exploitable vulnerabilities and subtle cracks
Anthropic’s Claude Mythos Preview has dominated security discussions since its April 7 announcement. Early reporting describes a powerful cybersecurity-focused AI system capable of identifying vulnerabilities at scale and raising serious questions about how quickly organizations can validate, prioritize, and remediate what it finds.
The debate that followed has mostly focused on the right
The AI Agent Authority Gap - From Ungoverned to Delegation
As discussed in our previous article, AI agents are exposing a structural gap in enterprise security, but the problem is often framed too narrowly.
The issue is not simply that agents are new actors. It is that agents are delegated actors. They do not emerge with independent authority. They are triggered, invoked, provisioned, or
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