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Ever wished you could rebuild your network from scratch to make it more secure, scalable and simple? Meet Meter, the company reimagining enterprise networking from the ground up. Meter builds full stack zero trust networks including hardware, firmware and software, all designed to work seamlessly together. The result? Fast, reliable and secure connectivity without the constant patching, vendor juggling or hidden costs. From wired and wireless to routing, switching, firewalls, DNS security and vpn, every layer is integrated and continuously protected in one unified platform. And since it's delivered as one predictable monthly service, you skip the heavy capital costs and endless upgrade cycles. Meter even buys back your old infrastructure to make switching effort, transform complexity into simplicity and give your team time to focus on what really matters, helping your business and customers thrive. Learn more and book your demo@meter.com cyberwire that's M E T E R.com cyberwire. Trump Signs the National Defense Authorization act for 2026 Danish intelligence officials accused Russia of orchestrating cyber attacks against critical infrastructure. Long nosed Goblin targets government institutions across Southeast Asia and Japan. A new Android botnet infects nearly 2 million devices. WatchGuard patches its Firebox firewalls. Amazon blocks more than 1800 North Korean operatives from joining its workforce. CISA releases nine new industrial control system advisories. The U.S. sentencing Commission seeks public input on deepfakes. Prosecutors indict 54 in a large scale ATM jackpotting conspiracy. Our guest is Natay Milner, CEO of Orion Security, discussing the issue with data leaking into AI tools and how CISOs must prioritize DLP and Riot Games Finds cheaters hiding in the BIOS. It's Friday, december 19, 2025. I'm dave buettner and this is your cyberwire intel brief.
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Foreign.
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Thanks for joining us here today. Happy Friday. It is great to have you with us. President Donald Trump signed a $901 billion National Defense Authorization act for 2026 that includes major cyber security provisions, and it passed with bipartisan support. The bill authorizes record defense spending and preserves the long debated dual hat leadership of US Cyber Command and the National Security Agency by barring Pentagon funds from weakening the Cyber Command's commander's authority. That provision reinforces a structure Trump previously considered splitting but ultimately abandoned. Trump also nominated Army Lt. Gen. Joshua Rudd to lead both organizations. The NDAA allocates roughly $417 million to Cyber Command for digital operations, other activities, and headquarters maintenance. It mandates secure encrypted mobile devices for senior Defense Department leaders following inspector General criticism of insecure communications. The bill also requires reviews of foreign sourced infrastructure components and and orders the Pentagon to streamline its cybersecurity requirements. Danish intelligence officials have accused Russia of orchestrating cyber attacks against Denmark's critical infrastructure as part of a broader hybrid campaign against Western countries. The Danish Defense intelligence service said two pro Russia groups, Z Pentest and Noname O5716, carried out attacks on water utilities and launched DDoS attacks ahead of local elections, aiming to create insecurity and punish Denmark for supporting Ukraine. Officials said the cyber activity is part of a wider influence effort to undermine Western backing of Kyiv, with elections used to attract public attention. Denmark's defense minister called the attacks unacceptable and said Russia's ambassador would be summoned. The warning aligns with broader European concerns echoed by incidents in Norway and a recent joint advisory from US And European agencies about pro Russian hacktivist threats to global critical infrastructure. Researchers have identified a previously unknown China aligned hacking group targeting government institutions across Southeast Asia and Japan. The group, dubbed Long nosed Goblin by ESET, has been active since at least September 2023 and was uncovered during an investigation of a Southeast Asian government network. The hackers abused Windows Group Policy, a legitimate administrative tool to deploy malware and move laterally. Their tools include Nosy Historian, which harvests browser data to identify high value victims, and Nosy Door, a selective backdoor suggesting carefully chosen targets. Researchers warn that a newly identified Android botnet dubbed Kimwolf, has infected more than 1.8 million devices and can launch massive DDoS attacks. Chinese firm Xlab says the botnet mainly targets Android TV set top boxes and focuses on traffic proxying, but issued over 1.7 billion attack commands in late November. Kimwolf is linked to the Turbo Mirai class Isuru botnet and may have powered recent near 30 terabit per second attacks. The malware uses encrypted DNS to evade detection and operates on a globally distributed infrastructure. Watchguard has issued an urgent warning for customers to patch a critical actively exploited remote code execution vulnerability affecting its Firebox firewalls. The flaw impacts devices running multiple versions of fireware OS and allows unauthenticated attackers to execute malicious code remotely through low complexity attacks. WatchGuard caution that devices may remain vulnerable even after certain VPN settings are removed. The company said it has observed active exploitation in the wild and and released indicators of compromise, urging affected users to rotate credentials if compromise is suspected. Temporary mitigations are available for organizations unable to patch immediately. The advisory follows a pattern of similar Watchguard firewall vulnerabilities that were widely exploited and later flagged by CISA. Amazon says it has blocked more than 1800 suspected North Korean operatives from joining its workforce since April 2020, underscoring how widespread the so called fake IT workers scam has become. Chief Security Officer Steve Schmidt said applications linked to North Korea rose 27% quarter over quarter this year. The scheme involves real developers using stolen or fabricated identities, AI generated resumes and even deepfakes to secure remote jobs, then funneling wages back to the regime. Some attackers also steal sensitive data or extort employers. Amazon uses AI screening and human verification to detect the fraud. But Schmidt warned tactics are evolving, including hijacked LinkedIn accounts and US based laptop farms that disguise overseas workers as domestic employees. CISA has released nine new industrial control system advisories covering security vulnerabilities across a wide range of widely used operational technology products. The advisories address systems from major vendors including Inductive Automation, Schneider Electric, National Instruments, Mitsubishi Electric, Siemens Advantech, Rockwell Automation and Axis Communications. Affected products range from SCADA platforms and distributed control systems to industrial networking stacks and camera management software. CISA urged asset owners, operators and administrators to review the advisories for detailed technical information and recommended mitigations to reduce risk in industrial and critical infrastructure environments. The U.S. sentencing Commission is proposing preliminary sentencing guidelines under the Take It Down Act, a bipartisan law passed earlier this year to combat non consensual deepfake pornography. The law makes it a federal crime to distribute real or AI generated intimate imagery without consent and requires platforms to remove reported content within 48 hours, with enforcement authority given to the Federal Trade Commission. It outlines prison sentences of up to two years for deep faking adults and up to three years for minors. With the commission now refining penalties by offense type, proposed updates clarify definitions tied to online services and intent, including abuse or sexual exploitation. The commission is seeking public comment on the guidelines through February 16, 2026. As concern grows over increasingly realistic AI generated media, US prosecutors have indicted 54 individuals for their alleged roles in a large scale ATM jackpotting conspiracy involving mal, malware and coordinated cash theft. A federal grand jury in Nebraska returned two indictments, one in October charging 32 people and another in December charging 22 more. Authorities allege the scheme used Plautus malware to force ATMs to dispense cash, resulting in losses of about $40.7 million as of August 2025. The indictment links the activity to Tren d', Arugua, a Venezuelan criminal syndicate designated as a foreign terrorist organization, accusing it of laundering proceeds to fund broader criminal operations. Investigators say the group conducted surveillance, physically accessed ATMs to install malware, and used techniques designed to evade detection and obscure evidence. If convicted, defendants face sentences ranging from decades to life in prison. Coming up after the break, my conversation with Nite Milner, CEO of Orion Security. We're discussing issues with data leaking into AI tools and Riot Games finds cheaters hiding in the bios. Stick around. What's your 2am Security worry? Is it do I have the right controls in place? Maybe Are my vendors secure? Or the one that really keeps you up at night? How do I get out from under these old tools and manual processes? That's where Vanta comes in. Vanta automates the manual work so you can stop sweating over spreadsheets, chasing audit evidence and filling out endless questionnaires. Their trust management platform continuously monitors your systems, centralizes your data, and simplifies your security at scale. And it fits right into your workflows, using AI to streamline evidence collection, flag risks, and keep your program audit ready all the time. With Vanta, you get everything you need to move faster, scale confidently, and finally, get back to sleep. Get started at vanta.com cyber that's V-A-N-T A.com cyber.
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Nitei Milner is CEO of Orion Security. We recently discussed the issues with data leaking into AI tools and how CISOs must prioritize DLP.
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So traditional DLP tools, legacy tools like Falsebone, Siemantec, were all about creating policies to make sure you protect your data. So the mission was to protect sensitive data. For banks it can be credit cards. For healthcare providers it can be phi data. And what you had to do with the traditional tools is you had to define a policy for every use case of data that you want to protect. For example, you don't want credit cards to get outside to external recipients over emails. So you had to sit down and create a policy, a rule basically for every one of these use cases. And then what usually would happen is you had to tweak it over and over again because you'd get a lot of false positives, catching all sorts of data that looks like credit card data or data that looks like phi data. And then you had thousands of alerts or false positives. And these tools were known for being, to say the least, not very effective for enterprise companies.
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And so what's changed over time in terms of the state of the art when it comes to DLP tools today?
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So over time, during the past years, technologies like UEBA try to basically reinvent DLP with anomaly detection, but that didn't really work well in other industries like EDR antiviruses. Anomaly detection makes a lot of sense because you can predict how, for example, processes should behave. But it's really, really hard to understand how people are going to behave. So anomaly detection for detecting data loss for people is really hard. So you get a lot of false positives because people change their, how they handle sensitive data every day. So it's hard to just use anomaly detection. And that had failed for the past 10 years. What had changed recently is LLMs and generative AI applications. So basically what is trying to be done right now in the market is to use LLMs, basically human cognition, the missing piece of DLP, and basically think like a security analyst for every data exploitation entitled the company, looking at a lot of indicators, for example, the person doing the action, the type of data that is being sent outside of the organization, the source of the data that's presentation, then getting to a decision if this is basically a verdict, if this is risky for the company or just a normal business ops business data flow in the organization.
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So is the idea here that you're making use of the LLM to basically sort through your logs, to check through a user's behavior and see how that matches up to a set of potential rules that you may have set up or red flags that you've set up?
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Yeah, so it's a different approach than rules. So rules, what we have up until now are deterministic rules. Policies are basically a one or a zero. But when you add LLMs to it, when you add cognition to it, it can have more possibility than just right or wrong. It can look at other context, at other criteria and basically get to a decision like basically a security. A DLP security analyst will look at the person doing the action, how long is he in the company, how does he usually act around sensitive data and then decide if this is a false positive or not. So this is what we're adding right now to the table, just like an ad hoc Verdict for every data exploitation attempt in the company.
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So then does the LLM, for example, when it makes a decision, it alerts a security professional, a human, as to whether or not maybe this needs a little more attention?
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Yeah, definitely. But the. So we're definitely keeping the human in the loop right now. But instead of meeting five DLP analysts today, that goes through, and I'm not exaggerating, thousands of alerts every month that most of them, like 90% of them are false positive. They would get more around like 5 or 10% of false positive. And they will be added into the loop only when necessary. So if you need like five people up until now to run your DLP program with the new technologies in the market, you can do it with 20% of an FTE time. And this is a real game changer in SmartKit.
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And are these systems growing in intelligence as they operate? Does the feedback go back into the process itself?
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Just like a security analyst, you can teach it. So basically when you get the false positives, you can mark a thumbs down and you can explain exactly why this is a false positive. For example, this is an approved destination to send our sensitive data to. Maybe it's a third party vendor that we're working with. Or this data is not really that sensitive for the company. And the LLM model adds it to his context in this specific company. And in next time it will happen, it will use this context to reduce the false positives.
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It really sounds to me like what you're introducing here is the ability to have nuance in these decisions.
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Exactly. You can think about it like it's more similar to like EDR for data. If you remember the old days of Noton and McAfee where you have antiviruses. So EDR came along and basically gave a new approach to detecting malware, a more detection and response approach. It's the same thing we're doing. But up until now it wasn't really possible in DLP because human behaviors are much more complicated than machine behaviors. But now with LLM, we can actually build something that looks like EDR for data. It's easy to maintain, it's a plug and play solution, and it can protect your data without needing to hire an army of DOP analysts.
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What about for people who are hesitant to feed any of their information into an LLM? Are there protections for them?
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Yeah, definitely. It doesn't train the model over separate customers and you can run your LLM model in your own environment. So basically you can keep the constraint on your side.
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Where do you Suppose this is headed, what's the future look like for dlp?
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That's a great question and what I've been waiting for. So basically what we talked up until nowadays is that how AI can help DLP and help data security. But we didn't talk about how AI is a threat in data security and how it's going to change the landscape around data excruciation. So there's three main ways of AI to be looked upon as a threat in data security. One is sensitive data extrudation to AI. For example, ChatGPT or Quad. An employee can take a broad presentation or a financial document with very sensitive data and just feed it to a third party chatgpt. It happens all the time and it's a top risk for a lot of companies today. The second one is AI agents exfiltrating data outside of the company. So AI agents will replace a lot of the human work. For example, an email assistant AI agent that will write emails for you and will share data for you. It can exfiltrate a lot of sensitive data maliciously or just by mistake. And the third one is AI makes corporate data very accessible. If you're familiar with companies like Glean data sharing and data searching with AI makes data very accessible, sometimes not the data that you want this person to access in the company. So for example, you can just type down the salary of the CEO and if by mistake you have access to it, you can see it right away. So data security is about to have a lot of new problems in the upcoming years. And AI can be looked upon as a threat, but also as a huge enaBler for creating 100x Betal solutions with one tenth of the operational cost associated with the traditional ones.
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So AI giveth and AI taketh away, right?
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Exactly. 100%. 100%, Dave.
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All right, well, I think I have everything I need for our story here. Is there anything I missed, anything I haven't asked you that you think is important to share?
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I think that data security is going through a generational shift and everybody can feel that right now that we can build much better solutions with much less cost for companies. And we're going to see a lot of new threats with AI. And like our mission, or my mission even personally, is to make sure that people can access these benefits as fast as possible. And I think that we're going to have a very interesting few years in front of us when it comes to data security and data protection.
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That's Nite Milner, CEO of Orion Security.
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So good.
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So good.
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So good.
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And finally, Riot Games has discovered that some recent motherboards were quietly letting cheaters slip past the velvet rope. A flaw in bios firmware from vendors including Asrock, Asus, Gigabyte, and MSI meant certain DMA based cheats could operate invisibly, bypassing protections meant to keep games fair. Riot says the issue undermined IOMMU defenses that looked awake but were not fully on the job. Like a nightclub bouncer dozing off mid shift, the fix is less glamorous than a ban wave, but more effective. Motherboard makers have released bios updates, and Riot's Vanguard Anti Cheat may now insist players install them before launching Valorant. Riot causes a necessary escalation in the hardware cheat arms race, one that shuts down a whole category of previously untouchable tricks and makes cheating a lot more expensive. And that's the Cyber Wire. For links to all of today's stories, check out our daily briefing@thecyberwire.com be sure to check out this weekend's Research Saturday in my conversation with Darren Meyer, security research advocate at Checkmarks. The research we're discussing is titled Bypassing AI Agent Defenses with Lies in the Loop. That's Research Saturday. Check it out. We'd love to know what you think of this podcast. Your feedback ensures we deliver the insights that keep you a step ahead in the rapidly changing world of cybersecurity. If you like our show, please share a rating and review in your favorite podcast app. Please also fill out the survey in the show notes or send an email to cyberwire2k.com N2K senior producer is Alice Carruth. Our Cyberwire producer is Liz Stokes. We're mixed by Trey Hester. With original music by Elliot Peltzman. Our executive producer is Jennifer Ibin. Idra Kilpe is our publisher. And I'm Dave Bittner. Thanks for listening. We'll see you back here next week. And Doug, here we have the Limu Emu in its natural habitat, helping people customize their car insurance and save hundreds with Liberty Mutual. Fascinating. It's accompanied by his natural ally, Doug.
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Episode: Where encryption meets executive muscle — December 19, 2025
Host: Dave Bittner
Guest: Nitei Milner, CEO of Orion Security
This episode delivers a brisk, comprehensive rundown of the day’s most pressing cybersecurity developments—from legislative moves and global threats to technical vulnerabilities and the evolving landscape of data loss prevention (DLP). The centerpiece is an interview with Nitei Milner, CEO of Orion Security, exploring urgent concerns about data leaking into AI tools and how modern DLP is transforming to keep up. The episode makes clear: encryption and executive action are converging as never before at every level of cybersecurity practice and policy.
Topic: The crisis (and opportunity) of data leaking into AI tools: How LLMs are reshaping DLP
Modern DLP with LLMs:
Tangible Impact:
Nuance & Learning: