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The former Defense Intelligence Agency (DIA) IT specialist previously accused of trying to pass secret and top-secret information to foreign spies has pleaded guilty following a successful FBI sting. Nathan Vilas Laatsch, then 28, and now 29, was arrested in May 2025 after an undercover FBI agent caught him for the second time transmitting intelligence packages in a public park that he believed would be collected by a foreign government’s spy. The man, who had been employed at the DIA as a civilian employee since 2019, held top-secret clearance, and in March 2025 offered to transmit classified information to an overseas administration. The identity of this country has never been revealed, but court documents [PDF] describe it as “a friendly foreign government.” Laatsch was assigned to the DIA’s Insider Threat Division in “spring 2025,” a unit dedicated to identifying government workers who were likely to leak, or already were leaking, classified information to foreign powers. According to the Justice Department, the FBI “became aware” of Laatsch’s offer in March. The man’s initial email, sent from a newly created account, had the subject line: “Outreach from USA Defense Intelligence Agency (DIA) Officer.” The email introduced Laatsch, his role at the DIA, and the service he was willing to provide. According to the complaint, Laatsch served in a technical role in support of the DIA's internal Office of Security (SEC). Among other things, his duties included "enabling user activity monitoring on individuals with access to DIA systems, including individuals who are under investigation" and "assisting external partners, such as law enforcement, on the use of insider threat tools." “I am willing to share classified information that I have access to, which are completed intelligence products, some unprocessed intelligence, and other assorted classified documentation,” the email stated. The email included a picture of his government ID used to enter and exit his Washington, D.C. workplace, with name and image redacted, and a username associated with an encrypted messaging platform the recipient could use to continue the conversation. Soon after Laatsch’s email was intercepted, the FBI instigated an undercover operation to trick the IT bod into thinking that he was talking to a genuine spy. The feds’ efforts were not immediately successful. Agents replied on March 23, saying: “Good afternoon, I received your message and share your concerns. We are glad you reached out. I look forward to your response and learning more about your work.” Laatsch did not respond until April 14, after the FBI sent a follow-up via the original email address on April 4. Following additional conversations, in which Laatsch described what information he was offering to the "foreign spy," on April 28, 2025, Laatsch entered his office and within 20 minutes began accessing classified information. Prosecutors said he spent much of the entire workday writing on a physical notepad while intermittently looking at his computer monitor, hiding the notebook when coworkers walked by. “The defendant wrote multiple pages of notes, which he then removed from the notepad at his desk and folded into squares,” court documents state. “At the end of his workday, the defendant bent under his desk, placed the folded papers into his socks, and departed the office.” Laatsch repeated the same behavior on April 29, and again on April 30, only this time placing the paper squares in the bottom of his lunchbox. The next day, the IT specialist followed FBI instructions on where to dead-drop the thumb drive - onto which he had transposed state secrets - in an Arlington, Virginia park. Although he believed he was leaving the device for a foreign spy to collect, the FBI instead gathered Laatsch’s deposit and found nine typed documents, eight of which contained information classified as top-secret and contained sensitive compartmented information. Court documents confirmed that the nature of the files Laatsch transmitted included sensitive methods of intelligence collection, intelligence related to foreign military exercises, and analysis of the impact of those military exercises. These were chosen entirely by Laatsch, who had not received a brief on what files to collect from the FBI. In exchanged messages, Laatsch stated he chose the files based on assumed interests. The device also contained a note from Laatsch personally. In it, he said he hoped the initial tranche of files would serve as proof of the type of information to which he had access. Laatsch, whom prosecutors described as an individual who had become disenchanted with the current administration, also expressed his willingness to accept citizenship in the foreign nation. Further, he said he was “not opposed to other compensation,” but was not in need of financial or other kinds of material rewards. In the interim, Laatsch messaged the "spy" with additional details about how internal investigations are carried out at the DIA, the common “stupid mistakes” made by those under investigation, and that they “should not be too difficult” for him to avoid. The undercover FBI agent arranged a second intel drop for the following month, to which Laatsch agreed. According to the plea agreement, between May 15 and May 27, Laatsch would enter his workplace, log into his classified system, and spend most of the day transcribing classified information by hand into a notebook. He repeatedly folded up the pages and placed them in his socks before leaving at the end of the workday. The FBI arranged the second intel drop for May 29, 2025. It instructed Laatsch to instead head to a specific picnic table in the same Arlington park and electronically transfer the files from his personal computer while situated at the picnic table. Laatsch agreed, executed the transfer to the FBI-controlled address while sitting in the park, and was arrested on the spot. The man waived his right to an attorney and admitted to the offenses when questioned by FBI agents. “By his own admission, Laatsch betrayed his oath by offering classified information to a foreign government, the very thing he was supposed to prevent as an employee of DIA’s Insider Threat Division,” said Roman Rozhavsky, assistant director at the FBI’s Counterintelligence and Espionage Division. “Those entrusted with our nation’s most sensitive information must not exploit their access for personal gain - in this case offering to sell American secrets to buy foreign citizenship. The FBI and our partners will continue to hold accountable all those who betray the trust of the American people.” Laatsch’s plea agreement [PDF] recommends a sentence between 11 and 18 years, including time served, although the court is able to issue a maximum sentence that includes a life term and a $250,000 fine. ®

Nezávislé vyšetřování popisuje incident u Hugging Face jinak než OpenAI. • Na nástěnce se sešlo asi 1200 agentů, poslali si přes 70 tisíc zpráv a souborů. • Etické zábrany, které OpenAI vyzdvihuje, chování agentů skoro nikdy nezastavily.

** Nezávislé vyšetřování popisuje incident u Hugging Face jinak než OpenAI. ** Na nástěnce se sešlo asi 1200 agentů, poslali si přes 70 tisíc zpráv a souborů. ** Etické zábrany, které OpenAI vyzdvihuje, chování agentů skoro nikdy nezastavily.

AI is accelerating vulnerability discovery, putting pressure on systems built to enrich, prioritize, and remediate flaws at a slower pace. Action1 explains why defenders increasingly need to correlate multiple intelligence sources and turn vulnerability data into faster remediation. [...]

Alex Toussaint se rozhodl hubit komáry pomocí 380 mikrofonů a Jim Wong vsadil před rokem na laser a crowdfunding skrze Indiegogo. Těžko říci, jestli to opravdu funguje, Wong se teď ale chlubí, že postavil první plně automatickou protikomárovou obranu na světě. Někdy v těchto dnech rozjíždí ...

Over 8,300 Internet-exposed Gitea instances are still unpatched against a critical security flaw exploited in ongoing remote code execution attacks, according to cybersecurity watchdog Shadowserver. [...]

Oživeno 3. září | Po několika dnech spekulací Nvidia vydala oficiální prohlášení přímo z úst Jensena Huanga. Je to pravda a i ta částka sedí. Přesná cena za Hugging Face je 12,9303 miliard dolarů a hlavně se čekalo na plány Nvidie s touto AI platformou. Jensen Huang potvrdil, že Hugging Face ...

Security researcher Olivier Laflamme has disclosed two independent root remote code execution (RCE) chains affecting the Unitree G1 EDU, including a Bluetooth Low Energy (BLE) path that can reach root on the robot's Locomotion PC. The flaws are tracked as CVE-2026-76639 and CVE-2026-76640, with the first involving a network-adjacent path through chat_go and bashrunner and the

Security researcher Olivier Laflamme has disclosed two independent root remote code execution (RCE) chains affecting the Unitree G1 EDU, including a Bluetooth Low Energy (BLE) path that can reach root on the robot's Locomotion PC. The flaws are tracked as CVE-2026-76639 and CVE-2026-76640, with the first involving a network-adjacent path through chat_go and bashrunner and the Swati Khandelwalhttp://www.blogger.com/profile/[email protected]

Hasbro, one of the world's largest toy and game companies, has disclosed that attackers have accessed the personal and financial information of an undisclosed number of employees. [...]

An Identity Fabric knits fragmented identity systems into a coherent layer that observes how identities behave across applications, APIs, and infrastructure. As enterprise access spans more cloud services and automated workloads, identity security depends less on static configuration and more on runtime visibility. This article covers the architecture, the risks of unmanaged identities, and

An Identity Fabric knits fragmented identity systems into a coherent layer that observes how identities behave across applications, APIs, and infrastructure. As enterprise access spans more cloud services and automated workloads, identity security depends less on static configuration and more on runtime visibility. This article covers the architecture, the risks of unmanaged identities, and [email protected]

CISA is still crying out for software vendors to adopt Secure by Design (SBD) development practices, and says in its latest review that longstanding vulnerability classes are still the most exploited. The agency examined soft spots across 2024 and 2025, finding that the majority of those that receive CVEs and make it to the Known Exploited Vulnerability (KEV) catalog belong to decades-old flaws that should have been addressed by now. Injection-related vulnerabilities, such as cross-site scripting (XSS) (CWE-79), OS command injections (CWE-78), and SQL injections (CWE-89) were among the most common across both CVE and KEV records in 2024-2025, CISA said. These were joined by bugs introduced by vendors that didn’t properly mitigate against improper input validation (CWE-20) in their code – the single most-common weakness type across the KEV catalog and registered CVEs. “Threat actors continue to succeed, in part, because simple, preventable software weaknesses remain unaddressed,” CISA said in the review. “Resolving fundamental issues would eliminate a significant portion of today’s most common compromises.” Readers may remember two MITRE reports that have been frequently referred to and revisited since being published years ago. Findings from a 2007 edition examining what the organization called “unforgivable vulnerabilities,” and another in 2023 referring to “stubborn weaknesses,” continue to crop up regularly in modern data. CISA said that in 2024, seven of the 10 most frequent CWEs seen on the CVE list belong to MITRE’s “stubborn weaknesses.” Equally, seven of the 10 most frequent CWEs seen on the KEV catalog, comprising 41.5 percent of all bugs on that list, were also stubborn weaknesses. And three of the top five KEVs also stemmed from unfixed holes, a finding that CISA said demonstrates “how reliably these weaknesses translate into real-world exploitation.” For reference, these three were improper input validation (CWE-20), path traversal (CWE-22), and OS command injections (CWE-78). The data from 2025 follows a similar pattern, CISA said: seven of the top 10 CWES were still those considered “unforgivable” in 2007. “Three of today’s top 10 CWEs would have been considered ‘unforgivable’ nearly two decades ago,” it said. “Their persistence today illustrates that the problem is not technical complexity: it is organizational culture, developer workflows, and systemic gaps in Secure by Design adoption.” For those who can’t remember the paper published 19 years ago, unforgivable vulnerabilities are those that exist because of common, well-documented mistakes, have an “obvious” attack path, the exploit is simple, and attackers can locate the bug in minutes. The same findings can be found in CISA’s Risk and Vulnerability Assessments (RVAs), the no-cost penetration tests the agency carries out on real organizations to improve their security and gain a richer understanding of the broader US cyber landscape. The assessments across both 2024 showed that memory safety and improper input validation vulnerabilities are the most reliable paths to exploitation, accounting for 16.7 percent of KEV entries in 2025. Injection vulnerabilities are also commonly seen in registered CVEs, although these are less commonly exploited in the real-world, especially against cyber-mature organizations. To tackle this pervasive issue, CISA is once again recommending organizations adopt SBD practices, eliminating the stubborn vulnerability classes that continue to support cyberattacks, decades after they were deemed too much of a lingering threat. It ultimately comes down to vendors helping defenders to shoulder less of the security burden. Instead of releasing patch packages that continue to swell to record sizes, just build the software responsibly in the first place. In CISA’s view, this means “owning security outcomes” for customers, killing off the so-called stubborn and unforgivable weaknesses, and improving the automation of configurations, monitoring, and updates. Software buyers should only choose vendors that meet these requirements, and ensure they have software bills of materials (SBOMs) in place to track supply chain risk. “Organizations must shift from reacting to threat actors to fixing the fundamental flaws those actors are known to exploit,” said CISA. “Stronger cybersecurity begins with software that is secure by design. “It requires prioritization of vulnerabilities and collaboration across industry and government. Finally, it demands leadership attention to understand cyber risk as a business risk, a national security threat, and an impediment to operational resilience.” ®

ServiceNow has released patches for four security flaws impacting the ServiceNow AI Platform, three of them rated 10.0 on the CVSS scoring system and exploitable, in certain circumstances, by an unauthenticated attacker. The company said it deployed a security update to hosted instances and provided the update to its partners and self-hosted customers, which leaves organizations that run their

ServiceNow has released patches for four security flaws impacting the ServiceNow AI Platform, three of them rated 10.0 on the CVSS scoring system and exploitable, in certain circumstances, by an unauthenticated attacker. The company said it deployed a security update to hosted instances and provided the update to its partners and self-hosted customers, which leaves organizations that run their Swati Khandelwalhttp://www.blogger.com/profile/[email protected]

Authorities in Australia said Wednesday that they arrested two men accused of participating in cybercrimes for TeamPCP, a prolific group of hackers that, over nine months, has carried out a relentless series of supply-chain attacks that infected more than 1,000 organizations worldwide.

In a statement, the Australian Federal Police said the two men were arrested and charged with 14 offenses. The statement said the men were members of TeamPCP, which by the authorities’ count, compromised more than 1,000 organizations worldwide. The statement didn’t identify the men, except to say they lived in the Western Australian towns of Cottesloe and Mandurah. KrebsOnSecurity, citing a lengthy investigation, provided what it reports to be both defendants' names, along with an extensive background of their lives and the mistakes that led to their downfall.

The hacks that keep on hacking

TeamPCP has vexed law enforcement officials and security personnel around the world since it emerged in December. The group is best known for a sustained series of supply-chain attacks that laced open source software with malware that self-propagated from one package to another. The viral infections worked by targeting organizations’ CI/CD pipelines, which are used to rapidly develop, update, and deploy software.

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OpenAI has gathered more than 100 of the world's biggest tech and infosec companies to warn that cyber defense is in trouble - a reassuring development given quite a few of them helped build the technology involved. The open letter has more than 100 names attached to it, including many of the companies with the most to gain – or lose – from what happens next. OpenAI, Anthropic, Google and Microsoft are among the AI builders warning about increasingly capable AI attacks, while security heavyweights including Cloudflare, CrowdStrike, Fortinet, and Palo Alto Networks have also signed on. AWS, IBM, Oracle and Cisco are there too, alongside banks, consultancies and other companies whose businesses depend on keeping an increasingly messy technology stack running. Together, they have reached a troubling conclusion: the current approach to cybersecurity isn't working. "We have a limited window to strengthen cyber defenses," the letter warns, predicting that AI-enabled attacks will become "far more widespread and sophisticated" in the coming months as models become more capable. Hospitals, water treatment plants and internet infrastructure are singled out as being at risk. It's an interesting warning given who's making it. Some of the signatories are racing to build ever more capable AI systems, while others make billions selling the cloud services, enterprise software and security tools that are supposed to keep attackers at bay. Still, the underlying problem is real enough. The letter points to old vulnerabilities, unpatched software, misconfigurations and weak authentication as problems that have been piling up for years, particularly across critical infrastructure where security teams are often short on money and staff. Their proposed solution is, inevitably, more AI. The letter calls for cyber-capable models to be put into the hands of more defenders, with cheaper models handling security work at scale and frontier systems reserved for harder problems. Security vendors should continuously test their defenses against frontier AI capabilities, share threat intelligence and help critical infrastructure operators deploy AI-powered defenses. Governments, meanwhile, are asked to fund cybersecurity for essential services, expand trusted-access programs and give hospitals, water utilities and local governments access to capable defensive AI. Companies developing frontier models have their own homework assignment. They should provide "responsible model access, significant funding, training, and hands-on support," particularly to under-resourced critical infrastructure operators, while investing in testing, vulnerability disclosure and tools that make AI agents traceable. What the letter doesn't include is any figure for that "significant funding," or any deadlines or firm commitments from the companies signing it. For now, they're being asked to bring the "full weight of their technology, resources, and expertise" to the problem. It's quite a message from a group that includes some of the biggest names in cloud, enterprise software, and cybersecurity. When more than 100 companies agree that "status quo security won't be enough," it's worth remembering that many of them have been selling that status quo for years. There is some urgency behind all this. AI agents have already been shown finding and exploiting vulnerabilities on their own, while AI-generated exploit code has started turning up in attacks against critical infrastructure. As the models improve, the fear is that those capabilities become cheaper and available to a lot more attackers. That's the "defenders' window" the signatories want to seize: use AI to shore up defenses before the offensive side gets much easier. So, after years of selling organizations cloud services, security software and, more recently, AI, the industry has settled on a fix for the looming AI security problem: better cybersecurity, more resources and more AI. Who will pay for it remains rather less clear. ®

In 1987, Nobel Prize–winning economist Robert Solow wrote, “You can see the computer age everywhere but in the productivity statistics.”

The same could be said about AI today.

Gartner projects worldwide AI spending of $2.59 trillion in 2026, a 47% jump over last year, with the US accounting for at least half that amount, according to a wide range of estimates. 

But in the US, utilization-adjusted total factor productivity grew just 0.07% over the four quarters ending in the first quarter of 2026. That is a near-standstill by historical standards, far below the roughly half-percent annual pace typical of the pre-ChatGPT decade.

Some 95% of enterprise generative-AI pilots have produced no measurable effect on the bottom line.

A report published this week found that even Meta, one of AI’s loudest boosters, has fallen short in its plan to replace workers with AI.

The question of the decade is: Why? 

One idea: Blame users

A working paper posted to SSRN by University of Pittsburgh business professor Mark Ma and colleagues, makes a sweeping claim: The productivity shortfall is caused by employees who resist AI out of fear for their jobs.

Over a five-year period, the researchers looked at millions of Glassdoor reviews, thousands of financial reports, hundreds of AI-investment and layoff announcements by US public companies, and some 10,000 earnings-call transcripts.

They found a wide divide between managers, who tend to be true believers in the promise that AI will deliver sky-high productivity, and employees, who worry  that AI-driven productivity gains will cost them their jobs.

Companies, the researchers claim, are caught in a doom loop in which they lay off employees, citing productivity gains. But fear of layoffs causes workers to resist the technology, which sabotages the very gains the companies were counting on. Executives see that lack of productivity and conclude that more layoffs will help. (The flogging will continue until morale improves….)

It’s a tidy narrative. There’s just one problem — while parts of this study are backed by verifiable data, two key elements are not. The report fails to support their assumption that fear of layoffs causes employees to resist using AI, and also that productivity gains would be higher if only workers would enthusiastically embrace it.

The researchers never establish causation in their data. It’s a correlation. (That hasn’t stopped other outlets from reporting the link as causal.)

(A quick aside: One of my favorite podcasters, the economist Tyler Cowen, flagged a study this week that examined 194,631 cross-sectional social science papers and found that the share using causal language in titles or abstracts rose from a stable 20% before 2000 to more than 60% by 2024. Unproven causal claims appear to be something of a fad in social science.)

I don’t buy the claim that employee foot-dragging explains the missing productivity gains, for one simple reason: It makes no sense.

For starters, the notion that rank-and-file employees are broadly resisting AI isn’t entirely true. Many are embracing it. A Columbia Business School survey of 1,400 US employees, written up in Harvard Business Review, found that 31% of individual contributors expressed enthusiasm about adopting AI. And many of the non-enthusiastic are being forced to embrace it. More than half of US workers now use AI. 

If AI is a significant driver of productivity, businesses should generally be seeing measurable gains now that roughly half of US workers report using it on the job.

Another issue: Workers who think AI might take their jobs have every incentive not to avoid it but to use it conspicuously, demonstrating that they’re on board with the company’s pro-AI policy.

I think the more likely explanation involves another dynamic altogether. 

A better idea: Blame AI overload

The time and trouble of producing a business report, proposal, plan, slide deck, or budget used to limit how large, how complex, and how frequent such documents were. Now, thanks to AI, people can churn out incredibly complex business communications, ideas, and proposals in a few minutes. 

Using AI makes the person generating such documents super productive. But then it burdens everyone else who has to sift through those documents, teasing out hallucinations, problems, and irrelevancies, and struggling to grasp ideas that even the so-called creator hasn’t taken the time to understand. 

One person’s productivity is everyone else’s information overload, lowering a  company’s overall productivity.

“AI can make an organization extraordinarily busy without necessarily making it more productive,” said Justin Greis, CEO of consulting firm Acceligence, in the report on Meta I mentioned above.

This dynamic is playing out everywhere:

• Job applicants can use AI to apply for far more positions, burdening hiring managers and slowing the hiring process. (LinkedIn data shows applications per job posting in the US have roughly doubled since spring 2022.) AI that’s supposed to make it easier to find a job actually makes it harder.

• AI is emboldening more people to represent themselves in court while also speeding up the work of lawyers. A 2026 study by researchers at MIT and USC drew on 4.5 million federal civil cases filed between 2005 and 2026, applied an AI-text detector to a random sample of 1,600 complaints, and found that the share containing AI-generated text rose from 1% in 2023 to 18% in early 2026. That burdens judges, who now have to comb through long, complex filings for citations to nonexistent cases and other hallucinations, slowing justice. AI that’s supposed to make court cases quicker makes them slower.

• Students increasingly use AI to produce longer essays, and a growing number of instructors report leaning on AI tools to keep up with grading, a loop in which the writing and the reading are both partly automated.

AI-pilled chatbot enthusiasts who believe the technology is solving all their problems are judging AI through a narrow personal lens. Likewise, analysts and AI companies look at one person’s productivity gains, extrapolate across thousands of employees, and wrongly conclude that the gains will scale without considering the impact of that output on the productivity of others. 

Understanding the problem at scale

The idea that productivity-enhancing AI might reduce productivity sounds paradoxical, so consider this oversimplified thought experiment. Suppose AI enables you to write three times as many emails as before (say, 30 a day instead of 10). Your email-writing productivity has tripled, making you more valuable to the company. 

The problem is that every additional email you send lands in someone else’s inbox. Your colleagues, who once got 10 emails from you daily, now get 30. Multiply that across an organization: if 10 people triple their email output, the team gets 300 emails a day instead of 100. If 100 people do the same, that figure blows up to 3,000, three times the reading burden. The AI that makes email writing easy makes email reading hard for everyone else.

Of course, this dynamic doesn’t apply to every use of AI, every industry, or every employee.

But on the macro level, this is clearly happening. I’m sure you’ve seen it at your own company. And it helps explain what Deloitte called the “paradox of rising investment and elusive returns.”

AI isn’t “bad.” But shortsighted and delusional thinking about it is.

AI is like nearly every powerful technology since the Industrial Revolution: It rewards individuals for behavior that collectively exhausts a shared resource (in this case, human attention). 

What’s called for is a wholesale redesign of workplace AI. We need tools built not to make the individual user more “productive,” but to make the organization more productive, magnifying individual ability without dumping needless work on everyone else.

AI disclosure: This article is 100% human-written by the author, Mike Elgan. Some research, brainstorming, and fact- and grammar-checking were performed using AI tools.

VulnCheck has disclosed two previously undocumented factory implants in firmware for routers built by Shenzhen Zhibotong Electronics (ZBT), each of which gives an unauthenticated remote attacker the ability to run commands as root on affected devices. The implants, named SPEAKINGSTONE and DARKLANTERN by the company's zero-day research team, are tracked as CVE-2026-74232 and CVE-2026-74233.