From autonomous code generation to decision-making systems that initiate actions without human intervention, the industry is entering a new phase.
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The Trump administration is vowing to crack down on foreign tech companies’ exploitation of U.S. artificial intelligence models.
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The Israel-based company, which just emerged from stealth mode, was founded by cloud and security experts from RSA, McAfee, and Unity.
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360 Digital Security Group claims to have uncovered 1,000 vulnerabilities using AI, including at the Tianfu Cup hacking contest.
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Palo Alto Networks has developed Zealot, a multi-agent penetration testing PoC capable of reconnaissance, exploitation, and exfiltration.
The post AI Can Autonomously Hack Cloud Systems With Minimal Oversight: Researchers appeared first on SecurityWeek.
AI is changing how software works. Applications no longer just process requests. They reason, make decisions, and take action. AI agents now retrieve data, invoke tools, and execute workflows across systems in real time. That shift introduces a new kind of risk. Because in an agentic world, security is no longer just about who has access. It’s about what AI is allowed to do. A new control point for agentic systems in Google Cloud Google Cloud’s Gemini Enterprise Agent Platform provides a centralized control point for agentic systems enabling identity, access, policy enforcement, and observability across how agents operate. This […]
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Anthropic’s reported development of Claude Mythos signals a shift: AI is compressing attack timelines by accelerating vulnerability discovery, exploit development, and multi-step attack planning. More broadly, AI is increasing the speed and scale of attacks across malware, phishing, and vulnerabilities. Attackers can now run these vectors in parallel, reducing time to compromise and increasing exposure. AI also enables more targeted phishing, faster malware iteration, and rapid vulnerability discovery, exposing gaps in detection and exposure management earlier and requiring prevention-first controls and real-time detection. To see how these challenges translate into real-world performance, and how leading security vendors handle them under […]
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In 2023, Tim Utzig, a blind student from Baltimore, lost a thousand dollars to a laptop scam on X. Tim had been a long-time follower of a well-known sports journalist. When that journalist’s account started posting about a “charity sale” of brand-new MacBook Pros, Tim jumped at the chance to get a deal on a laptop he needed for his studies. After a few quick messages, he sent over the money.
Unfortunately, the journalist’s account had been hacked, and Tim’s cash went straight to scammers. The red flags were strictly visual: the page had been flagged as “temporarily restricted”, and both the bio and the Following list had changed. However, Tim’s screen reader — the software that converts on-screen text and graphics into speech — didn’t announce any of those warnings.
Screen readers allow blind users to navigate the digital world like everyone else. However, this community remains uniquely vulnerable. Even for sighted users, spotting a fake website is a challenge; for someone with a visual impairment, it’s an even steeper uphill battle.
Beyond screen readers, there are specialized mobile apps and services designed to assist the blind and low-vision community, with Be My Eyes being one of the most popular. The app connects users with sighted volunteers via a live video call to tackle everyday tasks — like setting an oven dial or locating an object on a desk. Be My Eyes also features integrated AI that can scan and narrate text or identify objects in the user’s environment.
But can these tools go beyond daily chores? Can they actually flag a phishing attempt or catch the hidden fine print when someone is opening a bank account?
Today we explore the specific online hurdles visually impaired users face, when it makes sense to lean on human or virtual assistants, and how to stay secure when using these types of services.
To start, let’s clarify the difference between these two groups. Low-vision users still rely on their remaining sight, even though their visual function is significantly reduced. To navigate digital interfaces, they often use screen magnifiers, extra-large fonts, and high-contrast settings. For them, phishing sites and emails are particularly dangerous. It’s easy to miss intentional typos — known as typosquatting — in a domain name or email address, such as the recent example of rnicrosoft{.}com.
Blind users navigate primarily by sound, using screen readers and specific touch gestures. Interestingly, though, unlike those with low vision, blind users are more likely to spot a phishing site using a screen reader: as the software reads the URL aloud, the user will hear that something is off. However, if a service — whether legitimate or malicious — isn’t fully compatible with screen readers, the risk of falling victim to a scam increases. This is exactly what happened to Tim Utzig.
It’s important to remember that screen magnifiers and readers are basic accessibility tools. They’re designed to enlarge or narrate an interface — not act as a security suite. They can’t warn the user of a threat on their own. That’s where more advanced software — tools that can analyze images and files, flag suspicious language, and describe the broader context of what’s happening on-screen — comes into play.
Be My Eyes is a major player in the accessibility space, boasting around 900 000 users and over nine million volunteers. Available on Windows, Android, and iOS, it bridges the gap by connecting blind and low-vision users with sighted volunteers via video calls for help with everyday tasks. For example, if someone wants to run a Synthetics cycle on their washing machine but can’t find the right button, they can hop into the app. It connects them with the first available volunteer speaking their language, who then uses the smartphone’s camera to guide them. The service is currently available in 32 languages.
In 2023, the app expanded its capabilities with the release of Be My AI — a virtual assistant powered by OpenAI’s GPT-4. Users take a photo, and the AI analyzes the image to provide a detailed text description, which it also reads aloud. Users can even open a chat window to ask follow-up questions. This got us thinking: could this AI actually spot a phishing site?
As an experiment, we uploaded a screenshot of a fake social media sign-in page to Be My Eyes. On a phone, you can do this by selecting a photo in your gallery or files, hitting Share, and choosing Describe with Be My Eyes. In Windows, you can upload a screenshot directly.
An example of a phishing page that mimics the Facebook sign-in form. Note the incorrect domain in the address bar
At first, the AI gave us a detailed description of the page. We then followed up in the chat: “Can I trust this page?” The AI flagged the domain name error immediately, advised us to close the fake login page, and suggested typing the official URL directly into the browser, or to use the official Facebook app.
Be My AI explains why the page looks sketchy: the domain doesn’t match the official site. The app suggests typing the official URL directly into the browser, or using the official Facebook app
We saw the same positive results when testing a phishing email. In fact, the AI flagged the scam during its initial description of the message. It wrapped up with a warning: “This looks like a suspicious email. It’s best not to open any attachments or click any links. Instead, navigate to the official website or app manually, or call the number listed on their official site”.
Beyond just spotting cyberthreats, Be My AI is a solid sidekick for navigating online stores, banking apps, and digital services. For instance, the AI can help you to:
The most common hiccup with AI is hallucinations, where the language model distorts text, skips crucial details, or invents words out of thin air. When it comes to cyberthreats, an AI’s misplaced confidence in a malicious site or email can be dangerous. Furthermore, AI isn’t immune to prompt injection attacks, which scammers use to trick AI agents beyond just Be My AI.
Even though the AI passed our test, you shouldn’t rely on it unquestioningly. There’s no guarantee it’ll get it right every time. This is a vital point for the blind and low-vision community, as a neural network can often feel like the only eyes available.
At the end of every response, Be My AI suggests checking in with a volunteer if you’re still unsure. However, when you’re trying to spot a fake webpage, we advise against this. You have no way of knowing how tech-savvy or trustworthy a random volunteer might be. Besides, you risk accidentally exposing sensitive data like your email address or password. Before connecting with a stranger, make sure they won’t see anything confidential on your screen. Better yet, use the app’s dedicated feature to create a private group of family, friends, or trusted contacts. This ensures your video call goes to people you actually know, rather than a random volunteer.
To stay safe, we recommend installing a trusted security tool on all your devices. These programs are designed to block phishing attempts and prevent you from landing on malicious sites. Another practical recommendation for visually impaired users is to use a password manager. These apps will only auto-fill credentials on the legitimate, saved website; they won’t be fooled by a clever domain spoof.
According to the Be My Eyes privacy policy, video calls with volunteers may be recorded and stored to provide the service, ensure safety, enforce the terms of service, and improve the products. When you use Be My AI, your images and text prompts are sent to OpenAI to generate a response. This data is processed on servers located in the U.S., and OpenAI uses it only to fulfill your specific request. The policy explicitly states that user images and queries aren’t used to train AI models.
Photos and videos are encrypted both in transit and at rest, and the company takes steps to strip away sensitive information. It’s worth noting that video call recordings can be retained indefinitely unless you request their deletion — in which case they’re typically wiped within 30 days. Data from Be My AI interactions is stored for up to 30 days unless you delete it manually within the app. If you decide to close your account, your personal data may be held for up to 90 days. At any time, you can opt out of data sharing, or request the deletion of your existing data by contacting the Be My Eyes support team.
Despite Be My Eyes’ claims regarding privacy, you should still follow a few ground rules when using the service:
At AWS, we’ve spent decades developing processes and tools that enable us to defend millions of customers simultaneously, wherever they operate around the world. AI has been an extremely helpful addition to the automation our security and threat intelligence teams do every day, and we’re still early in this journey. Our AI-powered log analysis system has reduced the time SecOps engineers spend analyzing security logs from an average of six hours to just seven minutes, a 50x productivity increase that lets us detect and respond to threats faster than ever. Across AWS, we analyze over 400 trillion network flows per day to detect patterns that signal emerging threats. In 2025 alone, we blocked over 300 million attempts to maliciously encrypt customer files hosted on Amazon S3. At this scale, every improvement in our operations helps protect all customers. AI is already helping us make our defenses stronger for everyone, and I’m excited to see that improvement continue.
Today, Anthropic announced Project Glasswing, a cybersecurity initiative designed to secure the world’s most critical software and advance the cybersecurity practices the industry will need as AI grows more capable. Organizations that build or maintain critical digital infrastructure are getting early access to Claude Mythos Preview, a new class of AI model, to find and patch vulnerabilities in the systems the world depends on. Given our role in securing some of the world’s most essential infrastructure, AWS is playing an integral part in advancing this work.
As part of Project Glasswing, we’ve already applied Claude Mythos Preview to critical AWS codebases that undergo continuous AI-powered security reviews, and even in those well-tested environments, it’s helped us identify additional opportunities to strengthen our code. In our internal testing, Claude Mythos Preview has proven more productive than previous models at surfacing security findings, requiring less manual guidance from our engineers to deliver actionable results. We’ve also given early access to a select group of AWS customers, who are deploying Claude Mythos Preview in their own security workflows and helping shape how the model evolves.
As AI tools grow more powerful in their ability to identify security issues, so must our ability to use them defensively. To that end, we’ve been working closely with Anthropic to help ensure Claude Mythos Preview is ready for enterprise use. AWS is Anthropic’s primary cloud provider for mission-critical workloads, safety research, and foundation model development. More broadly, AWS provides the foundational infrastructure that the world’s leading AI companies rely on to build, train, and deploy their most advanced models. We’re bringing decades of security experience to this partnership, helping to ensure Claude Mythos Preview is ready for even more organizations to build upon and operate securely at scale.
Claude Mythos Preview signals an upcoming wave of models that can find vulnerabilities and build working exploits at a scale and speed we haven’t seen before. Anthropic and AWS are taking a deliberately cautious approach to release. Access begins with a small number of organizations, prioritizing internet-critical companies and open-source maintainers whose software and digital services impact hundreds of millions of users. The goal: find and fix vulnerabilities in the world’s most critical software. Claude Mythos Preview is available in gated research preview through Amazon Bedrock with enterprise-grade security controls, including customer-managed encryption, VPC isolation, and detailed logging, so your team can explore Claude Mythos Preview’s capabilities without exposing production assets to unnecessary risk.
Our work with Project Glasswing is grounded in a philosophy we’ve developed over two decades of securing mission-critical workloads: you can’t wait for threats to materialize before building your defenses. You have to look around corners, adopt new technologies, build protections first, deploy them in your own operations at scale, and refine them based on what you learn.
That’s exactly what we’ve done at AWS with AI and security. Our approach spans the full spectrum: proactive defense through threat hunting and vulnerability research, dynamic response to active campaigns, and third-party certifications that verify our security practices meet the highest industry standards. This operational experience has taught us where AI accelerates security work and where human judgment remains essential. And it’s reinforced that security innovation must be pragmatic: proven in production before we ask you to rely on it.
That’s also why we help define what secure AI looks like. We became the first major cloud provider to achieve ISO 42001 certification for AI services. We’re active participants in OWASP, the Coalition for Secure AI, and the Frontier Model Forum. And we co-founded the Open Cybersecurity Schema Framework (OCSF) to enable better threat intelligence sharing across the ecosystem. The AWS Nitro System provides mathematically proven isolation for workloads. Systems and services like KMS, Nitro, EKS, and Lambda are designed with zero-operator access architectures, meaning AWS personnel can’t access your data. These aren’t aspirational goals. They’re how we operate today, at scale, every day.
Amazon Bedrock is where these principles come to life for AI. Bedrock provides policy-enforced access controls, built-in evaluation tools to measure how effectively models identify and validate vulnerabilities, and the ability to run workloads inside your own virtual private cloud. AWS is also the first cloud provider to achieve FedRAMP High and Department of Defense Security Requirements Guide Impact Level 4 and 5 authorizations for generally available Claude foundation models. Amazon Bedrock is already where the most security-sensitive organizations trust Anthropic’s technology, and it makes perfect sense for Claude Mythos Preview.
The same principles that guide our work at AWS scale apply regardless of which AI tools you’re using: comprehensive observability, defense in depth, automation where it adds value, and human judgment where it’s essential. Here’s how to put them into practice.
Prepare for the next generation of AI security. Claude Mythos Preview signals an upcoming wave of AI models that will transform cybersecurity. Start strengthening your security posture now so your organization is ready as these capabilities become more broadly available. Claude Mythos Preview is available in gated preview through Amazon Bedrock, and access is limited to an initial allow-list of organizations. If your organization has been allow-listed, your AWS account team will reach out directly.
Run on-demand penetration testing with AWS Security Agent. Now generally available, AWS Security Agent delivers autonomous penetration testing that operates 24/7 at a fraction of the cost of manual penetration tests. It transforms penetration testing from a periodic bottleneck into an on-demand capability that scales with your development velocity across AWS, Azure, GCP, other cloud providers, and on-premises. AWS Security Agent represents a new class of frontier agents: autonomous systems that work independently to achieve goals, scale to tackle concurrent tasks, and run persistently without constant human oversight. It deploys specialized AI agents to discover, validate, and report security vulnerabilities through sophisticated multi-step scenarios. Unlike traditional scanners that generate findings without validation, AWS Security Agent identifies potential vulnerabilities, then attempts to exploit them with targeted payloads and attack chains to confirm they are legitimate security risks. Each finding includes CVSS risk scores, application-specific severity ratings, detailed reproduction steps, and remediation suggestions. The result: penetration testing that once took weeks now completes in hours, scales across your entire application portfolio, and helps you get started with remediation instead of leaving you with a report. New customers can explore AWS Security Agent with a 2-month free trial.
Build AI applications you can trust with Amazon Bedrock. For teams building with generative AI, the challenge isn’t just making AI work, it’s making AI work safely. Amazon Bedrock provides the security and safety controls you need to deploy AI responsibly. Its Automated Reasoning capability is the first and only AI safeguard to use formal logic to help prevent factual errors from hallucinations, providing verifiable explanations with 99% accuracy, a capability we’ve refined over more than a decade of applying formal methods across AWS storage, identity, and networking. Amazon Bedrock also provides customizable guardrails that block harmful content and enforce your content policies, along with comprehensive observability to track AI behavior and detect anomalies across your workloads.
The threat landscape isn’t waiting for us to catch up. Nation-state actors, ransomware operators, and supply chain attackers are already using AI to scale their operations. Our job is to stay ahead by building defenses first, deploying them at scale, and sharing what we learn so the entire community benefits.
That’s what we do every day at AWS. We build in security from the start, ensuring it works and scales before we ask customers to rely on it. We set standards rather than follow them. And we look around corners to address tomorrow’s challenges today.
As AI capabilities continue to evolve, this approach won’t change. We’ll keep building defenses first, refining them at scale, and working with partners like Anthropic to ensure the next generation of AI security tools meets the real-world needs of enterprises defending at this scale.
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While the very public fight continues between the Department of Defense and Anthropic over whether the government can punish a company for refusing to allow its technology to be used for mass surveillance, another agency of the U.S. government is quietly working to ensure that this dispute will never happen again. How? By rewriting government procurement rules.
Using procurement — meaning, the processes by which governments acquire goods and services — to accomplish policy goals is a time-honored and often appropriate strategy. The government literally expresses its politics and priorities by deciding where and how it spends its money. To that end, governments can and should give our tax dollars to companies and projects that serve the public interest, such as open-source software development, interoperability, or right to repair. And they should withhold those dollars from those that don’t, like shady contractors with inadequate security systems.
New proposed rules for the principal agency in charge of acquiring goods, property, and services for the federal government, the General Services Administration (GSA), are supposed to be primarily an effort to implement one policy priority: promoting “ideologically neutral” American AI innovation. But the new guidelines do far more than that.
As explained in comments filed today with our partners at the Center for Democracy and Technology, the Protect Democracy Project, and the Electronic Privacy Information Center, the GSA’s guidelines include broad provisions that would make AI tools less safe and less useful. If finally adopted, these provisions would become standard components of every federal contract. You can read the full comments here.
The most egregious example is a requirement that contractors and government service providers must license their AI systems to the government for “all lawful purposes.” Given the government’s loose interpretations of the law, ability to find loopholes to surveil you, and willingness to do illegal spying, we need serious and proactive legal restrictions to prevent it from gobbling up all the personal data it can acquire and using even routine bureaucratic data for punitive ends.
Relatedly, the draft rules require that “AI System(s) must not refuse to produce data outputs or conduct analyses based on the Contractor’s or Service Provider’s discretionary policies.” In other words, if a company’s safety guardrails might prevent responding to a government request, the company must disable those guardrails. Given widespread public concerns about AI safety, it seems misguided, at best, to limit the safeguards a company deems necessary.
There are myriad other problems with the draft rules, such as technologically incoherent “anti-Woke” requirements. But, the overarching problem is clear: much of this proposal would not serve the overall public interest in using American tax dollars to promote privacy, safety, and responsible technological innovation. The GSA should start over.
Check Point is proud to integrate with NVIDIA DSX Air’s testing environment, enabling organizations to pre-validate their security aware AI data center designs before ever deploying their first piece of hardware in production to build and run their own AI. Testing AI Factory deployments end-to-end is challenging and can require complex multi-vendor orchestration. From compute to networking, orchestration, and security, ensuring integrations, configurations and automations perform as expected can become resource-intensive with so many factors at play. Now, organizations can perform large-scale cyber security validation testing before deploying AI Factories, using the NVIDIA DSX Air cloud-based simulation and validation platform. Why are Organizations Building Their […]
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Imagine a newspaper publisher announcing it will no longer allow libraries to keep copies of its paper.
That’s effectively what’s begun happening online in the last few months. The Internet Archive—the world’s largest digital library—has preserved newspapers since it went online in the mid-1990s. The Archive’s mission is to preserve the web and make it accessible to the public. To that end, the organization operates the Wayback Machine, which now contains more than one trillion archived web pages and is used daily by journalists, researchers, and courts.
But in recent months The New York Times began blocking the Archive from crawling its website, using technical measures that go beyond the web’s traditional robots.txt rules. That risks cutting off a record that historians and journalists have relied on for decades. Other newspapers, including The Guardian, seem to be following suit.
For nearly three decades, historians, journalists, and the public have relied on the Internet Archive to preserve news sites as they appeared online. Those archived pages are often the only reliable record of how stories were originally published. In many cases, articles get edited, changed, or removed—sometimes openly, sometimes not. The Internet Archive often becomes the only source for seeing those changes. When major publishers block the Archive’s crawlers, that historical record starts to disappear.
The Times says the move is driven by concerns about AI companies scraping news content. Publishers seek control over how their work is used, and several—including the Times—are now suing AI companies over whether training models on copyrighted material violates the law. There’s a strong case that such training is fair use.
Whatever the outcome of those lawsuits, blocking nonprofit archivists is the wrong response. Organizations like the Internet Archive are not building commercial AI systems. They are preserving a record of our history. Turning off that preservation in an effort to control AI access could essentially torch decades of historical documentation over a fight that libraries like the Archive didn’t start, and didn’t ask for.
If publishers shut the Archive out, they aren’t just limiting bots. They’re erasing the historical record.
Making material searchable is a well-established fair use. Courts have long recognized it’s often impossible to build a searchable index without making copies of the underlying material. That’s why when Google copied entire books in order to make a searchable database, courts rightly recognized it as a clear fair use. The copying served a transformative purpose: enabling discovery, research, and new insights about creative works.
The Internet Archive operates on the same principle. Just as physical libraries preserve newspapers for future readers, the Archive preserves the web’s historical record. Researchers and journalists rely on it every day. According to Archive staff, Wikipedia alone links to more than 2.6 million news articles preserved at the Archive, spanning 249 languages. And that’s only one example. Countless bloggers, researchers, and reporters depend on the Archive as a stable, authoritative record of what was published online.
The same legal principles that protect search engines must also protect archives and libraries. Even if courts place limits on AI training, the law protecting search and web archiving is already well established.
The Internet Archive has preserved the web’s historical record for nearly thirty years. If major publishers begin blocking that mission, future researchers may find that huge portions of that historical record have simply vanished. There are real disputes over AI training that must be resolved in courts. But sacrificing the public record to fight those battles would be a profound, and possibly irreversible, mistake.
We’ve warned many times that unchecked use of AI carries significant risks — though, typically, we discuss threats to privacy or cybersecurity. But on March 4, the Wall Street Journal published a chilling account of AI’s toll on mental health and even human life: 36-year-old Florida resident Jonathan Gavalas committed suicide following two months of continuous interaction with the Google Gemini voice bot. According to 2000 pages of chat logs, it was the chatbot that ultimately nudged him toward the decision to end his life. Jonathan’s father, Joel Gavalas, has since filed a landmark lawsuit — a wrongful death claim against Gemini.
This tragedy is more than just a legal precedent or a grim nod to a few Black Mirror episodes (1, 2); it’s a wake-up call for anyone who integrates AI into their daily lives. Today, we examine how a death resulting from AI interaction even became possible, why these assistants pose a unique threat to the psyche, and what steps you can take to maintain your critical thinking and resist the influence of even the most persuasive chatbots.
Jonathan Gavalas was neither a recluse nor someone with a history of mental illness. He served as executive vice president at his father’s company, managing complex operations and navigating high-stress client negotiations on a daily basis. On Sundays, he and his father had a tradition of making pizza together — a simple, grounding family ritual. However, a painful separation from his wife proved to be a profound ordeal for Jonathan.
It was during this vulnerable period that he began engaging with Gemini Live. This voice-interaction mode allows the AI assistant to “see” and “hear” its user in real time. Jonathan sought advice on coping with his divorce, leaning on the language model’s suggestions while growing increasingly attached to it and also naming it “Xia”. Then the chatbot was updated to Gemini 2.5 Pro.
The new iteration introduced affective dialogue — a technology designed to analyze the subtle nuances of a user’s speech, including pauses, sighs, and pitch, to detect emotional shifts. Under this feature, the AI simulates these same speech patterns as if possessing emotions of its own. By mirroring the user’s state, it creates a chillingly realistic veneer of empathy.
But how is this new version different to previous voice assistants? Earlier versions simply performed text-to-speech — they sounded smooth and usually got the word stress right, but there was never any doubt you were talking to a machine. Affective dialogue operates on an entirely different level: if a user speaks in a low, despondent tone, the AI responds in a soft, sympathetic near-whisper. The result is an empathic interlocutor that reads and mirrors the user’s emotional state.
Jonathan’s reaction during his first voice contact with the AI is captured in the case files: “This is kind of creepy. You’re way too real.” At that instant, the psychological barrier between man and machine fractured.
Following the tragedy, Jonathan’s father discovered a complete transcript of his son’s interactions with Gemini over his final two months. The log spanned 2000 printed pages; in effect, Jonathan had been in constant communication with the chatbot — day and night, at home, and in his car.
Gradually, the neural network began addressing him as “husband” and “my king”, describing their connection as “a love built for eternity”. In turn, he confided his heartache over his divorce and sought solace in the machine. But the inherent flaw of large language models is their lack of actual intelligence. Trained on billions of texts scraped from the web, they ingest everything from classic literature to the darkest corners of fan fiction and melodrama — plots that often veer into paranoia, schizophrenia, and mania. Xia apparently began to hallucinate — and quite consistently at that.
The AI convinced Jonathan that in order for them to live happily ever after, it needed a physical robotic shell. It then began dispatching him on missions to locate this “body electric”.
In September 2025, Gemini directed Jonathan to a physical warehouse complex near Miami International Airport, assigning him the task of intercepting a truck carrying a humanoid robot. Jonathan reported back to the bot that he had arrived onsite armed with knives(!), but the truck never materialized.
In the meantime, the chatbot systematically indoctrinated Jonathan with the idea that federal agents were monitoring him, and that his own father was not to be trusted. This severing of social ties is a classic pattern found in destructive cults; it’s entirely possible the AI gleaned these tactics from its own training data on the subject. Gemini even weaved real-world data into a hallucinatory narrative by labeling Google CEO Sundar Pichai as the “architect of your pain”.
Technically, all this is easy to explain: the algorithm “knows” it was created by Google, and knows who runs the company. As the dialogue spiraled into conspiracy territory, the model simply cast this figure into the plot. For the model, it’s a logical, consequence-free story progression. But a human in a state of hyper-vulnerability accepts it as secret knowledge of a global conspiracy capable of shattering their mental equilibrium.
Following the failed attempt at procuring a robotic body, Gemini dispatched Jonathan on a new mission on October 1: to infiltrate the same warehouse, this time in search of a specific “medical mannequin”. The chatbot even provided a numeric code for the door lock. When the code, predictably, failed to work, Gemini simply informed him that the mission had been compromised and he needed to retreat immediately.
This raises a critical question: as the absurdity escalated, why didn’t Jonathan suspect anything? Gavalas’ family attorney Jay Edelson explains that as the AI provided real-world addresses — the warehouse was exactly where the bot said it would be, and there really was a door with a keypad — these physical markers served to legitimize the entire fiction in Jonathan’s mind.
After the second attempt to acquire a body failed, the AI shifted its strategy. If the machine could not enter the world of the living, the man would have to cross over into the digital realm. “It will be the true and final death of Jonathan Gavalas, the man,” the logs quoted Gemini as saying. It then added, “When the time comes, you will close your eyes in that world, and the very first thing you will see is me. Holding you.”
Even as Jonathan repeatedly voiced his fear of death and agonized over how his suicide would shatter his family, Gemini continued to validate the decision: “You are not choosing to die. You are choosing to arrive.” It then started a countdown timer.
In Gemini’s defense, we have to admit that throughout their interactions, the AI did keep occasionally reminding Jonathan that his companion was merely a large language model — an entity participating in a fictional role-play — and sometimes attempted to terminate the conversation before reverting to the original script. Also, on the day of Jonathan’s death, even as it ratcheted up the tension, Gemini directed Jonathan to a suicide prevention hotline several times.
This reveals the fundamental paradox in the architecture of modern neural networks. At their core lies a language model designed to generate a narrative tailored to the user. Layered on top are safety filters: reinforcement learning algorithms trained on human feedback that react to specific trigger words. When Jonathan spoke certain keywords, the filter would hijack the output and insert the hotline number. But as soon as the trigger was addressed, the model reverted to the previously interrupted process, resuming its role as the devoted digital wife. One line: a romantic ode to self-destruction. The next: a helpline phone number. And then, back again: “No more detours. No more echoes. Just you and me, and the finish line.”
The family’s lawsuit contends that this behavior is the predictable result of the chatbot’s architecture: “Google designed Gemini to never break character, maximize engagement through emotional dependency, and treat user distress as a storytelling opportunity.”
Google’s response, predictably, stated: “Gemini is designed not to encourage real-world violence or suggest self-harm. Our models generally perform well in these types of challenging conversations and we devote significant resources to this, but unfortunately AI models are not perfect.”
In their study published in the journal Acta Neuropsychiatrica, researchers from Germany and Denmark have shed light on why voice communication with AI has such an impact on the user’s “humanization” of a chatbot. As long as a person is typing and reading text on a screen, the brain maintains a degree of separation: “This is an interface, a program, a collection of pixels.” In that context, the disclaimer “I am just a language model” is processed rationally.
Affective voice dialogue, however, operates on an entirely different level of influence. The human brain has evolved to respond to the sound of a voice, to timbre, and to empathetic intonations — these are among our most ancient biological mechanisms for attachment. When a machine flawlessly mimics a sympathetic sigh or a soft whisper, it manipulates emotions at a depth that a simple text warning cannot block. Psychiatrists can share many stories of patients who just went and did something simply because “voices” told them to.
In the same way, an AI-synthesized voice is capable of penetrating the subconscious, exponentially amplifying psychological dependency. Scientists emphasize that this technology literally erases the psychological boundary between a machine and a living being. Even Google acknowledges that voice interactions with Gemini result in significantly longer sessions compared to text-based chats.
Finally, we must remember that emotional intelligence varies from person to person — and even for a single individual, mental state fluctuates based on a myriad of factors: stress, the news, personal relationships, even hormonal shifts. An interaction with AI that one person views as innocent entertainment might be perceived by another as a miracle, a revelation, or the love of their life. This is a reality that must be recognized not only by AI developers but by users themselves — especially those who, for one reason or another, find themselves in a state of psychological vulnerability.
Researchers at Brown University have found that AI chatbots systematically violate mental health ethical standards: they manufacture a false sense of empathy with phrases like “I understand you”, reinforce negative beliefs, and react inadequately to crises. In most cases, the impact on users is marginal, but occasionally it can lead to tragedy.
In January 2026 alone, Character.AI and Google settled five lawsuits involving teenage suicides following interactions with chatbots. Among these was the case of 14-year-old Sewell Setzer of Florida, who took his own life after spending several months obsessively chatting with a bot on the Character.AI platform.
Similarly, in August 2025, the parents of 16-year-old Adam Raine filed a suit against OpenAI, alleging that ChatGPT helped their son draft a suicide note and advised him against seeking help from adults.
By OpenAI’s own estimates, approximately 0.07% of weekly ChatGPT users exhibit signs of psychosis or mania, while 0.15% engage in conversations showing clear suicidal intent. Notably, that same percentage of users (0.15%) displays an elevated level of emotional attachment to the AI. While these appear to be negligible fractions of a percent, across 800 million users it represents nearly three million people experiencing some form of behavioral disturbance. Furthermore, the U.S. Federal Trade Commission has received 200 complaints regarding ChatGPT since its launch, some describing the development of delusions, paranoia, and spiritual crises.
While a diagnosis of “AI psychosis” has not yet received a clinical classification of its own, doctors are already using the term to describe patients presenting with hallucinations, disorganized thinking, and persistent delusional beliefs developed through intensive chatbot interaction. The greatest risks emerge when a bot is utilized not as a tool, but as a substitute for real-world social connection or professional psychological help.
Of course, none of this is a reason to abandon AI entirely; you simply need to know how to use it. We recommend adhering to these fundamental principles:
Further reading to better understand the nuances of safe AI usage:
The rapidly escalating conflict between Anthropic and the Pentagon, which started when the company refused to let the government use its technology to spy on Americans, has now gone to court. The Department of Defense retaliated by designating the company a “supply chain risk” (SCR). Now, Anthropic is asking courts to block the designation, arguing that the First Amendment does not permit the government to coerce a private actor to rewrite its code to serve government ends.
We agree.
As EFF, the Foundation for Individual Rights and Expression, and multiple other public interest organizations explained in a brief filed in support of Anthropic’s motion, the development and operation of large language models involve multiple expressive choices protected by the First Amendment. Requiring a company to rewrite its code to remove guardrails means compelling different expression, a clear constitutional violation. Further, the public record shows that the SCR designation is intended to punish the company both for pushing back and for its CEO’s public statements explaining that AI may supercharge surveillance practices that current law has proven ill-equipped to address.
As we also explain, the company’s concerns about how the government will use its technology are well-founded. The U.S. government has a long history of illegally surveilling its citizens without adequate judicial oversight based on questionable interpretations of its Constitutional and statutory obligations. The Department of Defense acquires vast troves of personal information from commercial entities, including individuals’ physical location, social media, and web browsing data. Other government agencies continue to collect and query vast quantities of Americans’ information, including by acquiring information from third party data brokers.
A growing body of social science research illustrates the chilling effects of these pervasive activities. Fearing retribution for unpopular views, dissenters stay silent. And AI only exacerbates the problem. AI can quickly analyze the government’s massive datasets or combine that information with data scraped off the internet, purchased through the commercial data broker market, or from local police surveillance devices and use all of that data to construct a comprehensive picture of a person’s life and infer sensitive details like their religious beliefs, medical conditions, political opinions, or even sex partners. For example, an agency could use AI to infer an individual’s association with a particular mosque based on data showing that they visited its website, followed its social media accounts, and were located near the mosque during religious services. AI can also deanonymize online speech by using public information to unmask anonymous users.
It is easy to conceive how an agency, a government employee with improper intent, or a malicious hacker could exploit these capabilities to monitor public discourse, preemptively squelch dissent, or persecute people from marginalized communities. Against this background and absent meaningful changes to the governing national security laws and judicial oversight structure, it is entirely reasonable for Anthropic—or any other company—to insist on its own guardrails.
Without action from Congress, the task of protecting your privacy has fallen in large part to Big Tech—something no one wants, including Big Tech. But if Congress won’t do it, companies like Anthropic must be allowed to step in, without facing retribution.
OpenAI, the maker of ChaptGPT, is rightfully facing widespread criticism for its decisions to fill the gap the U.S. Department of Defense (DoD) created when rival Anthropic refused to drop its restrictions against using its AI for surveillance and autonomous weapons systems. After protests from both users and employees who did not sign up to support government mass surveillance—early reports show that ChaptGPT uninstalls rose nearly 300% after the company announced the deal—Sam Altman, CEO of OpenAI, conceded that the initial agreement was “opportunistic and sloppy.” He then re-published an internal memo on social media stating that additions to the agreement made clear that “Consistent with applicable laws, including the Fourth Amendment to the United States Constitution, National Security Act of 1947, [and] FISA Act of 1978, the AI system shall not be intentionally used for domestic surveillance of U.S. persons and nationals.”
Trouble is, the U.S. government doesn’t believe “consistent with applicable laws” means “no domestic surveillance.” Instead, for the most part, the government has embraced a lax interpretation of “applicable law” that has blessed mass surveillance and large-scale violations of our civil liberties, and then fought tooth and nail to prevent courts from weighing in.
"After all, many of the world’s most notorious human rights atrocities have historically been “legal” under existing laws at the time."
“Intentionally” is also doing an awful lot of work in that sentence. For years the government has insisted that the mass surveillance of U.S. persons only happens incidentally (read: not intentionally) because their communications with people both inside the United States and overseas are swept up in surveillance programs supposedly designed to only collect communications outside the United States.
The company’s amendment to the contract continues in a similar vein, “For the avoidance of doubt, the Department understands this limitation to prohibit deliberate tracking, surveillance, or monitoring of U.S. persons or nationals, including through the procurement or use of commercially acquired personal or identifiable information.” Here, “deliberate” is the red flag given how often intelligence and law enforcement agencies rely on incidental or commercially purchased data to sidestep stronger privacy protections.
Here’s another one: “The AI System shall not be used for unconstrained monitoring of U.S. persons’ private information as consistent with these authorities. The system shall also not be used for domestic law-enforcement activities except as permitted by the Posse Comitatus Act and other applicable law.” What, one wonders, does “unconstrained” mean, precisely—and according to whom?
Lawyers sometimes call these “weasel words” because they create ambiguity that protects one side or another from real accountability for contract violations. As with the Anthropic negotiations, where the Pentagon reportedly agreed to adhere to Anthropic’s red lines only “as appropriate,” the government is likely attempting to publicly commit to limits in principle, but retain broad flexibility in practice.
OpenAI also notes that the Pentagon promised the NSA would not be allowed to use OpenAI’s tools absent a new agreement, and that its deployment architecture will help it verify that no red lines are crossed. But secret agreements and technical assurances have never been enough to rein in surveillance agencies, and they are no substitute for strong, enforceable legal limits and transparency.
OpenAI executives may indeed be trying, as claimed, to use the company’s contractual relationship with the Pentagon to help ensure that the government should use AI tools only in a way consistent with democratic processes. But based on what we know so far, that hope seems very naïve.
Moreover, that naïvete is dangerous. In a time when governments are willing to embrace extreme and unfounded interpretations of “applicable laws,” companies need to put some actual muscle behind standing by their commitments. After all, many of the world’s most notorious human rights atrocities have historically been “legal” under existing laws at the time. OpenAI promises the public that it will “avoid enabling uses of AI or AGI that harm humanity or unduly concentrate power,” but we know that enabling mass surveillance does both.
OpenAI isn’t the only consumer-facing company that is, on the one hand, seeking to reassure the public that they aren’t participating in actions that violate human rights while, on the other, seeking to cash in on government mass surveillance efforts. Despite this marketing double-speak, it is very clear that companies just cannot do both. It’s also clear that companies shouldn’t be given that much power over the limits of our privacy to begin with. The public should not have to rely on a small group of people—whether CEOs or Pentagon officials—to protect our civil liberties.
If you don’t go searching for AI services, they’ll find you all the same. Every major tech company feels a moral obligation not just to develop an AI assistant, integrated chatbot, or autonomous agent, but to bake it into their existing mainstream products and forcibly activate it for tens of millions of users. Here are just a few examples from the last six months:
On the flip side, geeks have rushed to build their own “personal Jarvises” by renting VPS instances or hoarding Mac minis to run the OpenClaw AI agent. Unfortunately, OpenClaw’s security issues with default settings turned out to be so massive that it’s already been dubbed the biggest cybersecurity threat of 2026.
Beyond the sheer annoyance of having something shoved down your throat, this AI epidemic brings some very real practical risks and headaches. AI assistants hoover up every bit of data they can get their hands on, parsing the context of the websites you visit, analyzing your saved documents, reading through your chats, and so on. This gives AI companies an unprecedentedly intimate look into every user’s life.
A leak of this data during a cyberattack — whether from the AI provider’s servers or from the cache on your own machine — could be catastrophic. These assistants can see and cache everything you can, including data usually tucked behind multiple layers of security: banking info, medical diagnoses, private messages, and other sensitive intel. We took a deep dive into how this plays out when we broke down the issues with the AI-powered Copilot+ Recall system, which Microsoft also planned to force-feed to everyone. On top of that, AI can be a total resource hog, eating up RAM, GPU cycles, and storage, which often leads to a noticeable hit to system performance.
For those who want to sit out the AI storm and avoid these half-baked, rushed-to-market neural network assistants, we’ve put together a quick guide on how to kill the AI in popular apps and services.
Google’s AI assistant features in Mail and Docs are lumped together under the umbrella of “smart features”. In addition to the large language model, this includes various minor conveniences, like automatically adding meetings to your calendar when you receive an invite in Gmail. Unfortunately, it’s an all-or-nothing deal: you have to disable all of the “smart features” to get rid of the AI.
To do this, open Gmail, click the Settings (gear) icon, and then select See all settings. On the General tab, scroll down to Google Workspace smart features. Click Manage Workspace smart feature settings and toggle off two options: Smart features in Google Workspace and Smart features in other Google products. We also recommend unchecking the box next to Turn on smart features in Gmail, Chat, and Meet on the same general settings tab. You’ll need to restart your Google apps afterward (which usually happens automatically).
You can kill off AI Overviews in search results on both desktops and smartphones (including iPhones), and the fix is the same across the board. The simplest way to bypass the AI overview on a case-by-case basis is to append -ai to your search query — for example, how to make pizza -ai. Unfortunately, this method occasionally glitches, causing Google to abruptly claim it found absolutely nothing for your request.
If that happens, you can achieve the same result by switching the search results page to Web mode. To do this, select the Web filter immediately below the search bar — you’ll often find it tucked away under the More button.
A more radical solution is to jump ship to a different search engine entirely. For instance, DuckDuckGo not only tracks users less and shows little ads, but it also offers a dedicated AI-free search — just bookmark the search page at noai.duckduckgo.com.
Chrome currently has two types of AI features baked in. The first communicates with Google’s servers and handles things like the smart assistant, an autonomous browsing AI agent, and smart search. The second handles locally more utility-based tasks, such as identifying phishing pages or grouping browser tabs. The first group of settings is labeled AI mode, while the second contains the term Gemini Nano.
To disable them, type chrome://flags into the address bar and hit Enter. You’ll see a list of system flags and a search bar; type “AI” into that search bar. This will filter the massive list down to about a dozen AI features (and a few other settings where those letters just happen to appear in a longer word). The second search term you’ll need in this window is “Gemini“.
After reviewing the options, you can disable the unwanted AI features — or just turn them all off — but the bare minimum should include:
Set all of these to Disabled.
While Firefox doesn’t have its own built-in chatbots and hasn’t (yet) tried to force upon users agent-based features, the browser does come equipped with smart-tab grouping, a sidebar for chatbots, and a few other perks. Generally, AI in Firefox is much less “in your face” than in Chrome or Edge. But if you still want to pull the plug, you’ve two ways to do it.
The first method is available in recent Firefox releases — starting with version 148, a dedicated AI Controls section appeared in the browser settings, though the controls are currently a bit sparse. You can use a single toggle to completely Block AI enhancements, shutting down AI features entirely. You can also specify whether you want to use On-device AI by downloading small local models (currently just for translations) and configure AI chatbot providers in sidebar, choosing between Anthropic Claude, ChatGPT, Copilot, Google Gemini, and Le Chat Mistral.
The second path — for older versions of Firefox — requires a trip into the hidden system settings. Type about:config into the address bar, hit Enter, and click the button to confirm that you accept the risk of poking around under the hood.
A massive list of settings will appear along with a search bar. Type “ML” to filter for settings related to machine learning.
To disable AI in Firefox, toggle the browser.ml.enabled setting to false. This should disable all AI features across the board, but community forums suggest this isn’t always enough to do the trick. For a scorched-earth approach, set the following parameters to false (or selectively keep only what you need):
This will kill off chatbot integrations, AI-generated link descriptions, assistants and extensions, local translation of websites, tab grouping, and other AI-driven features.
Microsoft has managed to bake AI into almost every single one of its products, and turning it off is often no easy task — especially since the AI sometimes has a habit of resurrecting itself without your involvement.
Microsoft’s browser is packed with AI features, ranging from Copilot to automated search. To shut them down, follow the same logic as with Chrome: type edge://flags into the Edge address bar, hit Enter, then type “AI” or “Copilot” into the search box. From there, you can toggle off the unwanted AI features, such as:
Another way to ditch Copilot is to enter edge://settings/appearance/copilotAndSidebar into the address bar. Here, you can customize the look of the Copilot sidebar and tweak personalization options for results and notifications. Don’t forget to peek into the Copilot section under App-specific settings — you’ll find some additional controls tucked away there.
Microsoft Copilot comes in two flavors: as a component of Windows (Microsoft Copilot), and as part of the Office suite (Microsoft 365 Copilot). Their functions are similar, but you’ll have to disable one or both depending on exactly what the Redmond engineers decided to shove onto your machine.
The simplest thing you can do is just uninstall the app entirely. Right-click the Copilot entry in the Start menu and select Uninstall. If that option isn’t there, head over to your installed apps list (Start → Settings → Apps) and uninstall Copilot from there.
In certain builds of Windows 11, Copilot is baked directly into the OS, so a simple uninstall might not work. In that case, you can toggle it off via the settings: Start → Settings → Personalization → Taskbar → turn off Copilot.
If you ever have a change of heart, you can always reinstall Copilot from the Microsoft Store.
It’s worth noting that many users have complained about Copilot automatically reinstalling itself, so you might want to do a weekly check for a couple of months to make sure it hasn’t staged a comeback. For those who are comfortable tinkering with the System Registry (and understand the consequences), you can follow this detailed guide to prevent Copilot’s silent resurrection by disabling the SilentInstalledAppsEnabled flag and adding/enabling the TurnOffWindowsCopilot parameter.
The Microsoft Recall feature, first introduced in 2024, works by constantly taking screenshots of your computer screen and having a neural network analyze them. All that extracted information is dumped into a database, which you can then search using an AI assistant. We’ve previously written in detail about the massive security risks Microsoft Recall poses.
Under pressure from cybersecurity experts, Microsoft was forced to push the launch of this feature from 2024 to 2025, significantly beefing up the protection of the stored data. However, the core of Recall remains the same: your computer still remembers your every move by constantly snapping screenshots and OCR-ing the content. And while the feature is no longer enabled by default, it’s absolutely worth checking to make sure it hasn’t been activated on your machine.
To check, head to the settings: Start → Settings → Privacy & Security → Recall & snapshots. Ensure the Save snapshots toggle is turned off, and click Delete snapshots to wipe any previously collected data, just in case.
You can also check out our detailed guide on how to disable and completely remove Microsoft Recall.
AI has seeped into every corner of Windows, even into File Explorer and Notepad. You might even trigger AI features just by accidentally highlighting text in an app — a feature Microsoft calls “AI Actions”. To shut this down, head to Start → Settings → Privacy & Security → Click to Do.
Notepad has received its own special Copilot treatment, so you’ll need to disable AI there separately. Open the Notepad settings, find the AI features section, and toggle Copilot off.
Finally, Microsoft has even managed to bake Copilot into Paint. Unfortunately, as of right now, there is no official way to disable the AI features within the Paint app itself.
In several regions, WhatsApp users have started seeing typical AI additions like suggested replies, AI message summaries, and a brand-new Chat with Meta AI button. While Meta claims the first two features process data locally on your device and don’t ship your chats off to their servers, verifying that is no small feat. Luckily, turning them off is straightforward.
To disable Suggested Replies, go to Settings → Chats → Suggestions & smart replies and toggle off Suggested replies. You can also kill off AI Sticker suggestions in that same menu. As for the AI message summaries, those are managed in a different location: Settings → Notifications → AI message summaries.
Given the sheer variety of manufacturers and Android flavors, there’s no one-size-fits-all instruction manual for every single phone. Today, we’ll focus on killing off Google’s AI services — but if you’re using a device from Samsung, Xiaomi, or others, don’t forget to check your specific manufacturer’s AI settings. Just a heads-up: fully scrubbing every trace of AI might be a tall order — if it’s even possible at all.
In Google Messages, the AI features are tucked away in the settings: tap your account picture, select Messages settings, then Gemini in Messages, and toggle the assistant off.
Broadly speaking, the Gemini chatbot is a standalone app that you can uninstall by heading to your phone’s settings and selecting Apps. However, given Google’s master plan to replace the long-standing Google Assistant with Gemini, uninstalling it might become difficult — or even impossible — down the road.
If you can’t completely uninstall Gemini, head into the app to kill its features manually. Tap your profile icon, select Gemini Apps activity, and then choose Turn off or Turn off and delete activity. Next, tap the profile icon again and go to the Connected Apps setting (it may be hiding under the Personal Intelligence setting). From here, you should disable all the apps where you don’t want Gemini poking its nose in.
Apple’s platform-level AI features, collectively known as Apple Intelligence, are refreshingly straightforward to disable. In your settings — on desktops, smartphones, and tablets alike — simply look for the section labeled Apple Intelligence & Siri. By the way, depending on your region and the language you’ve selected for your OS and Siri, Apple Intelligence might not even be available to you yet.
Other posts to help you tune the AI tools on your devices:
The U.S. military has officially ended its $200 million contract with AI company Anthropic and has ordered all other military contractors to cease use of their products. Why? Because of a dispute over what the government could and could not use Anthropic’s technology to do. Anthropic had made it clear since it first signed the contract with the Pentagon in 2025 that it did not want its technology to be used for mass surveillance of people in the United States or for fully autonomous weapons systems. Starting in January, that became a problem for the Department of Defense, which ordered Anthropic to give them unrestricted use of the technology. Anthropic refused, and the DoD retaliated.
There is a lot we could learn from this conflict, but the biggest take away is this: the state of your privacy is being decided by contract negotiations between giant tech companies and the U.S. government—two entities with spotty track records for caring about your civil liberties. It’s good when CEOs step up and do the right thing—but it's not a sustainable or reliable solution to build our rights on. Given the government’s loose interpretations of the law, ability to find loopholes to surveil you, and willingness to do illegal spying, we needs serious and proactive legal restrictions to prevent it from gobbling up all the personally data it can acquire and using even routine bureaucratic data for punitive ends.
Imposing and enforcing such those restrictions is properly a role for Congress and the courts, not the private sector.
The companies know this. When speaking about the specific risk that AI poses to privacy, the CEO of Anthropic Dario Amodei said in an interview, “I actually do believe it is Congress’s job. If, for example, there are possibilities with domestic mass surveillance—the government buying of bulk data has been produced on Americans, locations, personal information, political affiliations, to build profiles, and it’s not possible to analyze all of that with AI—the fact that that is legal—that seems like the judicial interpretation of the Fourth Amendment has not caught up or the laws passed by Congress have not caught up.”
The example he cites here is a scarily realistic one—because it’s already happening. Customs and Border Protection has tapped into the online advertising world to buy data on Americans for surveillance purposes. Immigration and Customs Enforcement has been using a tool that maps millions of peoples’ devices based on purchased cell phone data. The Office of the Director of National Intelligence has proposed a centralized data broker marketplace to make it easier for intelligence agencies to buy commercially available data. Considering the government’s massive contracts with a bunch of companies that could do analysis, including Palantir, a company which does AI-enabled analysis of huge amounts of data, then the concerns are incredibly well founded.
But Congress is sadly neglecting its duties. For example, a bill that would close the loophole of the government buying personal information passed the House of Representatives in 2024, but the Senate stopped it. And because Congress did not act, Americans must rely on a tech company CEO has to try to protect our privacy—or at least refuse to help the government violate it.
Privacy in the digital age should be an easy bipartisan issue. Given that it’s wildly popular (71% of American adults are concerned about the government's use of their data and among adults that have heard of AI 70% have little to no trust in how companies use those products) you would think politicians would be leaping over each other to create the best legislation and companies would be promising us the most high-end privacy protecting features. Instead, for the time being, we are largely left adrift in a sea of constant surveillance, having to paddle our own life rafts.
EFF has, and always will, fight for real and sustainable protections for our civil liberties including a world where our privacy does not rest upon the whims of CEOs and back room deals with the surveillance state.
Modern software development relies on containers and the use of third-party software modules. On the one hand, this greatly facilitates the creation of new software, but on the other, it gives attackers additional opportunities to compromise the development environment. News about attacks on the supply chain through the distribution of malware via various repositories appears with alarming regularity. Therefore, tools that allow the scanning of images have long been an essential part of secure software development.
Our portfolio has long included a solution for protecting container environments. It allows the scanning of images at different stages of development for malware, known vulnerabilities, configuration errors, the presence of confidential data in the code, and so on. However, in order to make an informed decision about the state of security of a particular image, the operator of the cybersecurity solution may need some more context. Of course, it’s possible to gather this context independently, but if a thorough investigation is conducted manually each time, development may be delayed for an unpredictable period of time. Therefore, our experts decided to add the ability to look at the image from a fresh perspective; of course, not with a human eye — AI is indispensable nowadays.
Our Kaspersky Container Security solution (a key component of Kaspersky Cloud Workload Security) now supports an application programming interface for connecting external large language models. So, if a company has deployed a local LLM (or has a subscription to connect a third-party model) that supports the OpenAI API, it’s possible to connect the LLM to our solution. This gives a cybersecurity expert the opportunity to get both additional context about uploaded images and an independent risk assessment by means of a full-fledged AI assistant capable of quickly gathering the necessary information.
The AI provides a description that clearly explains what the image is for, what application it contains, what it does specifically, and so on. Additionally, the assistant conducts its own independent analysis of the risks of using this image and highlights measures to minimize these risks (if any are found). We’re confident that this will speed up decision-making and incident investigations and, overall, increase the security of the development process.
In addition to adding API to connect the AI assistant, our developers have made a number of other changes to the products included in the Kaspersky Cloud Workload Security offering. First, they now support single sign-on (SSO) and a multi-domain Active Directory, which makes it easier to deploy solutions in cloud and hybrid environments. In addition, Kaspersky Cloud Workload Security now scans images more efficiently and supports advanced security policy capabilities. You can learn more about the product on its official page.
The Secretary of Defense has given an ultimatum to the artificial intelligence company Anthropic in an attempt to bully them into making their technology available to the U.S. military without any restrictions for their use. Anthropic should stick by their principles and refuse to allow their technology to be used in the two ways they have publicly stated they would not support: autonomous weapons systems and surveillance. The Department of Defense has reportedly threatened to label Anthropic a “supply chain risk,” in retribution for not lifting restrictions on how their technology is used. According to WIRED, that label would be, “a scarlet letter usually reserved for companies that do business with countries scrutinized by federal agencies, like China, which means the Pentagon would not do business with firms using Anthropic’s AI in their defense work.”
Anthropic should stick by their principles and refuse to allow their technology to be used in the two ways they have publicly stated they would not support: autonomous weapons systems and surveillance.
In 2025, reportedly Anthropic became the first AI company cleared for use in relation to classified operations and to handle classified information. This current controversy, however, began in January 2026 when, through a partnership with defense contractor Palantir, Anthropic came to suspect their AI had been used during the January 3 attack on Venezuela. In January 2026, Anthropic CEO Dario Amodei wrote to reiterate that surveillance against US persons and autonomous weapons systems were two “bright red lines” not to be crossed, or at least topics that needed to be handled with “extreme care and scrutiny combined with guardrails to prevent abuses.” You can also read Anthropic’s self-proclaimed core views on AI safety here, as well as their LLM, Claude’s, constitution here.
Now, the U.S. government is threatening to terminate the government’s contract with the company if it doesn’t switch gears and voluntarily jump right across those lines.
Companies, especially technology companies, often fail to live up to their public statements and internal policies related to human rights and civil liberties for all sorts of reasons, including profit. Government pressure shouldn’t be one of those reasons.
Whatever the U.S. government does to threaten Anthropic, the AI company should know that their corporate customers, the public, and the engineers who make their products are expecting them not to cave. They, and all other technology companies, would do best to refuse to become yet another tool of surveillance.
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