Nvidia, headquartered in Santa Clara, California, has emerged as a beacon of technological innovation, much as the industrial giants of a bygone era reshaped their worlds. Its latest creations—the Hopper GPU and Blackwell systems—are not merely advancements in computing; they are the tools of a new industrial revolution, their influence stretching across industries and into the lives of millions. As measured by its astonishing financial results, the company’s trajectory reflects the unparalleled demand for these tools.

The latest quarter’s revenue, a staggering $35.08 billion, represents a 94% leap from the $18.12 billion of a year prior—a figure that would have seemed fantastical not long ago. Its net income soared to $19.31 billion, more than double last year’s third-quarter figure of $9.24 billion. Even after accounting for adjustments, earnings reached 81 cents per share, outpacing Wall Street’s expectations of 75 cents per share on projected revenues of $33.17 billion, according to FactSet.

This is no mere coincidence of market forces or transient trends. Nvidia’s success is rooted in the astonishing versatility of its Hopper GPU and Blackwell systems. Their applications span a broad spectrum—from artificial intelligence to cybersecurity—each deployment, which is a testament to their transformative power. These are not simply tools but harbingers of a future where the limits of what machines can do are redrawn with each passing quarter.

The Hopper and Blackwell systems are not isolated achievements; they are central to Nvidia’s rise as a leader in innovation, its vision ever fixed on the horizon. The technology reshapes industries as varied as medicine, entertainment, finance, and autonomous systems, weaving a thread of progress through all it touches. Like the significant advancements of earlier eras, these creations do not merely answer existing questions; they pose new ones, unlocking doors to realms previously unimagined.

Thus, Nvidia’s record-breaking quarter is a financial milestone and a marker of its place in history. As it shapes the future of computing, the company’s influence extends far beyond the confines of Silicon Valley. It is, in a sense, a reflection of our age—a testament to human ingenuity and the ceaseless drive to innovate, explore, and create.

By Skeeter Wesinger

November 20, 2024

In the age of relentless digital transformation, software security remains both a bulwark and a vulnerability. The deployment of Large Language Models (LLMs) as tools to fortify this critical frontier marks a turning point, one that evokes the blend of promise and peril characteristic of technological revolutions. Like radar in the skies of the Second World War, these LLMs have the potential to detect threats unseen by the human eye, provided they are used judiciously and in concert with other defenses.

The power of LLMs lies in their unparalleled ability to analyze vast swaths of source code with a speed and thoroughness that human developers cannot match. From detecting the cracks in the foundation—buffer overflows, injection vulnerabilities, hardcoded credentials, and improper input validation—to recognizing subtle, non-obvious threats that arise from the interplay of complex systems, these models operate with an unrelenting vigilance. What might take a team of skilled engineers days or weeks to unearth, an LLM can flag in minutes, scouring line after line with mechanical precision.

This capability is most potent during the prerelease phase of development when the entire source code is laid bare. It is here, before a product sees the light of day, that LLMs can expose vulnerabilities lurking in the shadows, vulnerabilities that, if left unchecked, could later metastasize into full-blown breaches. The cost of such breaches is not merely financial but reputational, eroding the trust that underpins all digital enterprises.

Consider the subtle artistry of an LLM detecting insecure data handling in a function, not because the code itself appears flawed but because of the way it interacts with calls elsewhere in the codebase. This is no brute-force analysis; it is an exercise in pattern recognition, a demonstration of how machines are learning to see the forest as well as the trees.

Yet, as with radar, the promise of LLMs must be tempered by realism. They are not a standalone defense, nor do they obviate the need for more traditional measures. They complement fuzzing, which tests software by bombarding it with random inputs and identifying areas where such testing might be most fruitful. They serve as a first line of defense, flagging issues for human reviewers who can then apply their judgment and experience to resolve them.

Moreover, LLMs can act as vigilant assistants during development itself, offering real-time suggestions for secure coding practices. In doing so, they become not merely tools of analysis but instruments of prevention, guiding developers away from insecure practices before they become embedded in the code.

What sets LLMs apart is their scalability. Unlike manual reviews, which are labor-intensive and constrained by human resources, LLMs can analyze sprawling codebases or even multiple projects simultaneously. This scalability is nothing short of transformative for organizations tasked with securing complex software ecosystems.

Used in concert with fuzzing, manual reviews, and other security protocols, LLMs represent the new frontline in software security. They bring automation and scale to an arena that has long been constrained by the limitations of time and manpower. Their ability to access and analyze full source code during development ensures that the vulnerabilities they uncover are not only flagged but actionable.

The lessons of history remind us that no single technology, no matter how transformative, can operate in isolation. LLMs are tools of immense potential, but it is the interplay of man and machine, of automation and expertise, that will ultimately determine their success. In this emerging battle for the sanctity of our digital infrastructures, LLMs are an ally of immense promise, provided we deploy them wisely and with an understanding of their limitations.

By Skeeter Wesinger

November 18, 2024

https://www.linkedin.com/pulse/new-frontline-security-technology-skeeter-wesinger-olzbe

In a move that has set the cybersecurity world on alert, Palo Alto Networks has sounded the alarm on a significant security flaw in their Expedition tool, a platform designed to streamline the migration of firewall configurations to their proprietary PAN-OS. This vulnerability, codified as CVE-2024-5910, underscores the critical importance of authentication protocols in safeguarding digital boundaries. The flaw itself—a missing authentication mechanism—permits attackers with mere network access the alarming ability to reset administrator credentials, effectively opening the gate to unauthorized access and potentially compromising configuration secrets, credentials, and sensitive data that lie at the heart of an organization’s digital defenses.

The gravity of this flaw is underscored by the immediate attention of the U.S. Cybersecurity and Infrastructure Security Agency (CISA), which has not only added the vulnerability to its Known Exploited Vulnerabilities Catalog but also issued a direct mandate: all federal agencies must address this vulnerability by November 28, 2024. The urgency of this deadline signifies more than just bureaucratic efficiency; it speaks to the alarming nature of a vulnerability that CISA reports is being exploited in the wild, thus shifting this issue from a theoretical risk to an active threat.

Palo Alto Networks has responded with characteristic clarity, outlining a series of robust security measures to mitigate this vulnerability. They emphasize restricting the PAN-OS management interface to trusted internal IP addresses, advising against exposure to the open internet. In addition, they recommend isolating the management interface within a dedicated VLAN, further securing communications through SSH and HTTPS. These measures, while straightforward, demand a high level of attention to detail in implementation—an effort that could very well mean the difference between a fortified system and a compromised one.

Meanwhile, in a strategic pivot, Palo Alto Networks has announced that the core functionalities of Expedition will soon be integrated into new offerings, marking the end of Expedition support as of January 2025. The shift signals a broader evolution within the company’s ecosystem, perhaps heralding more advanced, integrated solutions that can preemptively address vulnerabilities before they surface.

The directive to apply patches and adhere to the recommended security configurations is not just sound advice; it is, as security expert Wesinger noted, a necessary defensive measure in a rapidly shifting landscape where the stability of one’s systems rests on the relentless vigilance of their custodians. The events unfolding around CVE-2024-5910 are a reminder that in cybersecurity, as in any theater of conflict, complacency remains the greatest vulnerability.

By Skeeter Wesinger

November 14, 2024

 

https://www.linkedin.com/pulse/new-front-cybersecurity-exposed-skeeter-wesinger-rjypf

The advent of Generative AI (GenAI) has begun to transform the professional services sector in ways that are reminiscent of past industrial shifts. In pricing models, particularly, GenAI has introduced an undeniable disruption. Tasks once demanding hours of meticulous human effort are now being automated, ushering in a reduction of operational costs and a surge in market competition. Consequently, firms are being drawn towards new pricing paradigms—cost-plus and competitive pricing structures—whereby savings born of automation are, at least in part, relayed to clients.

GenAI’s influence is most visible in the routinized undertakings that have traditionally absorbed the time and energy of skilled professionals. Drafting documents, parsing data, and managing routine communications are now handled with remarkable precision by AI systems. This liberation of human resources allows professionals to concentrate on nuanced, strategic pursuits, from client consultation to complex problem-solving—areas where human intellect remains irreplaceable. Thus, the industry drifts from the conventional hourly billing towards a value-centric pricing system, aligning fees with the substantive outcomes delivered, not merely the hours invested. In this, GenAI has flattened the landscape: smaller firms, once marginalized by the resources and manpower of larger entities, can now stand as credible competitors, offering similar outputs at newly accessible price points.

Further, the rise of GenAI has spurred firms to implement subscription-based or tiered pricing models for services once bespoke in nature. Consider a client subscribing to a GenAI-powered tool that provides routine reports or documentation at a reduced rate, with options to escalate for human oversight or bespoke customization. This hybrid model—where AI formulates initial drafts and human professionals later refine them—has expanded service offerings, giving clients choices between an AI-driven product and one fortified by expert review. In this evolving terrain, firms are experimenting with cost structures that distinguish between AI-generated outputs and those augmented by human intervention, enabling clients to opt for an economical, AI-exclusive service or a premium, expert-reviewed alternative.

Investment in proprietary GenAI technology has become a distinguishing factor among leading firms. To some clients, these customized AI solutions—tailored for fields such as legal interpretation or financial forecasting—exude an allure of exclusivity, thereby justifying the elevated fees firms attach to them. GenAI’s inherent capacity to track and quantify usage has also paved the way for dynamic pricing models. Here, clients are billed in direct proportion to their engagement with GenAI’s capabilities, whether through the volume of reports generated or the features utilized. In this, professional services firms have crafted a usage-based pricing system, a model flexible enough to reflect clients’ actual needs and consumption.

However, with progress comes the shadow of regulation. As governments and regulatory bodies move to address GenAI’s ethical and data implications, professional service firms, particularly in sensitive sectors like finance, healthcare, and law, may find themselves bearing the weight of compliance costs. These expenses will likely be passed on to clients, especially where data protection and GenAI-driven decision-making demand rigorous oversight.

In the aggregate, GenAI’s integration is compelling professional services firms towards a dynamic, flexible, and transparent pricing landscape—one that mirrors the dual efficiencies of AI and the nuanced insights of human expertise. Firms willing to incorporate GenAI thoughtfully are poised not only to retain a competitive edge but also to expand their client offerings through tiered and value-based pricing. The age of GenAI, it seems, may well be one that redefines professional services, merging the best of human acumen with the swift precision of artificial intelligence.

Skeeter Wesinger

November 8, 2024

https://www.linkedin.com/pulse/age-generative-ai-skeeter-wesinger-oe7pe

In early 2024, a team of researchers at the University of Michigan and Auburn University stumbled upon an overlooked flaw in Dominion’s Democracy Suite voting system. The flaw, astonishing in its simplicity, harked back to the 1970s: a rudimentary linear congruential generator for creating random numbers, a method already marked as insecure half a century ago. Yet there it lay, embedded in the heart of America’s election machinery. This flaw, known as DVSorder, allowed the order of ballots to be exposed, violating a voter’s sacred right to secrecy without needing inside access or privileged software.

Dominion Voting Systems responded, as companies often do, with carefully measured words—a single-page advisory noting that “best practices” and “legal advisors” could mitigate the flaw. A software update, Democracy Suite 5.17, was eventually rolled out, claiming to resolve the vulnerability. Yet this patch, touted as a “solution,” seemed only to deepen the questions surrounding Dominion’s response. Was it a fix, or merely a stopgap?

A Bureaucratic Response: The Slow March of Democracy Suite 5.17

The U.S. Election Assistance Commission granted its stamp of approval to Democracy Suite 5.17 in March 2023, seemingly content with its certification. But the rollout that followed revealed the entrenched and fragmented nature of America’s election infrastructure. Election officials, bound by local constraints, cited logistical challenges, costs, and the impending presidential election as reasons to delay. In the absence of federal urgency or clear guidance from the Cybersecurity and Infrastructure Security Agency (CISA), the vulnerability remained in effect, a silent threat from Georgia to California.

Even as researchers watched from the sidelines, Dominion and federal agencies moved cautiously, with state adoption of Democracy Suite 5.17 proceeding at a glacial pace. Some states, like Michigan and Minnesota, made efforts to upgrade, but others deferred, considering the patch a burden best shouldered after the election. Thus, the DVSorder vulnerability persisted, largely unresolved in precincts where patching was deemed too disruptive.

The Patchwork of Democracy Suite 5.17: A System in Pieces

As expected, Democracy Suite 5.17 encountered obstacles in deployment, emblematic of the fractured approach to American election security. States such as Michigan tried to sanitize data to safeguard voter privacy, but the result was incomplete; others attempted to shuffle ballots, a solution whose effectiveness remained dubious. The whole exercise appeared as a microcosm of America’s approach to its electoral machinery: decentralized, hesitant, and all too often compromised by cost and convenience.

A Sobering Reminder for Democracy’s Future

The DVSorder affair serves as a reminder that elections, despite their image of order, depend on fallible human governance and systems. In this case, a mere oversight in programming triggered a vulnerability that risked eroding voter privacy, a cornerstone of democracy itself. Dominion’s response, slow and bureaucratic, reveals the unsettling reality that our reliance on technology in elections opens doors to errors whose repercussions may be profound.

The researchers who exposed this flaw were not saboteurs but, in a sense, stewards of public trust. They brought to light a sobering truth: that in the age of digital democracy, even the smallest vulnerability can ripple outward, potentially undermining the promises of privacy and integrity on which the system stands.

As the dust settles, DVSorder may join the list of vulnerabilities patched and closed, yet a shadow lingers. With each election cycle, new threats and oversights emerge, casting a faint but persistent question over the future of American democracy. One wonders—will we be ready for the next vulnerability that arises? Who knows.

By Skeeter Wesinger

November 4, 2024

 

https://www.linkedin.com/pulse/dominion-voting-systems-dvsorder-affair-saga-american-wesinger-i4qoe

The Ultra Ethernet Consortium (UEC) has delayed release of the version 1.0 of specification from Q3 2024 to Q1 2025, but it looks like AMD is ready to announce an actual network interface card for AI datacenters that is ready to be deployed into Ultra Ethernet datacenters. The new unit is the AMD Pensando Pollara 400, which promises an up to six times performance boost for AI workloads. In edge deployments, running a firewall directly on the NIC allows for more efficient security enforcement, where system resources may be limited. Using the NIC for firewall tasks frees up CPU cores, allowing your system to scale more efficiently without degrading performance as traffic volumes increase.

The AMD Pensando Pollara 400 is a 400 GbE Ultra Ethernet card based on a processor designed by the company’s Pensando unit. The network processor features a processor with a programmable hardware pipeline, programmable RDMA transport, programmable congestion control, and communication library acceleration. The NIC will sample in the fourth quarter and will be commercially available in the first half of 2025, just after the Ultra Ethernet Consortium formally publishes the UEC 1.0 specification. Businesses can implement NIC-based firewalling to manage traffic across VLANs or isolated network segments, enhancing network security without the need for dedicated firewall hardware.

Pollara 400

The AMD Pensando Pollara 400 AI NIC is designed to optimize AI and HPC networking through several advanced capabilities. One of its key features is intelligent multipathing, which dynamically distributes data packets across optimal routes, preventing network congestion and improving overall efficiency. The NIC also includes path-aware congestion control, which reroutes data away from temporarily congested paths to ensure continuous high-speed data flow.

The AMD Pensando Pollara 400 AI NIC supports advanced programmability and can be integrated with a development kit that is available for free. The AMD Pensando Software-in-Silicon Development Kit (SSDK) provides a robust environment for building and deploying applications directly on the NIC, allowing you to offload networking, firewall, encryption, and even AI inference tasks from the CPU.

The SSDK supports programming in P416 for fast path operations, as well as C and C++ for more traditional processing tasks. It provides full support for network and security functions like firewalling, IPsec, and NAT, allowing these to be handled directly by the NIC rather than the host CPU. Developers can use the provided reference pipelines and code samples to quickly get started with firewall implementations or other network services.

The SDK and related tools are open and accessible via GitHub and AMD’s official developer portals, enabling developers to experiment with and integrate Pensando’s NICs into their systems without licensing fees. Some repositories and tools are available directly on GitHub under AMD Pensando’s.

The delay in the release of the Ultra Ethernet Consortium’s (UEC) version 1.0 specification, initially expected in the third quarter of 2024 and now pushed to the first quarter of 2025, does little to shake the confidence of those observing AMD’s bold march forward. While others may have stumbled, AMD stands ready to unveil a fully realized network interface card (NIC) for AI datacenters—the AMD Pensando Pollara 400—an innovation poised to redefine the landscape of Ultra Ethernet data centers. This NIC, a formidable 400 GbE unit, embodies the very pinnacle of technological advancement. Designed by AMD’s Pensando unit, it promises no less than a sixfold increase in AI workload performance.

The Pollara 400’s impact goes beyond sheer processing power. At the edge, where resources are scarce and security paramount, the NIC performs firewall tasks directly, relieving the central processing unit from such burdensome duties. Herein lies its genius: by offloading these critical tasks, system scalability is enhanced, enabling traffic to flow unhindered and system performance to remain steady, even under mounting demands.

As we await the final specifications from the UEC, AMD has announced that the Pollara 400 will be available for sampling by the fourth quarter of 2024, with commercial deployment anticipated in early 2025. It is no mere stopgap solution—it is a harbinger of a new era in AI networking, built upon a programmable hardware pipeline capable of handling RDMA transport, congestion control, and advanced communication library acceleration.

Furthermore, the NIC’s intelligent multipathing is a feat of engineering brilliance. With its path-aware congestion control, this marvel dynamically directs data around congested network routes, ensuring that AI workloads are never hampered by the bottlenecks that so often plague high-performance computing.

The Pollara 400 is more than just hardware; it is an ecosystem supported by the AMD Pensando Software-in-Silicon Development Kit (SSDK), a free and versatile tool that allows developers to fully leverage its capabilities. Whether programming in P416 for high-speed operations or using C and C++ for more traditional tasks, developers can easily deploy firewalls, IPsec, and NAT directly onto the NIC itself, bypassing the need for traditional CPU involvement.

The SSDK provides not only the means but also the guidance to streamline development. From pre-built reference pipelines to comprehensive code samples, it invites developers to embrace the future of network security and AI processing, all while maintaining openness and accessibility via AMD’s repositories on GitHub. This is no longer just the work of a single company—it is a shared endeavor, opening new frontiers for those bold enough to explore them.

Thus, as AMD prepares to thrust the Pollara 400 into the spotlight, one thing becomes abundantly clear: the future of AI networking will not be forged in the server rooms of yesterday but at the cutting edge of what is possible, where firewalls, encryption, and AI tasks are handled in stride by a NIC that rewrites the rules.

Story By

Skeeter Wesinger

October 11, 2024

 

https://www.linkedin.com/pulse/amd-pensando-pollara-400-skeeter-wesinger-yulwe

If it sounds like a spy novel, then it might just be true. Living off the Land (LotL) has become the first weapon in the new Cold War, this time between the United States and the People’s Republic of China. This modern battlefield is fought not with tanks or missiles but through the subtle, insidious operations of cyber espionage. It is a war where the battlefield is the internet, and the combatants are not soldiers but bots—small, autonomous programs acting as the foot soldiers of nation-state-sponsored operations.

These bots infiltrate corporate networks with surgical precision, using disguised communications to siphon off critical data and metadata. Unlike overt attacks that trigger alarms and demand immediate responses, these bots slip under the radar, blending seamlessly into the everyday digital traffic of a company. Their presence is not felt, their actions not seen, often for long stretches of time—weeks, months, or even years—until the damage is done.

And the damage, when it finally becomes clear, is catastrophic. Intellectual property is stolen, financial systems are compromised, and sensitive data leaks into the hands of foreign adversaries. The consequences of these attacks stretch far beyond individual companies, threatening the security and economic stability of nations. This new cold war is not fought on the ground but in the unseen spaces of cyberspace, where vigilance is the only defense.

A bot, once embedded within a company’s systems, begins its covert mission. It is a malicious program, programmed with a singular purpose: to relay the company’s most guarded secrets to its unseen master. But its greatest weapon is not brute force or direct confrontation; it is stealth. These bots conceal their communication within the very lifeblood of corporate networks—normal, everyday traffic. Disguised as benign emails, mundane web traffic, or encrypted transmissions that mimic legitimate corporate exchanges, they send stolen information back to their creators without raising suspicion. What appears to be routine data passing through the system is, in fact, a betrayal unfolding in real time.

Their quarry is not just the obvious treasures—financial records, intellectual property, or proprietary designs. The bots are after something less tangible but no less valuable: metadata. The seemingly trivial details about the data—who sent it, when, from where—might appear inconsequential at first glance. But in the hands of a skilled adversary, metadata becomes a road map to the company’s inner workings. It reveals patterns, weaknesses, and, critically, the pathways to deeper infiltration.

For the corporation targeted by such an attack, the consequences are manifold. There is, of course, the potential loss of intellectual property—the crown jewels of any enterprise. Plans, designs, and trade secrets—each a piece of the company’s competitive edge—can be stolen and replicated by rivals. Financial information, once in the wrong hands, can result in fraud, a hemorrhage of funds that can cripple a company’s operations.

Perhaps the most dangerous aspect of these attacks is that compromised security extends beyond the initial theft. Once attackers have a firm grasp of a company’s systems through stolen metadata, they possess a detailed map of its vulnerabilities. They know where to strike next. And when they do, the company’s defenses, having already been breached once, may crumble further. What begins as a single act of theft quickly escalates into a full-scale infiltration.

And then, of course, there is the reputation damage. In the modern marketplace, trust is currency. When customers or clients discover their data has been stolen, they do not hesitate to seek alternatives. The collapse of faith in a company’s ability to safeguard its information can lead to long-term harm, far more difficult to recover from than the financial blow. The loss of reputation is a slow bleed, often fatal.

In short, these disguised communications are the perfect cover for botnet activities, allowing attackers to slip past defenses unnoticed. And when the theft is finally uncovered—if it is ever uncovered—it is often too late. The stolen data has already been transferred, the secrets already sold. The damage, irreversible.

I am reminded of a particular case, an incident that unfolded with a certain sense of inevitability. A seemingly reputable bank auditor, entrusted with sensitive client documents, calmly removed them from the premises one afternoon, claiming a simple lunch break. Upon returning, security, perhaps acting on an inkling of suspicion, inspected the bag. Inside, the documents—marked confidential—lay exposed. The auditor, caught red-handed, was promptly denied further access, and the documents seized. But, alas, the harm had already been done. Trust had been violated, and in that violation, the company learned a hard lesson: Never trust without verifying.

Such is the nature of modern-day espionage—not just a battle of information, but of vigilance. And in this game, those who are too trusting, too complacent, will find themselves outmatched, their vulnerabilities laid bare.

Story by Skeeter Wesinger

September 23, 2024

A Large corporation with a well-funded cyber security team recently found out they’d been hacked! Their opponents used the combination of Living off the Land (LotL) techniques, fileless malware, legitimate credentials, and disguised communication makes these types of botnet activities incredibly difficult to detect, even for their expert tiger teams. Without the right focus on behavioral analysis, memory forensics, and network monitoring, even highly skilled teams could miss the subtle signs of this advanced form of attack.

If your teams are looking for traditional malware or malicious executables, they might not have focused on monitoring the activities of legitimate tools. Attackers are now using these tools can camouflage their actions to blend in with normal system administration tasks, so even if your tiger teams were monitoring system processes, the malicious use of these tools could easily go unnoticed.

One of the core advantages of LotL is the use of fileless techniques, which means that the attackers often don’t drop detectable malware on the system’s disk. Instead, they execute code directly in memory or utilize scripting environments like PowerShell. This method leaves behind little to no trace that traditional malware-detection tools or endpoint security would recognize.

The teams may have been conducting disk-based or signature-based analysis, which would be ineffective against fileless malware. Without leaving artifacts on the disk, the attackers bypass traditional endpoint detection, which would have been a major focus of the teams.
Since most of the activity occurs in memory, it would require deep memory forensics to uncover these types of attacks. If the tiger teams didn’t perform real-time memory analysis or use sophisticated memory forensics tools, they could miss the attack entirely.

Story By Skeeter Wesinger

September 19, 2024

BitLocker, Microsoft’s encryption software for SSDs, has faced various challenges since its debut. The upcoming Windows 11 version 24H2 update, also known as the 2024 update, may introduce a new concern for users: BitLocker could be enabled by default during the installation process for all editions of Windows, including the Home edition. This information comes from a report by the German news outlet Deskmodder, which was subsequently covered by Neowin. Enabling BitLocker by default is seen as problematic for several reasons outlined below.

Firstly, enabling BitLocker, which encrypts and decrypts data continuously on your SSD, can significantly decrease your PC’s performance. Specifically, it could slow down system performance by up to 45% in Windows Pro, with similar impacts likely on other versions of the operating system.

Secondly, there is a risk for users who are not familiar with encryption. They might end up encrypting their data unintentionally during installation and could face difficulties decrypting it later if they misplace or fail to save the necessary decryption key. This could render both the CPU and the SSD inaccessible.

A third concern highlighted involves security vulnerabilities in BitLocker. According to YouTuber Stacksmashing, BitLocker’s encryption can be easily breached. They demonstrate that with a modest investment in a $10 Raspberry Pi Pico and physical access to the machine, encrypted data on a system with an external Trusted Platform Module (TPM) can be decrypted.

However, there is a straightforward remedy for this automatic encryption: users can disable Device Encryption in the Privacy & security section of the Settings menu. While this option exists, many Windows 11 users, particularly those with the Home version, may not be aware of it or know how to manage these settings.

If these reports are accurate, it would be prudent for Microsoft to reconsider the default auto-encryption feature before releasing the update. Such a feature seems to introduce more problems than it resolves.

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