I met my wife back when you used Blockbuster for DVD’s. Do you remember the hybrid model, where you could go to the store, AND get DVDs delivered?
I’m not old, you are.

Anyway, I digress.

Accuracy in the language used in cybersecurity is honestly pretty frustrating.
It can't be the only industry where a marketing description of a product to be 100% right, and oh so, so, so wrong.
"We prevent the attack" can either be usually right, or usually wrong.
May the person with the most fireworks, models (male and female), jazz hands, and biggest marketing claims win.

The devil is, indeed, in the details.
Cybersecurity is also one of those really deep knowledge fields where, because consumers and engineers alike are walking on the shoulders of engineering giants, it is really easy for consumers and even technologists to really not have the time to figure out those details. Even when it really matters. Even when, in cybersecurity, a lot of that "research" is not really taught in schools (though that's better and improving now). Marketing analysts will, of course, for the right price tell the story that needs to be told as trusted advisors to end users trying to separate fact from fiction.
A bit like when I go to the doctor, to be honest.
I nod, knowingly, but I honestly am not a doctor (cue a Star Trek Bones references). I don't even play one on TV.

I remember a conversation with Greg Fulk, former customer, current investor, who now has his own pretty cool company (check it out, seriously), having to talk about his own investigative journey before purchasing. Despite a busy schedule, he took time out of his day to unwind the layers of groupthink from the rest of the security vendor marketing (at least for endpoint-based security), and make an assessment for himself whether Cyber Crucible's different approach has merit or not.

Not everyone has the time or technical skill to do that.
Some are too busy being experts in keeping the Board happy, or at keeping the OT and IT teams from donning luchador masks every patch Tuesday.
And that's all right, because those are skills too.

I did speak to a guy once that tried to point out to a cadre of executives at a manufacturing company that they knew in detail every component's MTBF (Mean Time Before Failure) in their plant's operation, but clueless for the "nerdy" IT and security stuff.

I don't think that guy got a bunch of executives jumping up to ask questions about PKI, but I hear he made progress.
Rome wasn't built in a day.
Neither was Netflix's library.
And getting to the result you want in the end, after a bunch of effort, can be pretty chill.
Wait, no, that's not what I meant.

I think everyone will enjoy this short little podcast.

Time to write this like AI.
“This is not a podcast by Dennis. It is an experience.”

Much like the time I ate at one of those fancy restaurants.
You know the type; the type you always leave hungry.

One of the experiences included must have resulted from a sale on organic beets, and the chef put a TON of beet foam on a couple of the dishes.
I assume beet foam was at one point beets, in what I would assume is some type of Hellraiser horror for vegetables everywhere.

Well, now I’m WAY off topic. Enough about beets.

This was recorded before the news about the Microsoft CoPilot snooping on Outlook inboxes more than it was supposed to.

That’s all I have to say about that.

https://epodcastnetwork.com/can-your-ai-tell-you-who-gets-bonuses-this-year

Check out this cool Forbes article by Danny Pehar, as a relevant topic.

https://www.forbes.com/councils/forbestechcouncil/2026/03/09/ransomware-in-2026-why-prevention-is-now-a-board-level-discipline-not-an-it-project/

Read more

The Evolution of Online Identity

The fundamental nature of online identity has changed. It is no longer a simple username and password. Modern digital identity is a constellation of cryptographically secured objects—keys, tokens, and credentials—stored directly on endpoints, representing a persistent and highly-privileged access to the entire enterprise ecosystem.

Tokens: The New Digital Passport

Legacy authentication methods, such as Basic Auth, required a user to send their actual username and password across the network for every single request. This practice significantly increased the risk of credentials being intercepted. OAuth (Open Authorization), the de facto standard, revolutionized this by introducing tokens.

The modern web application environment is powered by this token-based authorization. When a user first logs into a web application, their credentials are exchanged for an access token and often a refresh token.

• The access token is a unique, short-lived string of characters that acts as a digital passport, granting the client application permission to access specific resources on the user’s behalf.

• The refresh token is a longer-lived secret used to obtain a new access token once the current one expires, ensuring continuous, seamless access without requiring the user to re-authenticate repeatedly.

These tokens, which effectively bypass the password for day-to-day operations, are stored in local databases and files on the user’s machine by browsers, email clients, and desktop applications. Regardless of whether Multi-Factor Authentication (MFA) or biometrics are used for the initial login, the underlying communication method after that point is managed by these session tokens and refresh tokens. An attacker who steals an active token instantly bypasses every defensive measure deployed at the initial login stage.

The Keys to the Kingdom: API, Private, and VPN Keys

Beyond OAuth tokens, critical access is encapsulated in other cryptographic assets residing on the endpoint:

• API Keys are unique codes that identify an application’s requests to a service’s API, acting like a specialized digital keycard that grants programmatic access to features or data. Exposure of an API key allows an attacker to make requests on the company’s behalf, leading to unexpected charges, data compromise, and service interruption.

• Private Keys are essential in asymmetric cryptography, providing the ability to decrypt data or sign requests. They are the ultimate secret and are used to establish encrypted connections, such as those used in a Virtual Private Network (VPN). Stealing a VPN private key grants an attacker the ability to log in as an authorized user, bypassing the network perimeter and gaining access to internal resources.

Cryptowallets: Financial Identity on the Endpoint

Cryptocurrency wallets that exist as applications on user machines are essentially the user’s financial identity in the digital economy. A wallet doesn’t physically hold the cryptocurrency; it securely stores the private keys used to authorize and sign transactions on the blockchain. The theft of these private keys is equivalent to having a physical safe’s combination, allowing the attacker to empty the associated digital assets, which can represent significant corporate or personal funds.

The Vulnerability: When Keys and Tokens are Stolen

The theft of API keys, private keys, session tokens, and refresh tokens is the central vulnerability in the modern enterprise. While passwords still pose a risk, they are a one-time gate. In automated attacks, keys and tokens are the preferred target because they offer persistent, undetectable access. An attacker with a stolen, valid session token or VPN key is indistinguishable from an authorized user, rendering most boundary-based defenses obsolete. This stolen identity data provides a “legitimate” backdoor to the network that security teams struggle to detect for months.

Hacker Automation: The “Smash and Grab” Attack

Modern cyber adversaries have replaced human-driven attacks with highly efficient, hyper-automated “smash and grab” operations. These are not methodical, long-term surveillance campaigns—they are blindingly fast data theft blitzes.

Automated attacks rely on predictable, known data points across all operating systems to maximize efficiency. The attacker’s pre-programmed tool doesn’t waste time analyzing a specific network; it is designed to go straight for universally-known locations:

• User Profile and Desktop Locations (e.g., C:\Users\[Username]).

• Common Application Data Folders (where browsers and email clients store tokens and credentials).

• Standard VPN Key Locations.

The automated tool’s primary goal is a Stage 1 smash and grab: targeting these known identity locations to instantly exfiltrate tokens, session cookies, and private keys—the “keys to the kingdom”. This provides an immediate return on investment and, more crucially, a persistent backdoor for a more lucrative, long-term data theft operation (Stage 2) later. The sheer speed of these scripts—infiltrating, collecting data, and self-deleting in a few seconds—makes human or even cloud-based detection and response an impossibility.

The Impossibility of Reactive Identity Defense

Preventing credential and identity theft is paramount, but it poses a profound challenge to incumbent cybersecurity technologies. A reactive EDR/XDR tool, which sends data to a cloud-based SOC for analysis, is defeated by the latency of network communication and the biological latency of the human analyst. When an automated attack can steal an identity in under a second, a defense model that takes minutes or hours to respond is fundamentally broken. True defense must be purely preventative, kernel-level, and autonomous.

Cyber Crucible: Autonomous, Kernel-Level Identity Prevention

Cyber Crucible challenges the flawed response-driven model by embedding autonomous, real-time protection directly into the endpoint’s kernel. Our defense is a direct counter to the hyper-automated threats, stopping the “smash and grab” before a single key or token is stolen.

Genetic AI-Powered Behavioral Modeling and Response

The core of Cyber Crucible’s identity protection is its patented Genetic AI-powered behavioral modeling and response engine. This technology operates at the deepest level of the operating system—the kernel—to provide a superhumanly fast decision-making process.

When any program attempts to access known identity theft and data theft entry points—the critical directories storing tokens, keys, and credentials:

• Real-time Program and Library Integrity: Every program, even legitimate ones, and its supporting libraries are assessed for tampering in memory before access is allowed. This neutralizes fileless and in-memory injection attacks where malicious code hides inside a trusted process.

• Behavioral Modeling: Cyber Crucible’s AI engine instantly analyzes the process’s intent. It tracks the program’s parent-child relationships, memory behavior, and the target data location.

• Autonomous Decision and Interception: If a malicious behavioral pattern is detected—such as a non-browser process attempting to read a credential store—the system automatically intercepts and stops the program in under 200 milliseconds. This is a full, non-disruptive suspension of the malicious process, neutralizing the threat before any data is exfiltrated.

Protecting Sensitive Data from Vendors

In a world where security products have become a data liability, Cyber Crucible operates with a focus on data sovereignty. While many security vendors may require or offer to upload sensitive identity data like private keys or session tokens to their hosted SOC teams, Cyber Crucible’s autonomous, edge-first design eliminates this risk. Known and verified programs, such as legitimate antivirus tools that pass the integrity assessment, are allowed to continue protecting their systems. However, Cyber Crucible’s core function is to locally and autonomously prevent the malicious access to identity data, ensuring that sensitive assets never leave the secure boundary of the endpoint or are exposed to the control of a third-party vendor. This ensures true quiet security and complete control for the customer.

Cyber Crucible is the necessary evolution from reactive analysis to autonomous prevention. The future of cybersecurity is not forensic; it’s prevention.

The Open Architecture Paradox 🤝

The operating systems in the Linux, UNIX, and macOS family are built on a foundation of open, modular design. This philosophy, originating from UNIX, encourages transparency and community-driven development. Linux, in particular, thrives on its open-source model, allowing developers and security researchers to inspect and contribute to the source code. This open nature, while beneficial for rapid bug fixes and feature development, gives attackers the same level of visibility into the system's inner workings. They can study the code to find vulnerabilities and anticipate how security tools will function, making them more effective at bypassing defenses.

The Insufficiency of User-Level Tools 🧰

Many cybersecurity agents operate at the user level. They are applications that run on the system and, as such, are subject to the same permissions and limitations as any other program. An attacker who gains administrative privileges can easily terminate, suspend, or modify these tools. For example, a malicious actor with sudo access can simply use kill -9 to stop a security agent's process. These tools are valuable for general threat detection but are fundamentally vulnerable to a targeted, privileged attack.

Kernel modules, in contrast, operate with the highest level of privilege in kernel space (Ring 0). They have direct, unimpeded access to all system functions and data. This allows them to monitor and control processes, file systems, and network traffic with a level of granularity and efficiency that user-level tools cannot. However, even these powerful modules are not immune to attack.

The Fragility of Kernel Modules 💥

By default, security kernel modules can be unloaded from a running system. A malicious actor with sudo or root access can simply use commands like rmmod to remove a security module. This action effectively disables the most powerful layer of the security agent's defense, leaving the system exposed. This is a critical flaw: the most effective tools for protecting a system can be easily deactivated by the very adversary they are designed to stop.

The Limits of Mandatory Access Controls (MACs) 🔐

To address this issue, operating systems employ Mandatory Access Control (MAC) policies, such as SELinux and AppArmor. These frameworks enforce a system-wide, kernel-level access policy that is designed to be more secure than the standard Discretionary Access Control (DAC) model. A MAC policy can, for example, prevent a root user from unloading a specific security kernel module. This seems like a robust solution, but there's a catch.

The very mechanism that provides this protection can be disabled by a user with root access. A malicious actor with elevated privileges can simply turn off the MAC policy (e.g., using sudo setenforce 0 on a system with SELinux), then proceed to unload the security module. This means there is no solid, inherent manner to prevent a malicious actor with root access from disabling security kernel modules on these systems.

Attacker Tradecraft: A Calculated Bypass 🕵️‍♂️

A modern attacker's tradecraft on a non-Windows system would be highly automated and methodical, designed to disable security controls in a specific order:

1. Disable User-Level Tools: The attacker, having gained initial access, would first use scripts to identify and terminate any user-level security processes. They might search for known process names, then use killall or pkill to remove them from memory.

2. Disable MAC Policies: With user-level agents neutralized, the attacker would then escalate privileges to root and disable any active MAC policy. This is often a single command, making it a quick and effective way to remove a major barrier to their next step.

3. Unload Kernel Modules: Finally, with the MAC policy disabled, the attacker would use rmmod to unload the security kernel module. The system is now fully exposed, allowing the attacker to establish persistence, exfiltrate data, and execute their full attack without a major security agent to stop them.

This automated, multi-stage process highlights the central challenge: the very tools meant to protect the system can be leveraged against themselves.

The Cyber Crucible Angle: A Call for a New Approach

Cyber Crucible has successfully replicated all of its key functionalities for Windows products on non-Windows operating systems. This includes advanced behavioral analysis, memory introspection, and real-time in-memory analysis of libraries like shared objects (the non-Windows equivalent of a Windows DLL).

We recognize that most enterprise attacks begin on Windows and then use stolen credentials to migrate to other systems, especially virtualization management portals like vCenter, Veeam, or Hyper-V. While our existing identity theft prevention capabilities largely mitigate this risk, a robust non-Windows capability would be valuable for catching insider threats or attackers who already have access to these highly sensitive administrative portals.

However, a critical conversation must be had within the non-Windows security community: the persistence issue. The fact that a security tool can simply be turned off by an attacker who gains root access is a glaring hole in risk management. Our Microsoft product is designed to be ultra-resilient and is often the last security tool running on a compromised system. We cannot, in good faith, deploy a non-Windows tool with the same expectations of resilience and dependability, knowing it can be so easily disabled.

Currently, our research and development teams are working to address this fundamental problem of persistence and build the level of resilience our customers expect. Until then, the Cyber Crucible team recommends that organizations limit access to non-Windows machines as much as possible, as no security tool can truly provide the necessary protection until this critical issue is resolved.

The modern cybersecurity threat landscape is defined by its speed and autonomy. While ransomware has traditionally been the headline-grabbing threat, a more insidious and sophisticated form of attack is emerging: the fusion of remote access tools (RATs) with hacker automation. This white paper will explore how attackers are leveraging pre-built surveillance and theft capabilities within remote access tools to conduct completely autonomous operations. It will contrast the network dependencies of these attacks with the more self-sufficient nature of ransomware and detail the new hybrid methodologies attackers are employing to achieve both rapid and long-term data theft.

The Evolution of Remote Access Tools as an Attack Vector

Read more

The cybersecurity landscape is in a state of continuous evolution, but perhaps no trend is as transformative and dangerous as the rise of hacker automation. Once a domain of manual, human-driven attacks, cybercrime has shifted into a hyper-efficient, machine-speed operation. This white paper explores the evolution of hacker automation, from its early roots in simple scripts to today's sophisticated, AI-powered "smash and grab" attacks. It will detail the specific tactics that make these automated attacks so effective, the critical vulnerabilities they exploit, and the necessary paradigm shift in defense strategies required to combat them.

The Evolution of Cyberattacks: From Manual to Automated

Read more

Read more

For much of the last decade, cybersecurity was defined by the herd defense model, a concept central to early Endpoint Detection and Response (EDR) and Extended Detection and Response (XDR) solutions. This approach was built on the assumption that cybercriminals' methods would evolve slowly enough for security vendors to respond. The strategy was to analyze a new attack after it had successfully compromised a small number of victims, then rapidly deploy a countermeasure to protect the wider customer base. This meant that there was always an unfortunate "control group" of victims every time a criminal organization mutated its attacks. The model, while intended to protect the greater good, was inherently reactive.

The effectiveness of this model began to wane as the pace of new exploits and automated attack tool mutations accelerated. The telemetry collected from endpoints and networks, once a valuable source of actionable intelligence, became a tidal wave of ambiguous data. This "less definitive smoking gun" telemetry was often the only evidence of an attack, and it was typically discovered long after the compromise had already occurred.

Both customers and security companies were now drowning in a sea of data. For customers, hiring the multitude of specially trained security analysts required to sort through this volume of data was financially unfeasible. For security companies, while they could afford to hire analysts, the challenge was no less daunting. This situation is perfectly captured by a non-cybersecurity analogy: the factory floor of Veruca Salt's father in Willy Wonka and the Chocolate Factory. Mr. Salt's workers were tasked with a Herculean effort, opening countless chocolate bars in a relentless quest to find a single Golden Ticket. Similarly, in cybersecurity, companies hired expensive analysts to sort through endless data, a Sisyphean task of interpreting logs and alerts to find a hacker.

Human analysts were constantly losing this battle. The sheer volume of incomplete data, false positives, and ambiguous indicators led to an overwhelming sense of "alert fatigue." In this environment, attackers continued to gain victims using traditional methods, as the herd defense model could not keep up with the speed of their automated mutations. The "control group of victims" versus the "protected members of the herd" had grown to the point where every EDR customer was always in the control group, always a potential victim of whatever new attack the criminals’ automated mutations conjured up next.

The Disruptive Force of Artificial Intelligence

Artificial intelligence emerged as the only viable solution to process and correlate these immense volumes of data. However, the introduction of a disruptive technology that requires a dramatic change in methodology is never seamless. Consider the shift from the horse and buggy to the internal combustion engine. For companies and innovators, a new technology presents a triple challenge: commercialization, market adoption, and overcoming resistance from incumbents.

Market incumbents, with established revenue streams based on the old ways of doing business, are often the most resistant to change. They may see the new technology as a risk to their existing business model and may even invest in startups to gain inside knowledge or acquire them on favorable terms, all to control or thwart the disruption. Beyond capitalism, the commercialization of a new technology is an evolutionary process itself, with unexpected successes and failures as society and commerce learn to adapt.

In cybersecurity, it was only natural that the market, dominated by overworked analysts, would first use AI to amplify the existing human-driven approach. This is the equivalent of Veruca Salt's father adding robotic arms to his factory workers to help them open chocolate bars faster. This incremental use of technology is beneficial—it can reduce analyst fatigue and improve efficiency—but it is still constrained by the underlying, flawed operational model. It's an improvement, but not a revolution. AI offers a myriad of new ways to approach the challenge of offense and defense, but simply stapling it onto the herd defense model prevents it from reaching its full potential.

Cyber Crucible and the Genetic AI Revolution

Cyber Crucible's innovation lies in its complete departure from the herd defense concept. It leverages genetic AI algorithms to create a new way of approaching cyber defense—one that is proactive and resilient to the continuous mutations of attacker tools. This is not about building a larger factory floor to hold more box-opening employees; it’s about a completely different operational method.

This shift is the difference between adding robotic arms to the workers on the factory floor and inventing an entirely new machine: an x-ray machine to scan every chocolate bar instantly, looking for the unique shape of the Golden Ticket without ever having to open the box.

Genetic AI allows Cyber Crucible to move beyond analyzing known attack patterns among a control group of victims. Instead, it creates a robust, resource efficient system that can assess the fundamental nature of hacker actions. Just like the x-ray machine, Cyber Crucible first had to invent multiple new sources of data that could provide the right information at the right time, resilient to hacker attempts to blind the sensors. The right data, at the right time, to the right decision model allows for proactive defense that can anticipate and neutralize threats even when they are brand new and have no known signature. By breaking out of the herd defense mentality, Cyber Crucible provides a new paradigm for cybersecurity that eliminates the need for a "control group of victims" and provides a truly proactive defense against a constantly mutating threat landscape.

Cyber Crucible was undoubtedly building an AI-infused cybersecurity product before AI was “cool”. Certainly, its development was built off decades of effort and research from a multitude of projects and academic research. Perhaps it stands as the first cybersecurity product to embrace a new method of defense orthogonal to herd defense type strategies. In 2025, with a stream of new AI-wielding cybersecurity companies emerging which use artificial intelligence as a robotic arm for the security analyst, Cyber Crucible may be the only company separating from the legacy tradecraft.

Cyber Crucible’s corporate agenda is focused on customer empowerment, transparency, integrity, and “making cybersecurity boring” through the use of new artificial intelligence advancements. The future is bright for the Company and its customers, as it can now focus on using new use cases for artificial intelligence and associated technologies to achieve their life and corporate goals now that AI by the good guys is winning against AI in use by the criminals.