Article
AI Deep Dive Part 1: The History of AI
Arete Analysis
Cyber Threats

Artificial intelligence (AI) is a subset of computer science that focuses on creating systems that can replicate human intelligence and problem-solving capabilities. This is accomplished by feeding large amounts of data into machine learning models (MLMs) and processing the data. The result is technology that can simulate human learning, comprehension, problem-solving, decision-making, creativity, and autonomy.
While often seen as new, cutting-edge technology, AI has been around far longer than most would think. While the concept of AI goes back to ancient philosophers theorizing on life and death, AI as we know it began in the early 1900s. The conception of what AI is began to be portrayed in science fiction by various authors and artists throughout the early 1900s prior to what is commonly known as “the birth of AI.”
AI Through the Ages
The Birth of AI: 1950 – 1956
Computer scientists such as Alan Turing, Arthur Samuel, and John McCarthy set the stage for the beginning of AI. Turing published “Computer Machinery and Intelligence,” which annotated a test of machine intelligence called the Imitation Game. Turing theorized that any machine able to fool a human judge would be classified as artificial intelligence.
AI Maturation: 1957 – 1979
The next twenty years showed little growth for AI at a technical level. While the concept of AI became popular in pop culture, funding-backed research was minimal during this period. However, that is not to say that strides towards what AI is today were not made. The first programming languages were created, paving the way for future development. The first AI chatbot was created, which adopted a new approach to AI that we now call deep learning, and the first examples of an autonomous vehicle were created.
AI Boom: 1980 – 1987
During the seven-year period known as the AI boom, government funding and associated research significantly increased. The first Association for the Advancement of Artificial Intelligence (AAAI) conference was held at Sanford, and the first driverless car demonstrated its ability to drive up to 55 mph on empty roads.
AI Winter: 1987 – 1993
Overall, funding and interest in AI decreased during this period, leading to fewer advancements in the technology than in years prior.
AI agents: 1993 – 2011
Despite the initial lack of investment in AI, the technology as a whole significantly increased its capabilities during this time period. Most notably, this is when AI began being integrated into people’s daily lives with items such as the Roomba and the release of Apple’s virtual assistant, Siri.
Early Generative Artificial Intelligence: 2012 – Present
This brings us up to the current state of AI. The last decade has shown impressive leaps in AI’s ability to aid humans in day-to-day functions. This is also accompanied by enormous data collection from well-known companies that are able to train their AI models, which has led to the release of consumer-facing AI models such as ChatGPT, Copilot, and more.
Conclusion
AI as a whole is a fast-changing, fluid concept. Organizations regularly unveil new capabilities and breakthroughs. This was especially evident in the recent unveiling of Deepseek and the subsequent data privacy concerns. In a single day, this overturned the sector in one fell swoop. AI will likely remain a constantly changing field in the near term.
What’s Next?
Part 2 of Arete’s AI Deep Dive will examine the risks and benefits of organizations adopting AI into their business models
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Article
Europol Disrupts AudiA6 Crypto Laundering Service
European authorities have dismantled AudiA6, a major cryptocurrency laundering service linked to ransomware groups and broader cybercriminal networks. Between 2022 and 2025, the platform is believed to have processed over €336 million in illicit funds, enabling threat actors to obscure financial trails and monetize cybercrime proceeds. Its operators are also suspected of running Dark2Web, a dark web forum that facilitated collaboration, services, and connections among cybercriminals globally. This development underscores the expanding role of sophisticated, large-scale cryptocurrency laundering services in sustaining the cybercrime economy, enabling threat actors to obscure illicit funds and evade regulatory controls.
What’s Notable and Unique
Following law enforcement disruption of Cryptex and Garantex, AudiA6 emerged as another platform involved in financial activities linked to ransomware groups. Investigators believe that AudiA6 became a central hub for cybercriminals seeking to launder stolen digital assets while obscuring the transaction trail from authorities.
On June 10, 2026, a coordinated operation resulted in two arrests in Georgia, the dismantling of key infrastructure (30+ servers, 25 domains), the freezing or seizure of over €778,000 in crypto, and the takedown of the AudiA6 and Dark2Web platforms.
Analyst Comments
Ransomware groups and cybercriminal networks are increasingly leveraging sophisticated techniques, including chain-hopping, decentralized exchanges, and mixer-as-a-service platforms, to rapidly move illicit cryptocurrency across multiple blockchains, effectively obscuring transaction trails. Concurrently, the widespread use of fraudulent exchange accounts, mule wallets, and privacy-enhancing tools has elevated cryptocurrency laundering to a core enabler of the cybercrime ecosystem, allowing actors to bypass anti-money-laundering controls at scale. This investigation identified over 6,000 KYC records linked to money-mule accounts, many of which were tied to Russian-speaking intermediaries specifically recruited to facilitate the movement of illicit proceeds. These threat actors systematically used both commercial and domain-controlled email services to establish mule accounts across multiple cryptocurrency platforms. Collectively, these findings underscore the growing scale, coordination, and professionalization of cryptocurrency-enabled crime, highlighting the critical need for sustained, intelligence-led, and internationally coordinated efforts to disrupt these evolving financial ecosystems.
Sources
Ransomware gangs cut off from EUR 336 million ‘AudiA6’ crypto laundering pipeline
Article
Threat Actors Leverage AI for EDR Evasion
A threat actor has developed and deployed a ransomware attack toolkit enhanced with AI-assisted development workflows, enabling automated Active Directory (AD) discovery and improved EDR evasion capabilities. The toolkit leverages agent-based AI systems, such as Claude’s Opus and Cursor agents, for iterative malware development, testing, and refinement.
What’s Notable and Unique
Researchers have highlighted that this toolkit can not only generate ransomware code but also bypass sophisticated security defenses and identify AD networks for malware distribution.
The framework incorporates multiple capabilities, including automated AD discovery and reconnaissance mechanisms, iterative EDR testing environments to refine evasion techniques, and a command-and-control (C2) infrastructure that leverages Telegram APIs and Cloudflare redirectors for stealth.
Additionally, some agents were tasked with checking security research and technical posts for various bypass techniques. The agents recognized what was required for reproduction, extracted the techniques, mapped them to the MITRE ATT&CK knowledge base of adversary behaviors, set up a test lab, carried out the methodology, and reported the results.
After a few repetitions, the modules seemed to avoid nearly all EDR solutions, despite the agent’s initial suggestion of a high failure rate. Although researchers found no evidence that AI was embedded in deployed malware or was operating independently in victim environments, the technology was still used to accelerate the iterative process of developing, testing, and refining payloads against security products, shortening the period between the publication of offensive security research and its practical implementation by threat actors.
Analyst Comments
AI-driven tools like this could accelerate the pace and sophistication of ransomware attacks, enabling even relatively inexperienced actors to launch high-impact campaigns. This development underscores the urgent need for security solutions to adapt to AI-assisted threats. Organizations must respond by strengthening detection engineering, improving visibility across environments, and maintaining robust security fundamentals.
Sources
AI-built ransomware toolkit automates EDR evasion, AD discovery
Pointing a Cursor at evading detection
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Arete's 2026 Q1 Crimeware Report
Harness Arete’s unique data and expertise on extortion and ransomware to inform your response to the evolving threat landscape.
Article
CMS Vulnerability Leads to ClickFix Campaign
Threat actors compromised at least 700 education and technology websites in a recent ClickFix campaign by exploiting a critical SQL injection flaw (CVE-2026-26980) in the Ghost content management system (CMS). Adversaries combined the vulnerability with the ClickFix social engineering tactic to steal admin keys and inject a malicious JavaScript that delivers a fake Cloudflare or CAPTCHA verification pop-up, tricking victims into copying and pasting a malicious command into their systems.
What’s Notable and Unique
Rather than targeting the end user first, this campaign is unique in its initial exploitation of the system, followed by social engineering attempts. This hybrid attack style is likely being leveraged to bypass traditional defenses.
This recent campaign also highlights how trusted web properties can be weaponized at scale and coupled with unpatched CMS vulnerabilities. Rather than using the CMS compromise to perpetrate a single attack, threat actors turned it into a supply-chain attack that ultimately affected over 700 trusted websites.
Analyst Comments
As network defenders and their tools enhance threat detection capabilities, adversaries increasingly seek methods to bypass these defenses. By combining vulnerability exploitation, social engineering techniques, and staging for ancillary attacks, this campaign successfully bypassed traditional defenses and inflicted significant impact. Defending against hybrid cyberattacks requires comprehensive security controls beyond simply patching vulnerabilities. Organizations should focus on limiting movement within the environment, detecting abuse of trusted applications, and preventing end-user manipulation.
Sources
700+ education and tech websites hijacked in huge ClickFix malware campaign
Under the engineering hood: Why Malwarebytes chose WordPress as its CMS
Think before you Click(Fix): Analyzing the ClickFix social engineering technique
Ghost CMS Vulnerability Exploited to Infect 700 Sites With ClickFix Malware



