The commission disclosed the attack on March 27, when Bleeping Computer confirmed the breach of the European Union’s primary executive body.
Recently, the European Commission informed CERT-EU about the breach, informing them that their Cybersecurity Operations was not warned about an API exploit, a possible account hack, or any malicious network traffic until March 24.
In March, TeamPCP exploited a compromised AWS API key to manage rights over different Commission AWS accounts (hacked in the Trivy supply-chain breach).
After that, the gang deployed TruffleHog to look for more secrets, then added a new access key to an existing user to escape detection before doing more spying and data theft.
In the past, TeamPCP has been known for supply-chain attacks targeting developer code forums like NPM, Docker, PyPi, and GitHub. The gang also attacked the LiteLLM PyPI package in a campaign that affected tens of thousands of devices via its “TeamPCP Cloud Stealer” data-stealing malware.
Later, data extortion gang ShinyHunters posted the stolen data on their dark web leak site as a 90 GB archive of documents (around 340GB uncompressed), which includes email addresses, contacts, and email information.
According to the CERT-EU analysis, hackers have stolen tens of thousands of documents; the leak affects around 42 internal European Commission clients and around 20 other Union firms.
"The threat actor used the compromised AWS secret to exfiltrate data from the affected cloud environment. The exfiltrated data relates to websites hosted for up to 71 clients of the Europa web hosting service: 42 internal clients of the European Commission, and at least 29 other Union entities,” CERT-EU said. Regarding the dataset, CERT-EU said it also contained “at least 51,992 files related to outbound email communications, totalling 2.22 GB. The majority of these are automated notifications with little to no content. However, 'bounce-back' notifications, which are responses to incoming messages from users, may contain the original user-submitted content, posing a risk of personal data exposure."
No websites were taken offline or altered as a result of this attack, and no lateral movement to other Commission AWS accounts has been found, according to CERT-EU.
Although it would probably take "a considerable amount of time" to analyze the exfiltrated databases and information, the Commission has informed the appropriate data protection authorities and is in direct contact with the impacted organizations.
After learning that a mobile device management platform used to oversee employees' devices had been compromised, the European Commission revealed another data breach in February.
Advanced Micro Devices has revealed plans to acquire long-time rival Intel Corporation, marking a dramatic reversal in one of the most enduring rivalries in the semiconductor industry.
The proposed transaction, structured entirely as a stock-based deal, signals a major shift in industry power. Once viewed as the underdog, AMD has now surpassed Intel in market valuation, and the acquisition would further cement that transition.
For over four decades, the relationship between the two companies has been defined by competition, imitation, legal disputes, and strategic overlap. AMD historically operated in Intel’s shadow, often positioning itself as a secondary supplier while attempting to challenge its dominance. In recent years, however, AMD has strengthened its position across multiple computing segments and improved investor confidence, while Intel has faced setbacks.
Intel’s struggles have included delays in manufacturing advancements, inconsistent product execution, and repeated strategic adjustments. These challenges have contributed to a broader shift in market perception, allowing AMD to close the gap and eventually move ahead in key areas.
The idea of AMD acquiring Intel would have seemed highly unlikely just a few years ago, given Intel’s long-standing dominance as the central force in the personal computing ecosystem. The potential merger now reflects how drastically that balance has changed.
If completed, integrating the two companies could present organizational and cultural challenges, given their long history as direct competitors. Leadership from AMD indicated that the combined entity could accelerate product development timelines, streamline user experience, and maintain a level of internal competition despite operating under one structure.
In its response, Intel stated that the agreement could enhance shareholder value while providing its engineering teams with clearer direction and stronger operational support to rebuild competitive product offerings.
Industry analysts are still assessing the broader implications. Historically, Intel’s scale and manufacturing capabilities positioned it at the center of the computing market, while AMD functioned as a challenger that introduced competitive pressure. That dynamic has shifted as AMD expanded its presence in servers, desktops, and mobile computing, while Intel’s recovery efforts remain ongoing.
Several practical questions remain unresolved. These include how branding will be handled, whether both product lines will continue independently, and how regulators will evaluate the consolidation of two primary x86 architecture competitors under a single entity.
Sources familiar with the matter suggest AMD may adopt a structure that retains both brands in the near term. One internal concept reportedly frames Intel as a legacy-focused division, reflecting its historical significance while redefining its position within the organization.
Investor reaction has ranged from surprise to cautious optimism. Some market participants see the potential for operational efficiency and reduced rivalry, while others are concerned that combining the two companies could limit competition in the x86 processor market.
From a regulatory perspective, the deal is likely to face scrutiny due to the potential concentration of market power. The long-standing competition between AMD and Intel has historically driven innovation and pricing balance, and its reduction could reshape industry dynamics.
The announcement comes at a time when the semiconductor sector is undergoing rapid transformation, driven by demand for artificial intelligence, high-performance computing, and evolving global supply chains. Both companies have been investing heavily in these areas, alongside competitors such as NVIDIA Corporation.
At present, the timeline for completion remains subject to regulatory approvals and further review. While the companies have indicated confidence in moving forward, the scale and implications of the deal mean that its outcome will be closely watched across the industry.
Cybersecurity experts have discovered another incident of the ongoing GlassWorm campaign, which uses a new Zig dropper that's built to secretly compromise all integrated development environments (IDEs) on a developer's system.
The tactic was found in an Open VSX extension called "specstudio.code-wakatime-activity-tracker”, which disguised as WakaTime, a famous tool that calculates the time programmes spend with the IDE. The extension can not be downloaded now.
In previous attacks, GlassWorm used the same native compiled code in extensions. Instead of using the binary as the payload directly, it is deployed as a covert indirection for the visible GlassWorm dropper. It can secretly compromise all other IDEs that may be present in your device.
The recently discovered Microsoft Visual Studio Code (VS Code) extension is a replica (almost).
The extension installs a universal Mach-O binary called "mac.node," if the system is running Apple macOS, and a binary called "win.node" for Windows computers.
These Zig-written compiled shared libraries that load straight into Node's runtime and run outside of the JavaScript sandbox with complete operating system-level access are Node.js native addons.
Finding every IDE on the system that supports VS Code extensions is the binary's main objective once it has been loaded. This includes forks like VSCodium, Positron, and other AI-powered coding tools like Cursor and Windsurf, in addition to Microsoft VS Code and VS Code Insiders.
Once this is achieved, the binary installs an infected VS Code extension (.VSIX) from a hacker-owned GitHub account. The extension, known as “floktokbok.autoimport”, imitates “steoates.autoimport”, an authentic extension with over 5 million downloads on the office Visual Studio Marketplace.
After that, the installed .VSIX file is written to a secondary path and secretly deployed into each IDE via editor's CLI installer.
In the second-stage, VS Code extension works as a dropper that escapes deployment on Russian devices, interacts with the Solana blockchain, gets personal data, and deploys a remote access trojan (RAT). In the final stage, RAT installs a data-stealing Google Chrome extension.
“The campaign has expanded repeatedly since then, compromising hundreds of projects across GitHub, npm, and VS Code, and most recently delivering a persistent RAT through a fake Chrome extension that logged keystrokes and dumped session cookies. The group keeps iterating, and they just made a meaningful jump,” cybersecurity firm aikido reported.
Instead of relying on a single model, Copilot's Researcher agent can now pull outputs from both OpenAI's GPT and Anthropic's Claude models for each response, thanks to a new feature called "Critique."
According to Microsoft, Claude will check the quality and correctness of the response before GPT provides it to the user. In the future, the business hopes to make that workflow bidirectional so that GPT may also evaluate Claude's writings.
"Having different models from different vendors in Copilot is highly attractive - but we're taking this to the next level, where customers actually get the benefits of the models working together," Nicole Herskowitz, VP of Copilot and Microsoft, said to Reuters.
The multi-model strategy will assist in increasing productivity and quality for customers by accelerating user workflow, controlling AI hallucinations, which occur when systems give incorrect information, and producing more dependable outputs.
Additionally, Microsoft is introducing a feature called "Council" that will let users compare results from various AI models side by side. The updates coincide with Microsoft expanding access to its new Copilot Cowork agentic AI tool for members of its "Frontier" program, which gives users early access to some of its most recent AI innovations.
According to Jared Spataro, Microsoft's AI-at-Work efforts leader, “We work only in a cloud environment, and we work only on behalf of the user. So you know exactly what information it (Copilot Cowork) has access to.”
On Monday, the company's stock increased by almost 1%. However, as investor confidence in AI declines, the stock is poised for its worst quarter since the global financial crisis of 2008, with a nearly 25% decline.
Microsoft capitalized on the increasing demand for autonomous AI agents earlier this month by releasing Copilot Cowork, a solution based on Anthropic's popular Claude Cowork product, in testing mode.
In the face of fierce competition from rivals like Google (GOOGL.O), the new tab Gemini, and autonomous agents like Claude Cowork, the Windows manufacturer has been rushing to enhance its Copilot assistant to promote greater usage.
New research suggests the cryptocurrency industry may have less time than anticipated to prepare for the risks posed by quantum computing, with potential implications for Bitcoin, Ethereum, and other major digital assets.
A whitepaper released on March 31 by researchers at Google indicates that breaking the cryptographic systems securing these networks may require fewer than 500,000 physical qubits on a superconducting quantum computer. This marks a sharp reduction from earlier estimates, which placed the requirement in the millions.
The study brings together contributors from both academia and industry, including Justin Drake of the Ethereum Foundation and Dan Boneh, alongside Google Quantum AI researchers led by Ryan Babbush and Hartmut Neven. The research was also shared with U.S. government agencies prior to publication, with input from organizations such as Coinbase and the Ethereum Foundation.
At present, no quantum system is capable of carrying out such an attack. Google’s most advanced processor, Willow, operates with 105 qubits. However, researchers warn that the gap between current hardware and attack-capable machines is narrowing. Drake has estimated at least a 10% probability that a quantum computer could extract a private key from a public key by 2032.
The concern centers on how cryptocurrencies are secured. Bitcoin relies on a mathematical problem known as the Elliptic Curve Discrete Logarithm Problem, which is considered practically unsolvable using classical computers. However, Peter Shor demonstrated that quantum algorithms could solve this problem far more efficiently, potentially allowing attackers to recover private keys, forge signatures, and access funds.
Importantly, this threat does not extend to Bitcoin mining, which relies on the SHA-256 algorithm. Experts suggest that using quantum computing to meaningfully disrupt mining remains decades away. Instead, the vulnerability lies in signature schemes such as ECDSA and Schnorr, both based on the secp256k1.
The research outlines three potential attack scenarios. “On-spend” attacks target transactions in progress, where an attacker could intercept a transaction, derive the private key, and submit a fraudulent replacement before confirmation. With Bitcoin’s average block time of 10 minutes, the study estimates such an attack could be executed in roughly nine minutes using optimized quantum systems, with parallel processing increasing success rates. Faster blockchains such as Ethereum and Solana offer narrower windows but are not entirely immune.
“At-rest” attacks focus on wallets with already exposed public keys, such as reused or inactive addresses, where attackers have significantly more time. A third category, “on-setup” attacks, involves exploiting protocol-level parameters. While Bitcoin appears resistant to this method, certain Ethereum features and privacy tools like Tornado Cash may face higher exposure.
Technically, the researchers developed quantum circuits requiring fewer than 1,500 logical qubits and tens of millions of computational operations, translating to under 500,000 physical qubits under current assumptions. This is a substantial improvement over earlier estimates, such as a 2023 study that suggested around 9 million qubits would be needed. More optimistic models could reduce this further, though they depend on hardware capabilities not yet demonstrated.
In an unusual move, the team did not publish the full attack design. Instead, they used a zero-knowledge proof generated through the SP1 zero-knowledge virtual machine to validate their findings without exposing sensitive details. This approach, rarely used in quantum research, allows independent verification while limiting misuse.
The findings arrive as both industry and governments begin preparing for a post-quantum future. The National Security Agency has called for quantum-resistant systems by 2030, while Google has set a 2029 target for transitioning its own infrastructure. Ethereum has been actively working toward similar goals, aiming for a full migration within the same timeframe. Bitcoin, however, faces slower progress due to its decentralized governance model, where major upgrades can take years to implement.
Early mitigation efforts are underway. A recent Bitcoin proposal introduces new address formats designed to obscure public keys and support future quantum-resistant signatures. However, a full transition away from current cryptographic systems has not yet been finalized.
For now, users are advised to take precautionary steps. Moving funds to new addresses, avoiding address reuse, and monitoring updates from wallet providers can reduce exposure, particularly for long-term holdings. While the threat is not immediate, researchers emphasize that preparation must begin well in advance, as advances in quantum computing continue to accelerate.
A newly observed version of the Chaos malware is now targeting poorly secured cloud environments, indicating a defining shift in how this threat is being deployed and scaled.
According to analysis by Darktrace, the malware is increasingly exploiting misconfigured cloud systems, moving beyond its earlier focus on routers and edge devices. This change suggests that attackers are adapting to the growing reliance on cloud infrastructure, where configuration errors can expose critical services.
Chaos was first identified in September 2022 by Lumen Black Lotus Labs. At the time, it was described as a cross-platform threat capable of infecting both Windows and Linux machines. Its functionality included executing remote shell commands, deploying additional malicious modules, spreading across systems by brute-forcing SSH credentials, mining cryptocurrency, and launching distributed denial-of-service attacks using protocols such as HTTP, TLS, TCP, UDP, and WebSocket.
Researchers believe Chaos developed from an earlier DDoS-focused malware strain known as Kaiji, which specifically targeted exposed Docker instances. While the exact operators behind Chaos remain unidentified, the presence of Chinese-language elements in the code and the use of infrastructure linked to China suggest a possible connection to threat actors from that region.
Darktrace detected the latest variant within its honeypot network, specifically on a deliberately misconfigured Hadoop deployment that allowed remote code execution. The attack began with an HTTP request sent to the Hadoop service to initiate the creation of a new application.
That application contained a sequence of shell commands designed to download a Chaos binary from an attacker-controlled domain, identified as “pan.tenire[.]com.” The commands then modified the file’s permissions using “chmod 777,” allowing full access to all users, before executing the binary and deleting it from the system to reduce forensic evidence.
Notably, the same domain had previously been linked to a phishing operation conducted by the cybercrime group Silver Fox. That campaign, referred to as Operation Silk Lure by Seqrite Labs in October 2025, was used to distribute decoy documents and ValleyRAT malware, suggesting infrastructure reuse across campaigns.
The newly identified sample is a 64-bit ELF binary that has been reworked and updated. While it retains much of its original functionality, several features have been removed. In particular, capabilities for spreading via SSH and exploiting router vulnerabilities are no longer present.
In their place, the malware now incorporates a SOCKS proxy feature. This allows compromised systems to relay network traffic, effectively masking the origin of malicious activity and making detection and mitigation more difficult for defenders.
Darktrace also noted that components previously associated with Kaiji have been modified, indicating that the malware has likely been rewritten or significantly refactored rather than simply reused.
The addition of proxy functionality points to a broader monetization strategy. Beyond cryptocurrency mining and DDoS-for-hire operations, attackers may now leverage infected systems to provide anonymized traffic routing or other illicit services, reflecting increasing competition within cybercriminal ecosystems.
This shift aligns with a wider trend observed in other botnets, such as AISURU, where proxy services are becoming a central feature. As a result, the threat infrastructure is expanding beyond traditional service disruption to include more complex abuse scenarios.
Security experts emphasize that misconfigured cloud services, including platforms like Hadoop and Docker, remain a critical risk factor. Without proper access controls, attackers can exploit these systems to gain initial entry and deploy malware with minimal resistance.
The continued evolution of Chaos underlines how threat actors are persistently enhancing their tools to expand botnet capabilities. It also reinforces the need for continuous security monitoring, as changes in how APIs and services function may not always appear as direct vulnerabilities but can exponentially increase exposure.
Organizations are advised to regularly audit configurations, restrict unnecessary access, and monitor for unusual behavior to mitigate the risks posed by increasingly adaptive malware threats.
Privacy issues have always bothered users and business organizations. With the rapid adoption of AI, the threats are also rising. DuckDuckGo’s Duck.ai chatbot benefits from this.
The latest report from Similarweb revealed that traffic to Duck.ai increased rapidly last month. The traffic recorded 11.1 million visits in February 2026, 300% more than January.
The statistics seem small when compared with the most popular chatbots such as ChatGPT, Claude, or Gemini.
Similarweb estimates that ChatGPT recorded 5.4 billion visits in February 2026, and Google’s Gemini recorded 2.1 billion, whereas Claude recorded 290.3 million.
For DuckDuckGo, the numbers show a good sign, as the bot was launched as beta in 2025, and has shown a sharp rise in visits.
DuckDuckGo browser is known for its privacy, and the company aims to apply the same principle to its AI bot. Duck.ai doesn't run a bespoke LLM, it uses frontier models from Meta, Anthropic, and OpenAI, but it doesn't expose your IP address and personal data.
Duck.ai's privacy policy reads, "In addition, we have agreements in place with all model providers that further limit how they can use data from these anonymous requests, including not using Prompts and Outputs to develop or improve their models, as well as deleting all information received once it is no longer necessary to provide Outputs (at most within 30 days, with limited exceptions for safety and legal compliance),”
What is the reason for this sudden surge? The bot has two advantages over individual commercial bots like ChatGPT and Gemini, it offers an option to toggle between multiple models and better privacy security. The privacy aspect sets it apart. Users on Reddit have praised Duck.ai, one person noting "it's way better than Google's," which means Gemini.
In March, Anthropic rejected a few applications of its technology for mass surveillance and weapons submitted by the Department of Defense. The DoD retaliated by breaking the contract. Soon after, OpenAI stepped in.
The incident stirred controversies around privacy concerns and ethical AI use. This explains why users may prefer chatbots like Duck.ai that safeguard user data from both the government and the big tech.