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PhantomCore Exploits TrueConf Flaws to Breach Russian Networks

  A pro-Ukrainian hacktivist group known as PhantomCore has been exploiting vulnerabilities in TrueConf video conferencing software to infil...

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ShinyHunters Targets McGraw Hill In Salesforce Data Leak Dispute Over Breach Scope

 

A breach at McGraw Hill came to light when details appeared on a leak page run by ShinyHunters, a hacking collective now seeking payment. Appearing online without warning, the listing suggested sensitive data had been taken. The firm acknowledged something went wrong only after outsiders pointed to the published claims. Instead of silence, there followed a brief statement - no elaborate explanations, just confirmation. What exactly was accessed remains partly unclear, though the criminals promise more leaks if demands go unmet. Their method? Take data first, then pressure victims publicly through exposure. 

Though the collective says it pulled around 45 million records from Salesforce setups, McGraw Hill challenges how serious the incident really was. A flaw in a cloud-based Salesforce setup - misconfigured, not hacked - led to what occurred, according to the company. Public release looms unless money changes hands by their stated date. Not a breach of core infrastructure, they clarify. Timing hinges on whether terms get fulfilled. What surfaced came via access error, not forced entry. 

Later came confirmation from the firm: only minor data sat exposed through a public page tied to Salesforce. Not part of deeper networks - systems handling daily operations stayed untouched. Customer records? Still secure. Educational material platforms? Unreached. Personal identifiers like income traces or school files showed no signs of exposure. The breach never reached those layers. A single weak link elsewhere might open doors wider than expected. Problems often start outside core networks, hidden in connected tools. 

One misstep in setup could ripple across several teams relying on Salesforce. When outside systems slip, sensitive details sometimes follow. Security gaps far from the main system still carry risk close to home. What seems distant can quickly become immediate. Even with those reassurances, ShinyHunters insists the breached records include personal details - setting their version against the firm’s own review. Contradictions like this often surface when attacks aim to extort, as hackers sometimes inflate what they took to push targets into responding. 

Now operating at a steady pace, ShinyHunters stands out within the underground scene by focusing less on locking files and more on quietly siphoning information. Instead of scrambling networks, they pressure victims using material already taken - payment demands follow exposure threats. Their name surfaced after breaches hit well-known companies, where leaked datasets served as leverage. Rather than causing immediate downtime, their power lies in what could be revealed. 

What stands out lately is how this group exploited a security gap at Anodet, an analytics company, gaining entry through leaked access tokens aimed squarely at cloud-based data systems. Alongside that incident came the public drop of massive corporate datasets - another sign their main goal remains pulling vast amounts of information from high-profile targets. Among recent breaches, the one involving McGraw Hill stands out - not because of its scale, but due to how it reveals weaknesses hidden within standard cloud setups. 

Instead of breaking through strong defenses, hackers often slip in via small errors made during setup steps handled by outside teams. What makes this case notable is less about immediate damage, more about what follows: sensitive information pulled quietly into unauthorized hands. While systems keep running without interruption, stolen data becomes the weapon - threatening public release unless demands are met. 

Over time, such tactics have shifted the focus of digital attacks away from crashes toward silent leaks. With probes still underway, one thing becomes clear: oversight of outside connections matters more now than ever. When digital intruders challenge what companies say, credibility hinges on openness. Tight rules around setup adjustments help reduce weak spots. How firms handle disclosures can shape public trust just as much as technical fixes. Clarity during crises often separates measured responses from confusion.

The Shift from Cyber Defense to Recovery-Driven Security


 

There has been a structural recalibration of cybersecurity strategies as organizations recognize that breaches impact operations, finances, and reputation in ways that extend far beyond the moment of intrusion. 

Incidents that once remained within the domain of IT are now affecting the entire organization, with containment cycles lasting up to months and remediation costs reaching tens of millions for large-scale breaches. 

Leaders in response are shifting their focus from absolute prevention to sustained operational continuity, recognizing that resilience is not defined by the absence of attacks, but rather by the capability of recovering quickly and precisely. 

The shift is driving a renewed focus on creating integrated cyber resilience frameworks that align business continuity objectives with security controls, ensuring critical systems remain recoverable even after active compromises. There is also a disconnect between security enforcement and operational accessibility resulting from this evolution. 

The cybersecurity function has historically prioritized perimeter hardening and strict authentication, whereas business operations demand uninterrupted data availability with minimal friction to operate. With increasing threat landscapes and competing priorities, these priorities are convergent, often revealing inefficiencies, in which layered authentication mechanisms, while indispensable, inadvertently delay recovery workflows and extend downtime during critical incidents.

By integrating adaptive intelligence and automation into Zero Trust architectures, this divide is beginning to be reconciled. The approach organizations are taking is to design environments where continuous verification is co-existing with streamlined restoration capabilities rather than treating security and recovery as opposing forces. 

Zero Trust, at its core, is a strategic model rather than a single technology that requires rigorous, context-aware authentication utilizing multiple data points prior to granting access. In combination with intelligent recovery systems, this approach is redefining resilience by enabling secure access without compromising recovery agility, resulting in high-assurance environments that are able to maintain operations even under persistent threat circumstances. 

With the increased sophistication of ransomware campaigns, conventional backup-centric strategies are revealing their limitations, as adversaries increasingly design attacks that extend beyond the initial system compromises. Threat actors execute long reconnaissance phases during many incidents, mapping enterprise environments, identifying high-value assets, and, critically, locating backups and undermining them before encrypting or destroying data.

By intentionally targeting a variety of entities, cybercrime has evolved into a coordinated and enterprise-like environment where operational disruption is designed to maximize leverage. Attackers effectively eliminate an organization's ability to restore from trusted states when they compromise recovery pathways, amplifying downtime and causing an increase in financial and regulatory risk. 

Due to this inevitability, forward-looking organizations are repositioning their security postures to reflect this inevitability, incorporating defensive controls into a more holistic security model that includes assured recoverability. As part of this approach, cyber resilience and cyber recovery are integrated, where the objective is to not only withstand intrusion attempts but to maintain data integrity, availability, and rapid restoration under adversarial circumstances. 

The modern cyber recovery architectures are reflecting these evolving threat dynamics by incorporating resilience as an integral part of their development, repositioning data protection from a passive safeguard to an active line of defense. Hardened recovery frameworks are becoming increasingly popular among organizations, which include air-gapped vaulting and immutable storage, in order to ensure backup data is not susceptible to adversarial manipulation while enabling integrity validation before restoration through advanced malware scanning. 

A controlled virtual environment is used to test recovery processes isolated from one another, along with point-in-time restoration capabilities that are capable of restoring systems back to a known, uncompromised state with minimal operational disruptions as a complement to this. 

Separate recovery enclaves are also crucial to preventing lateral movement and credential-based compromise, as backup infrastructure is decoupled from production networks, thus eliminating lateral movement pathways. This architecture ensures that security and compliance requirements are not treated as an afterthought but are integrally integrated, supported by comprehensive audit trails, tagging of data, and a verifiable chain of custody. These capabilities together provide organizations with a structured, audit-ready recovery posture that maintains business continuity, even under sustained cyber pressure, a transition from reactive incident response.

In an effort to maintain continuous visibility into backup repository integrity and behavior, organizations are extending the focus beyond safeguarding backup repositories in their resilience frameworks. There is an increasing trend among threat actors to employ persistence-driven techniques that alter backup configurations or introduce incremental data corruption to erode reliable recovery points over time—often without triggering immediate alerts. 

Unless granular monitoring is employed, manipulations of this kind can be undetected until the recovery process has been initiated, at which point recovery pathways may already be compromised. It is for this reason that enterprises are integrating advanced telemetry, behavioral analytics, and anomaly detection in backup ecosystems, enabling early detection of irregular access patterns, unauthorized configuration changes, and deviations in data consistency. 

By enhancing proactive visibility, enterprises can not only respond more quickly to incidents but also prevent adversaries from dismantling recovery capabilities silently. Rapid recovery is of little value if latent threats are reintroduced into production environments. 

Furthermore, it is important to ensure that recovered data is intact and uncompromised. In this regard, organizations are integrating validation layers, such as isolated forensic sandboxes and automated recovery testing, to verify backup integrity well in advance of a loss. 

By implementing a comprehensive architectural shift in which recovery is engineered as a fundamental capability instead of a reactive measure, enterprises are positioned to sustain operations with minimal disruption by embedding immutability, isolation, continuous monitoring, and trusted validation into data protection strategies from conception. 

Consequently, resilience is no longer based on the ability to evade every attack, but rather on the ability to restore systems as quickly and precisely as possible, especially when defenses have been breached inevitably. Cybersecurity effectiveness is no longer defined by absolute prevention, but rather by the assurance that controlled, reliable recovery can be achieved under adverse circumstances. 

A growing number of adversaries continue to develop techniques that bypass traditional defenses and target recovery mechanisms themselves, forcing organizations to adopt a design philosophy based on the expectation of compromise rather than treating compromise as an exception. 

In order to maintain operational continuity, it is imperative that security postures, continuous monitoring, and resilient recovery architectures are integrated cohesively. In order to mitigate the cascading impact of cyber incidents, enterprises should align detection capabilities with verified restoration processes and embed trust throughout the recovery lifecycle. 

The key to establishing resilience is not eliminating risk, but rather abiding by its ability to absorb disruption, restore critical systems with integrity, and sustain business operations without interruption in a world where cyber incidents have become an operational certainty rather than simply a possibility.

AI Was Meant to Help. So Why Is It Making Work Harder for Women in Indonesia?

 



Artificial intelligence is often presented as a neutral and forward-looking force that improves efficiency and removes human bias from decision-making. In practice, however, many women working in Indonesia’s gig economy experience these systems very differently. Rather than easing workloads, AI-driven platforms are intensifying existing pressures.

Recent research examining female gig workers introduces the concept of “AI colonialism.” This idea describes how older patterns of domination continue through digital systems. In this framework, powerful technology actors, largely based in wealthier regions, extract labour, data, and economic value from workers in developing countries, reinforcing unequal global relationships. The structure resembles historical colonial systems, but operates through algorithms and platforms instead of direct political control.

In Indonesia, platforms such as Gojek, Grab, Maxim, and Shopee rely heavily on informal workers. These companies have not transformed the nature of employment. Instead, they have digitised an already informal labour market. Workers are labelled as independent “partners,” which excludes them from basic protections such as minimum wages, paid sick leave, and maternity benefits. Earnings depend entirely on the number of completed tasks and algorithm-based performance scores.

For women, this structure intersects with what is often described as the “double burden,” where paid work must be balanced alongside unpaid domestic responsibilities. One delivery worker, Lia, begins her day before sunrise by preparing meals and organising her children’s routines. Only after completing these responsibilities can she log into the platform. As she explains, the system recognises only whether she is online, not the constraints shaping her availability.

Platform algorithms prioritise continuous, uninterrupted activity. Incentive systems often require completing a fixed number of orders within strict time windows. For workers managing caregiving roles, this creates structural disadvantages. Logging off to attend to family responsibilities can result in lost bonuses, while reducing work hours due to fatigue or health issues leads to declining performance metrics.

This reflects a greater economic reality in which unpaid domestic labour underpins the formal economy without recognition or compensation. Instead of addressing this imbalance, AI systems can intensify it. Another worker, Cinthia, observed a noticeable drop in job assignments after taking time off due to illness. The experience created a sense that the system penalises any interruption, making workers reluctant to pause even when necessary.

Although algorithms do not explicitly target women, they are designed around an ideal worker who is always available and unconstrained by caregiving duties. This assumption produces indirect but consistent disadvantage. The claim that digital platforms operate neutrally is further challenged by everyday experiences. For example, a driver named Yanti often informs passengers in advance that she is female, leading to frequent cancellations. While the system records these cancellations, it does not capture the gender bias behind them.

Safety concerns also shape participation. Many women avoid working late hours due to risk, which limits access to peak-demand periods and higher earnings. The system interprets this reduced availability as lower productivity. Scholars such as Virginia Eubanks have argued that automated systems frequently replicate and amplify existing social inequalities rather than eliminate them.

Similar patterns have been observed in other countries. In India, women working in ride-hailing services report lower average earnings, partly because safety considerations influence when and where they work. Algorithms, however, measure output without accounting for these risks.

Safety challenges persist even within delivery roles. Around 90% of women in group discussions reported choosing delivery work over ride-hailing due to perceived safety advantages, yet harassment remains a concern from both customers and other drivers. During the COVID-19 pandemic, gig workers were classified as essential, but their incomes declined sharply, in some cases by up to 67% in early 2020. To compensate, many worked more than 13 hours a day. Despite these conditions, platform performance systems remained unchanged, and illness-related breaks often resulted in lower ratings.

This inflicts a deeper impact in the contemporary labour control, where oversight is embedded within digital systems rather than managed by human supervisors. AI colonialism, in this sense, extends beyond ownership to the structure of control itself. Workers provide labour, time, and data, while platforms retain authority over decision-making processes.

In response, women workers have developed informal networks through messaging platforms to share information, warn others about unsafe situations, and adapt to algorithmic changes. They support each other by increasing activity on inactive accounts, lending money for operational costs, and collectively responding to account suspensions. When harassment occurs, information is circulated quickly to protect others.

These practices represent a form of mutual support rooted in shared vulnerability. Rather than relying on formal recognition as employees, many women build systems of protection among themselves. This surfaces a form of everyday resistance, where collective action becomes a strategy for navigating structural constraints.

Artificial intelligence is not inherently exploitative. However, when deployed within unequal economic systems, it can reinforce patterns of extraction and imbalance. As digital platforms continue to expand, understanding the lived experiences of workers, particularly women in developing economies, is essential. Behind every efficient system is a human reality shaped by trade-offs between income, safety, and dignity.


Rival Ransomware Gangs 0APT And Krybit Clash In Unusual Cyber Extortion Battle

 

A clash almost unseen among digital outlaws has begun - 0APT, a hacking collective, now warns it will unmask operatives from enemy faction Krybit. This shift came to light through surveillance of hidden online forums. Tension simmers beneath the surface of these underground circles. Rival gangs once operating in parallel seem to fracture under pressure. Trust, usually scarce, is vanishing faster than usual. Evidence points toward escalating friction inside ransomware communities. 

What began as covert threats may reshape alliances unexpectedly. Reports indicate 0APT sent a threat to Krybit, insisting on payment under risk of exposing private records - names, positions, operational files - if ignored. A limited set of claimed stolen materials was published shortly after, serving as evidence - a move mirroring classic dual-pressure methods seen in attacks on businesses. Yet using such an approach toward another illicit network stirs doubt around its real impact, given that public image matters little within hidden communities. 

Even so, the danger remains somewhat real. Because cybercrime networks depend on staying hidden, revealed identities might invite legal trouble or revenge attacks. From the exposed information, security analysts pulled login details tied to Krybit members - alongside digital currency wallets - hinting at weak points in how the group functions. Yet the full impact stays unclear. Now showing a blank page, Krybit's site now displays only a standard upkeep notice, hinting at disruptions tied to recent events. Little is known about the collective so far, mainly because big security analysts have published almost nothing on them - possibly a sign they are just beginning operations. 

On the opposite end, 0APT emerged around spring 2026 and gained attention fast, marked by complex tools and methods, even though some doubt surrounds how truthful their early reports of breaches really were. Odd as it seems, infighting among hackers has happened before. Earlier clashes included DragonForce going after opponents - BlackLock, then Mamona - by altering web pages and exposing private messages. 

In much the same way, activity aimed at RansomHub tied back to DragonForce, revealing ongoing friction between ransomware crews. This conflict taking shape between 0APT and Krybit signals changes in how cybercriminals operate - motives like money, dominance, and competition now spark open clashes. With ransomware networks evolving fast, these kinds of face-offs might happen more often, making it harder for security experts to follow the players involved.

UAE Businesses Warned of Escalating AI‑Powered Cyber Threats

 

UAE businesses are being urgently warned about a sharp rise in AI‑powered cyber threats that can compromise systems within hours, and sometimes even minutes, if organisations remain unprepared. Cybercriminals are increasingly using artificial intelligence to craft highly realistic phishing emails, deepfake voice and video impersonations, and automated attacks that exploit gaps in security before teams can respond. 

Nature of AI‑driven threats 

Attackers are leveraging generative AI to personalize scams at scale, including cloned emails, synthetic voices, and fake video calls that mimic senior executives or partners. These AI‑enabled methods make spear‑phishing and impersonation fraud far more convincing, increasing the chances that employees will authorise fraudulent transfers or share sensitive credentials. 

AI tools now allow adversaries to perform reconnaissance, scan for vulnerabilities, and launch password‑guessing and ransomware attacks in a fraction of the time it once took. Security experts note that many organisations now face same‑day compromises, where attackers move from initial access to data theft or system encryption within a single business day.

Impact on UAE firms and the economy 

The UAE’s role as a regional financial and technology hub makes it a prime target for state‑backed and criminal hacking groups that use AI to intensify their campaigns.Breaches can lead to substantial financial losses, reputational damage, regulatory penalties, and disruption of critical services, especially as digital‑government and smart‑city initiatives expand.

Cyber professionals recommend continuous staff training on spotting AI‑powered phishing and impersonation, tightening access controls, securing machine identities, and maintaining tested incident‑response and recovery plans. With AI adoption accelerating across industries, firms that act quickly to strengthen cyber resilience will be better positioned to withstand the next wave of AI‑enhanced cyber threats in the UAE.

Pre Stuxnet Fast16 Threat Revealed Targeting Engineering Environments


 

New discoveries regarding early stages of cyber sabotage are changing the historical timeline of offensive digital operations and revealing that sophisticated disruption techniques were developed well before they became widely popular. 

An undocumented malware framework that was discovered in the mid-2000s underscores the extent to which threat actors were already manipulating industrial and engineering systems with precision, laying the foundations for highly specialized cyber weapons that would develop later in time. 

A Lua-based malware framework, named fast16, which predates the outbreak of the Stuxnet worm by several years has been identified by cybersecurity researchers based on this context. According to a detailed analysis published by SentinelOne, the framework originated around 2005, with its operational focus focused on engineering and calculation software with high precision. 

The fast16 algorithm was designed rather than causing immediate system failure to introduce inaccuracies that propagate across interconnected environments by subtly corrupting computational outputs. With its lightweight scripting capabilities and seamless integration with C/C++, Lua is an excellent choice for modular malware development, allowing attackers to extend functionality without recompiling core components. 

Upon analyzing fast16, researchers identified distinct Lua artifacts, including bytecode signatures beginning with /x1bLua and environmental markers such as LUA_PATH, which allowed them to trace svcmgmt.exe, a sample which initially appeared benign, but ultimately appeared to be a part of the early attack framework.

Researchers Vitaly Kamluk and Juan Andrés Guerrero-Saade concluded that the malware's architecture suggested a deliberate intent to spread disruption through self-propagation mechanisms, effectively standardizing erroneous results across entire facilities through self-propagation mechanisms. This approach is a reflection of an early understanding of systemic compromise, which emphasizes data integrity rather than availability as the primary attack vector. 

Fast16 is estimated to have emerged at least five years before Stuxnet, widely regarded as the first digital weapon designed for physical disruption of the world. While fast16 offers a compelling precedent, despite the historical association between Stuxnet and state-sponsored efforts to disrupt Iran's nuclear infrastructure and later influence Duqu and other tools.

The report demonstrates that conceptual basis for cyber-physical sabotage had already been explored in earlier, less visible campaigns, suggesting a more advanced and complex evolution of offensive cyber capabilities than previously assumed. Further reverse engineering confirmed that fast16 did not conform to typical malware engineering patterns observed in the mid-2010s. 

In response to Vitaly Kamluk's observation, several implementation choices indicated that the project was developed much earlier than it was actually implemented, a view that SentinelOne later reinforced by environmental and code-level constraints. 

The sample exhibits compatibility limitations consistent with legacy systems, which can only be executed reliably on Windows XP and single-core processors, which were pre-existing when multi-core consumer processors were introduced by Intel in 2006.

In accordance with behavioral analysis, the implant implements a kernel-level component, fast16.sys, in conjunction with worm-like propagation routines to establish persistence. Moreover, its architecture predates other advanced threats such as Flame, as well as being among the earliest known examples of a Windows-based malware that embeds a Lua virtual machine as an integral component. 

Initially identified as a generic service wrapper, the svcmgmt.exe executable appears to have originated the framework. However, it was later discovered to contain the Lua 5.0 runtime and encrypted bytecode payload, which formed the framework. As indicated by the timestamp metadata, the build date is August 2005, and the submission to VirusTotal was more than a decade later, further supporting the fact that the program has a long history.

In an in-depth inspection, it was revealed that Windows NT subsystems were tightly integrated, including direct interaction with the file system, registry, service control, and networking APIs. In addition to the Lua bytecode containing the core execution logic, an associated driver whose PDB path dates July 2005 enables interception and manipulation of executable data while the data is being read from the disk, an advanced stealth and control technique. 

Additionally, references to "fast16" have been found within driver lists associated with sophisticated intrusion toolsets reportedly linked to the National Security Agency, which were disclosed by Shadow Brokers. By combining technical lineage with leaked operational tooling, this intersecting information further exacerbates the ambiguity surrounding the framework's origins, highlighting its significance within the early development of cyber-physical attack methodologies. 

Further analysis positions svcmgmt.exe as the operational core of the framework, operating as a highly flexible carrier that can adapt execution paths depending on runtime conditions. SentinelOne asserts that embedded forensic markers, particularly a path in the PDB, establish a link between the sample and deconfliction signatures which were revealed in leaks attributed to tools used by the National Security Agency, suggesting that the origin is far more sophisticated. 

From an architectural perspective, the module consists of three components: Lua bytecode controlling configuration and propagation logic, a dynamic library that assists with configuration, and a kernel-level driver (fast16.sys) that performs low-level manipulations. After installation of the malware as a Windows service, it can elevate privileges by activating the kernel implant and initiating a controlled propagation routine that targets legacy Windows environments with weak authentication controls once deployed. 

There is a particular emphasis on operational stealth in its conditional execution, which either occurs manually or when specific security products are detected through registry inspections, indicating an early but deliberate effort to extend its spread. On a functional level, the kernel driver represents the framework's sabotage capability, intercepting executable flows and modifying them according to rule-based rules, especially against binaries compiled using Intel C/C++ tools. As a result, the outputs of high-precision engineering and simulation platforms such as LS-DYNA, PKPM, and MOHID can be precisely manipulated. 

Through the introduction of subtle, systematic deviations into mathematical models, this malware can negatively impact simulation accuracy, undermine research integrity, and affect real-world engineering outcomes over the long term. Further enhancement of situational awareness is provided by supporting modules; for example, a network monitoring component logs connection information through Remote Access Service hooks, strengthening the framework's surveillance capabilities.

Modular separation of a stable execution wrapper from encrypted, task-specific payloads promotes a reusable design philosophy, thus allowing operators to tailor deployments while maintaining a stable outer binary footprint. As a result of these findings, the timeline for cyber-physical attacks has been significantly revised in comparison to the broader threat landscape. 

A correlation with artifacts released by the Shadow Brokers, as well as a correlation with early offensive toolchains, suggest that capabilities often associated with later campaigns, including Stuxnet, were being developed and could have been deployed years earlier. As a result, fast16 is no longer merely an isolated discovery, but also a transitional framework bridging covert early stage experimentation with the more visible development of advanced persistent threats.

During the period covered by this paper, state-aligned actors operationalized long-term, precision-focused sabotage strategies well before such activities became public knowledge, a year in which software became a major tool for influencing physical systems on a strategic level. 

A number of factors, including the emergence of fast16, reframe long-held assumptions about the origins of cyberphysical sabotage, demonstrating that highly targeted, computation-focused attack models were operational well in advance of their public recognition. This modular design, selective propagation logic, and precision-driven payloads demonstrate a maturity typically associated with advanced persistent threat campaigns of a later stage.

The report emphasizes, in addition to its strategic significance, the shift away from disruptive attacks that target system availability to covert manipulation of data integrity within critical engineering environments. 

Fast16 is therefore both an historical anomaly and the prototype of modern state-aligned cyber operations, in which subtle interference can have a far-reaching impact without immediate detection within critical engineering environments.

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