Open Access

Phishing remains one of the most common and effective forms of social engineering, with cybercriminals constantly refining their tactics to exploit human vulnerabilities. The sheer volume of phishing attacks is staggering: almost 1.2% of all emails sent are malicious. This equates to around 3.4 billion phishing emails per day. The effectiveness of phishing attacks is also underlined by numerous studies. Phishing is identified as the leading initial attack vector, responsible for 41% of security incidents. This means that practically every company is threatened by phishing attacks.In parallel, there have been rapid advances in the field of artificial intelligence (AI) in recent years, giving the general public access to powerful tools that can handle complex tasks with ease. However, alongside these benefits, the potential for abuse has also become a major concern. The integration of AI into social engineering attacks has significantly increased the opportunities for cybercriminals. Research has shown that AI-generated phishing emails are difficult for humans to distinguish from real messages. According to one study, phishing emails written by AI were opened by 78% of recipients, with 21% clicking on malicious content such as links or attachments. Although the click-through rate is still lower compared to human-crafted emails, generative AI tools (GenAI) can help cybercriminals compose phishing emails at least 40% faster, which can lead to a significant increase in phishing success rates. The increasing potential to use public AI tools for abusive purposes has also been recognized by the developers of AI models. Thus, publicly available AI tools often have built-in mechanisms to detect and prevent misuse. This paper examines the potential for misuse of publicly available AI in the context of phishing attacks, focusing on the content generation phase. In particular, the study examines the effectiveness of existing abuse prevention mechanisms implemented by AI platforms like fine-tuning, filters, rejection sampling, system prompts and dataset filtering. To this end, it is explored how prompts to the AI need to be altered for circumventing the misuse preventing mechanisms. While in some cases the simple request to write a phishing email succeeds, other AI tools implement more sophisticated mechanisms. In the end, however, all prevention safeguards could be circumvented. The findings highlight the significant threat posed by AI-powered social engineering attacks and emphasize the urgent need for robust defense in depth strategies against phishing attacks and increased awareness to mitigate the risks in the evolving digital landscape.In addition, the paper demonstrates that the quality of the AI tool varies in terms of the phishing emails generated. To this end, the phishing emails generated by circumventing the protection mechanisms of the AI are (subjectively) compared and evaluated by the authors. The preliminary conclusion is that automatically generated phishing emails of some public AI tools can certainly match that of manually generated emails. While the objective confirmation of this hypothesis requires further study even the subjective quality of the generated phishing emails shows the dimension of the problem.

The bioconversion of salinized land into healthy agricultural systems by utilizing low-rank coal (LRC) is a strategic approach for sustainable agricultural development. The aims of this study were: (1) to isolate bacterial strains associated with the rhizosphere of native plants in coal-containing soils, (2) to characterize their plant growth-promoting (PGP) and coal-solubilizing capabilities under laboratory conditions and (3) to evaluate their influence on the germination and growth of chia seeds under saline stress. Fourteen bacterial cultures were isolated from the rhizosphere of Artemisia annua L. using culture media containing salt and coal. Based on their PGP activities (nitrogen fixation, phosphate solubilization, siderophore and indole-3-acetic acid production), five strains were selected, belonging to the genera Bacillus, Phyllobacterium, Arthrobacter, and Pseudomonas. Solubilization assays were conducted to confirm the ability of these strains to utilize coal efficiently. Finally, the selected strains were inoculated with chia seeds (Salvia hispanica L.) to evaluate their ameliorating effect under saline stress conditions in coal-containing media. Inoculation with A. subterraneus Y1 resulted in the highest germination and growth metrics of chia seeds. A positive but comparatively weaker response was observed with P. frederiksbergensis AMA1 and B. paramycoides Lb-1 as inoculants. Coal inoculated with halotolerant bacteria can serve as the foundation for humified organic matter in salt-affected environments. The selected halotolerant bacteria enhance coal biotransformation while exhibiting PGP traits.

The SAMLER-KI (Semi-autonomous Micro Rover for Lunar Exploration using Artificial Intelligence) project aims to open up further potential for future lunar micro rover missions. The focus is on the conceptual design of a micro rover with a higher level of autonomy and the ability to survive the lunar night. Achieving this capability requires a sophisticated thermal design to endure the harsh lunar environment and maintain acceptable temperatures not only during the extreme cold of the lunar night but also while addressing the power demands of autonomous exploration activities during daytime operations. Simultaneously, the structural design must withstand the vibration loads experienced during rocket launch. The design process is challenged by the conflicting requirements between the structural and thermal subsystems, further compounded by the mission’s mass requirement of 20 kg. An initial rover design has been developed in alignment with these requirements and the overall mission scenario. This paper presents a structural and thermal assessment of the preliminary rover design concept under mission-relevant load conditions. The analyses identify critical design weaknesses, including major parasitic thermal pathways and structurally vulnerable components. Although the current design does not yet meet the imposed requirements, the findings provide essential insights into critical areas that show potential for improvement. These results are expected to guide future iterations towards achieving a feasible and robust thermal and structural design.

The increasing demand for bio-based chemicals and sustainable materials has placed biomass-derived lactic acid in the spotlight as a key building block for biodegradable polylactic acid (PLA). Perennial ryegrass (Lolium perenne) is a promising feedstock due to its high dry matter (DM) yield, adaptability, and widespread agricultural use. This study investigates an integrated lactic acid–silage cascade process, focusing on how pH regulation, harvest timing, and biomass characteristics influence lactic acid production while maintaining agronomic efficiency. The results highlighted the crucial role of pH management and silage duration in optimizing lactic acid production. A silage period of 21 days was found to be optimal, as peak lactic acid yields were consistently observed at this stage. Maintaining a pH range of 4.5 to 6 proved essential for stabilizing fermentation, with citrate buffering at pH 6 leading to the highest lactic acid yields and minimizing undesirable by-products. Harvest timing also significantly affected lactic acid yield per hectare. While later harvesting increased total DM yield, it led to a decline in lactic acid concentration per kg DM. Tetraploid ryegrass (Explosion) maintained stable lactic acid yields due to higher biomass accumulation, whereas diploid varieties (Honroso) experienced a net reduction. From an agronomic perspective, optimizing harvest timing and variety selection is key to balancing biomass yield and fermentation efficiency. While tetraploid varieties offer greater flexibility, diploid varieties require precise harvest timing to avoid losses. These findings contribute to sustainable forage management, improving lactic acid production, silage efficiency, and agricultural resource use.

The paper at hand evaluates the necessity of depicting topographic features like boulders on the lunar environment in thermal analyses for a size of up to 6.5 m in diameter. The question regarding the thermal influence becomes relevant when analysing a technical system within the lunar environment. This influence on the thermal behaviour of a test object is investigated in sensitivity studies. It is shown that the local surroundings can significantly alter a system’s net heat flux and can lead to overheating or critically cooling down instead of theoretically surviving when not considering local topographic features. Especially for small and lightweight systems ≤20 kg, like micro rovers, the effect of the surrounding on the system’s temperature becomes critical due to the low thermal capacity. Thus, it is a substantial aspect to be accounted for during the design phase as well as in mission operation.