Search Results (88)

The Pampas fox (Lycalopex gymnocercus) is a widespread meso-predator in Southern South America, present in grasslands, agroecosystems, and human-modified landscapes. Although numerous studies have examined its diet, parasites, distribution, and behaviour, knowledge remains fragmented without an integrative synthesis. This review compiles over 150 documents from Argentina, Uruguay, Brazil, Paraguay, and Bolivia to unify dispersed information. Key findings highlight unresolved taxonomy, population structure, and biogeography (based on genetic, morphological, and phylogeographic data), the species’ ecological roles as a meso-predator, seed disperser, and scavenger, and major threats (including road mortality, hunting, persecution, and interactions with domestic dogs). The Pampas fox also harbours pathogens—including zoonotic agents and those threatening livestock and pets—and is frequently stigmatised as a pest, persecuted without substantiated evidence. By integrating ecological, health, and conflict perspectives, this review provides a regional baseline, reframing its importance and guiding more effective management. Full article

Objectives: This study aims to present an AI-driven threat-hunting framework that automates both hypothesis generation and hypothesis validation through a hybrid deep learning model that combines Convolutional Neural Networks (CNN) with Long Short-Term Memory (LSTM) networks. The objective is to operationalize proactive threat hunting by embedding anomaly detection within a structured workflow, improving detection performance, reducing analyst workload, and strengthening overall security posture. Methods: The framework begins with automated hypothesis generation, in which the model analyzes network flows, telemetry data, and logs sourced from IoT/IIoT devices, Windows/Linux systems, and interconnected environments represented in the TON_IoT dataset. Deviations from baseline behavior are detected as potential threat indicators, and hypotheses are prioritized according to anomaly confidence scores derived from output probabilities. Validation is conducted through iterative classification, where CNN-extracted spatial features and LSTM-captured temporal features are jointly used to confirm or refute hypotheses, minimizing manual data pivoting and contextual enrichment. Principal Component Analysis (PCA) and Recursive Feature Elimination with Random Forest (RFE-RF) are employed to extract and rank features based on predictive importance. Results: The hybrid model, trained on the TON_IoT dataset, achieved strong performance metrics: 99.60% accuracy, 99.71% precision, 99.32% recall, an AUC of 99%, and a 99.58% F1-score. These results outperform baseline models such as Random Forest and Autoencoder. By integrating spatial and temporal feature extraction, the model effectively identifies anomalies with minimal false positives and false negatives, while the automation of the hypothesis lifecycle significantly reduces analyst workload. Conclusions: Automating threat-hunting processes through hybrid deep learning shifts organizations from reactive to proactive defense. The proposed framework improves threat visibility, accelerates response times, and enhances overall security posture. The findings offer valuable insights for researchers, practitioners, and policymakers seeking to advance AI adoption in threat intelligence and enterprise security. Full article

The Philippine brown deer (Rusa marianna Desmarest, 1822) is a tropical cervid increasingly threatened by hunting and habitat loss. It is endemic to the Philippine archipelago, now listed as Endangered under the Philippine Red List and as Vulnerable in the IUCN Red List. This study examined the cultural sensitivities and perspectives of the Mandaya Indigenous peoples through in-depth interviews with 29 Indigenous experts and community observations from Davao Oriental, Philippines. In Mandaya cosmology, the brown deer is known as Yatag ni Magbabaya, or a gift from the Creator, and is regarded as an integral part of Mandaya culture and the ancestral lands. The brown deer is a sacred species and an indigenous food source, and its hunting is a Mandaya tradition passed down through generations. Anthropogenic disturbances remain the leading threats against the brown deer, including forest clearing and indiscriminate hunting. Poverty is also a critical driver of hunting pressures, inducing many community members to depend on forest resources and products. The causal layered analysis revealed that human-deer interactions shape local perspectives on conservation, providing insights into the effectiveness of national protection policies. In addition, the futures triangle envisions a sustainable brown deer population to address food security and economic challenges. The research findings call for culturally sensitive conservation strategies and contextualised community education that align with the Mandayas’ traditions and values. Their engagement ensures that conservation goals are met while addressing the community’s socio-economic needs. This study also emphasises the urgent need to reassess the brown deer conservation status to inform protection and management decisions. Full article

Aujeszky’s disease, or pseudorabies, is a viral infection caused by Suid herpesvirus 1 (pseudorabies virus), with swine as its natural host. Although eradicated in domestic pigs in many European countries, PRV remains endemic in wild boar populations, posing a risk to other species, including carnivores. In this study, we report eight fatal cases of PRV infection in hunting dogs from Epirus and Thessaly, Greece, all of which followed direct contact with hunted wild boars. Postmortem brain samples tested positive for PRV via PCR targeting the glycoprotein C (gC) gene. Partial sequencing and phylogenetic analysis of the amplified gC fragments revealed genetic divergence among the examined isolates. The Epirus-derived strains formed a distinct cluster, closely related to previously reported Greek strains from the region of Central Macedonia as well as to the French strain FRA 527 and the German isolate GER614BW. In contrast, the two Thessaly sequenced isolates were phylogenetically distant from all other Greek strains, potentially representing an independently evolving lineage, and clustered more closely with the Kaplan strain. These findings underscore the persistent threat of PRV transmission from wild to domestic species and highlight the genetic heterogeneity of PRV strains circulating in Greece. Veterinary practitioners should consider PRV in the differential diagnosis of encephalitic symptoms in hunting dogs. Enhanced molecular surveillance and public awareness are critical to mitigating the risks posed by this emerging threat. Full article

Major human impacts on New Zealand’s ecology began about 800 years ago with immigration firstly from Polynesia, then Europe starting a few centuries later. The humans cleared habitat, hunted species to extinction, and introduced biota, including plants, birds, fish, invertebrates, and mammals. Over the last 70 years, government-funded campaigns have been waged against some of the introduced mammals that became considered harmful to native biota. These campaigns spread poisonous food baits from aircraft to kill and suppress target animals (mainly brushtail possums (Trichosurus vulpecula) and rats (Rattus spp.)) over large areas. Increased intensity, frequency, and scale of poisoning are being trialled under a new conservation strategy (Predator Free 2050) to eradicate several mammalian species. The present study investigates the opportunity for a paradigm shift in conservation, emphasizing the rationales for transitioning from spreading of pesticides to a more targeted approach. NZ’s poison- and predator-focused ecological management has been criticized internationally as cruel and unnecessary, while independent NZ ecologists have called for, and outlined, a new system of conservation management based on ecological knowledge, which embraces all threats to native biota. A central tenet of proposed new methods is the engagement of all relevant stakeholders. Efficient management tools include remote monitoring, and smart, self-resetting kill traps for targeted small mammal control. Ecology-driven, commercially sound, targeted, monitored, relatively humane management can be implemented to protect the remnants of NZ’s natural heritage. Full article

Malicious actors often exploit persistence mechanisms, such as unauthorized modifications to Windows startup directories or registry keys, to achieve privilege escalation and maintain access on compromised systems. While information technology (IT) teams legitimately use these AutoStart Extension Points (ASEPs), adversaries frequently deploy malicious binaries with non-standard naming conventions or execute files from transient directories (e.g., Temp or Public folders). This study proposes a threat-hunting framework using a custom Elasticsearch Security Information and Event Management (SIEM) system to detect such persistence tactics. Two hypothesis-driven investigations were conducted: the first focused on identifying unauthorized ASEP registry key modifications during user logon events, while the second targeted malicious Dynamic Link Library (DLL) injections within temporary directories. By correlating Sysmon event logs (e.g., registry key creation/modification and process creation events), the researchers identified attack chains involving sequential registry edits and malicious file executions. Analysis confirmed that Sysmon Event ID 12 (registry object creation) and Event ID 7 (DLL loading) provided critical forensic evidence for detecting these tactics. The findings underscore the efficacy of real-time event correlation in SIEM systems in disrupting adversarial workflows, enabling rapid mitigation through the removal of malicious entries. This approach advances proactive defense strategies against privilege escalation and persistence, emphasizing the need for granular monitoring of registry and filesystem activities in enterprise environments. Full article

This paper examines near-term generative large language models (GenLLM) for cybersecurity applications. We experimentally study three common use cases, namely the use of GenLLM as a digital assistant, analysts for threat hunting and incident response, and analysts for access management in zero trust systems. In particular, we establish that one of the most common GenLLMs, ChatGPT, can pass cybersecurity certification exams for security fundamentals, hacking and penetration testing, and mobile device security, as well as perform competitively in cybersecurity ethics assessments. We also identify issues associated with hallucinations in these environments. The ability of ChatGPT to analyze network scans and security logs is also evaluated. Finally, we attempt to jailbreak ChatGPT in order to assess its application to access management systems. Full article

Global biodiversity losses continue despite intensive conservation efforts. Many mammal species are understudied due to their specialized ecological niches. One such species is the Philippine colugo (Cynocephalus volans), a nocturnal endemic species in the Philippines. In this study, we utilized Local Ecological Knowledge (LEK) to obtain baseline information on species knowledge, attitudes, population status, and threats. Between June and September 2023, we interviewed 471 residents across all villages in Anda, Bohol. The majority of local people recognized the species and had witnessed it in Anda, occasionally near households. Residents have limited knowledge of colugo diet and distribution, which they get primarily through word-of-mouth and personal experience. The species is perceived as neutral, but the willingness to conserve it is high. Although the Philippine colugo population seems to be present in several villages in Anda, one-fourth of the respondents believe it is declining. We identified hunting for consumption as the main threat to the colugo population in Anda, which, together with other threats, may corroborate this result. We recommend actively involving male farmers in colugo population monitoring and behavioral observations, as well as investigating the drivers and importance of colugo meat consumption among residents to design a proper conservation strategy. Full article

The elongated tortoise (Indotestudo elongata), a Critically Endangered (CR) species, faces numerous threats across its range. Yet, the ecological and anthropogenic factors affecting its conservation in fragmented habitats remain poorly understood. This study integrated field surveys and community questionnaires to assess the distribution drivers and local perceptions, such as attitudes, knowledge, conservation practices, and perceived threats, in the Jalthal Forest, one of the last remnants of suitable habitat for the elongated tortoise in eastern Nepal. Using ArcMap, we established 138 randomly selected grids (500 m × 500 m) to evaluate the environmental covariates of tortoise occurrence and anthropogenic pressures. Generalized linear models revealed that tortoise occurrence was negatively associated with dense ground cover (β = −3.50, p = 0.017) and human disturbance (β = −8.11, p = 0.019). Surveys of local residents from community forest user groups (n = 236 respondents) indicated strong local support for tortoise conservation (69% willing to protect the species). Despite this, the respondents identified persistent threats, including hunting for bushmeat and traditional medicine (74%), habitat degradation (65%), and forest fires. While 60% of the respondents recognized the threatened species status, significant knowledge gaps regarding that status and ongoing illegal exploitation persisted. These findings underscore the need for targeted habitat management, reduced anthropogenic pressures, and community-led initiatives to align local attitudes with conservation actions. This study provides critical baseline data for conserving the elongated tortoise in human-modified landscapes and emphasizes the necessity of integrated ecological and socio-cultural strategies for its long-term survival. Full article

As Advanced Persistent Threats (APTs) continue to evolve, constructing a dynamic cybersecurity knowledge graph requires precise extraction of entity–relationship triples from unstructured threat intelligence. Existing approaches, however, face significant challenges in modeling low-frequency threat associations, extracting multi-relational entities, and resolving overlapping entity scenarios. To overcome these limitations, we propose the Symmetry-Aware Prototype Contrastive Learning (SAPCL) framework for joint entity and relation extraction. By explicitly modeling syntactic symmetry in attack-chain dependency structures and its interaction with asymmetric adversarial semantics, SAPCL integrates dependency relation types with contextual features using a type-enhanced Graph Attention Network. This symmetry–asymmetry fusion facilitates a more effective extraction of multi-relational triples. Furthermore, we introduce a triple prototype contrastive learning mechanism that enhances the robustness of low-frequency relations through hierarchical semantic alignment and adaptive prototype updates. A non-autoregressive decoding architecture is also employed to globally generate multi-relational triples while mitigating semantic ambiguities. SAPCL was evaluated on three publicly available CTI datasets: HACKER, ACTI, and LADDER. It achieved F1-scores of 56.63%, 60.21%, and 53.65%, respectively. Notably, SAPCL demonstrated a substantial improvement of 14.5 percentage points on the HACKER dataset, validating its effectiveness in real-world cyber threat extraction scenarios. By synergizing syntactic–semantic multi-feature fusion with symmetry-driven dynamic representation learning, SAPCL establishes a symmetry–asymmetry adaptive paradigm for cybersecurity knowledge graph construction, thus enhancing APT attack tracing, threat hunting, and proactive cyber defense. Full article

Proactively hunting known attack behaviors within system logs, termed threat hunting, is gaining traction in cybersecurity. Existing methods typically rely on constructing a query graph representing known attack patterns and identifying it as a subgraph within a system-wide provenance graph. However, the large scale and redundancy of provenance data lead to poor matching efficiency and high false-positive rates. To address these issues, this paper introduces SGMNet, a supervised seeded graph-matching network designed for efficient and accurate threat hunting. By selecting indicators of compromise (IOCs) as initial seed nodes, SGMNet extracts compact subgraphs from large-scale provenance graphs, significantly reducing graph size and complexity. It then learns adaptive node-expansion strategies to capture relevant context while suppressing irrelevant noise. Experiments on four real-world system log datasets demonstrate that SGMNet achieves a runtime reduction of over 60% compared to baseline methods, while reducing false positives by 35.2% on average. These results validate that SGMNet not only improves computational efficiency but also enhances detection precision, making it well suited for real-time threat hunting in large-scale environments. Full article

Considering the taxonomic uncertainties of Neotropical deer species, as well as the threat status of many of them, new studies and strategies for their maintenance are urgently needed. Obtaining live cells is of great importance for the conservation of wild species in order to allow cytogenetic and molecular studies to be carried out and for the construction of genomic resource banks. In order to increase the genetic diversity stored in these banks, the possibility of collecting skin fragments from dead animals (e.g., run over, hunted, deaths related to disease or natural causes) becomes a valuable source and a last alternative for obtaining material from these individuals. However, the interval between the death of the animal and the collection of tissue can directly interfere with the quality of the sample obtained and it is therefore essential to identify the maximum time during which viable cells are still found. Thus, this study sought to establish a protocol for the collection, storage, cryopreservation, and cultivation of skin obtained postmortem from individuals of the species Subulo gouazoubira (gray brocket deer) and Mazama rufa (red brocket deer). The collection of tissue fragments at different postmortem intervals (0 h, 1 h, 2 h, 3 h, 4 h, 5 h, 6 h, 7 h, 8 h, 9 h, 10 h, and 11 h) was evaluated. The tissues were analyzed for fibroblast cell viability immediately after collection. Their ability to undergo cryopreservation was evaluated based on techniques that can be directly applied to samples obtained in the field and their subsequent thawing and success of cell cultures was performed in the laboratory. Regarding the genetic integrity of the cells, the number of metaphases was observed by the mitotic index. The cell viability presented by the samples always remained above 60%. It was possible to establish cell cultures even with the tissues obtained 11 h after the death of the individuals; however, they required twice as many days to reach bottle confluence compared to the cultures performed with the tissues obtained 0 h after the death of the individuals. The results suggest that the best rates of cell viability, time to reach confluence, and number of metaphases per cell (mitotic index) are found in skin fragments collected up to 5 h after the death of individuals when their carcasses are kept at room temperature. Full article

The introduction of alien species may pose an enormous threat to indigenous flora and fauna. Among introduced animals, probably the most destructive to the natural environment are mammals. This is true at least in regard to the Afrotropical Region (sub-Saharan Africa). This review attempts to summarize our knowledge on alien mammals in this region and their impact on indigenous vertebrate fauna. This review includes 56 mammal species, belonging to 20 families, introduced to sub-Saharan Africa over the last 2000 years. Most are representatives of the following orders: Artiodactyla, Carnivora, and Primates. Most species introduced to sub-Saharan Africa originated from the Oriental (n = 20) and Palearctic (n = 19) regions. Two species, Mus musculus and Rattus rattus, were introduced before 1400 (probably as early as 800 AD), while three others were introduced between 1401 and 1700. The first half of the 17th century saw the highest number (n = 10) of introduced species. Between 1651 and 1850, only two species were introduced; in the following 175 years (1851–2025), as many as 24 species were introduced. Ten of the introduced mammal species, namely Sus scrofa, Capra hircus, Rattus rattus, R. norvegicus, Mus musculus, Felis catus, Canis familiaris, Viverricula indica, Urva auropunctata, and Maccaca fuscicularis, have become invasive species. A total of 39 mammal species were relocated (mainly for hunting purposes) within sub-Saharan Africa. Most of them were representatives of the family Bovidae (76.9%). Relocations are not considered introductions. Based on published records of the impacts of alien mammals on the vertebrate fauna of sub-Saharan Africa, the following mechanisms may be distinguished: predation, competition, hybridization, transmission of diseases and parasites, and habitat destruction (grazing, herbivory, browsing). Most vertebrate species (79.4%) were affected through direct predation, predation and habitat destruction (7.1%), or predation and competition (1.4%). Alien mammals have caused habitat destruction for only 10 species (7.1%). Other effects (competition and genetic pollution) were marginal (3.5%). At least 144 vertebrate species, representing 52 families, have been affected by alien mammals in sub-Saharan Africa: 3 amphibians, 23 reptiles, 89 birds, and 29 mammals. As a result of mammal introductions, 65 species in sub-Saharan Africa have become globally extinct, 45 are considered threatened (listed in the RDB), and 31 other species are in decline, although not included in the RDB. Most extinct birds were affected by introduced rats, mice, feral cats, and dogs. In continental Africa, only seven vertebrate species have been negatively affected by alien mammals. All other affected vertebrates occur on islands. An especially high rate of extinction has been recorded in the Mascarene Islands. In comparison with alien birds in sub-Saharan Africa, the number of introduced mammal species is much lower, but their negative impact on vertebrate fauna is significantly greater. Full article

One of the main threats for the survival of the Iberian lynx is infectious disease. Feline parvoviruses cause often fatal diseases in cats and have been isolated from different species of Felidae and other carnivores. The present study is the first description of a parvoviral sequence isolated from the brain of an Iberian lynx which died four weeks after being transferred to a quarantine centre from a hunting estate in Castilla-La-Mancha (southern border of the Iberian plateau). Four days prior to death, it had developed anorexia and muscle weakness. The nucleotide sequence, at 4589 nt long (GenBank PP781551), was most proximal to that isolated from a Eurasian badger in Italy but also showed great homology with others from cats and other carnivores isolated in Spain and Italy, including that from a cat sequenced by us to elucidate the origin of the infection, which has not been clarified. The phylogenetic analysis of the capsid protein, VP2, which determines tropism and host range, confirmed that the lynx sequence was most proximal to feline than to canine parvoviruses, and was thus typed as Protoparvovirus carnivoran1. More studies, including serology, are needed to understand the pathogenesis of this infection. Full article

This paper explores the potential use of Large Language Models (LLMs), such as ChatGPT, Google Gemini, and Microsoft Copilot, in threat hunting, specifically focusing on Living off the Land (LotL) techniques. LotL methods allow threat actors to blend into regular network activity, which makes detection by automated security systems challenging. The study seeks to determine whether LLMs can reliably generate effective queries for security tools, enabling organisations with limited budgets and expertise to conduct threat hunting. A testing environment was created to simulate LotL techniques, and LLM-generated queries were used to identify malicious activity. The results demonstrate that LLMs do not consistently produce accurate or reliable queries for detecting these techniques, particularly for users with varying skill levels. However, while LLMs may not be suitable as standalone tools for threat hunting, they can still serve as supportive resources within a broader security strategy. These findings suggest that, although LLMs offer potential, they should not be relied upon for accurate results in threat detection and require further refinement to be effectively integrated into cybersecurity workflows. Full article