Cracks and keygens have long been a problem for software vendors in that they allow users to install their products without needing to pay for a legitimate license. As the Internet and website development advanced and became more accessible, the number of sites offering software cracking tools grew.
Our research team recently searched the Web for websites that peddle cracks and keygens in an attempt to add more artifacts to publicly available lists of indicators of compromise (IoCs). We used 39 domains identified as IoCs as a starting point and found:
time lapse tool keygen crack
Our research team collated 39 domains known for hosting malicious crack and keygen sites. Accessing any of these is harmful to corporate network-connected users in that the activity could lead to malware infection. Worse than that, however, using cracked software is illegal and companies that allow employees to use them could be fined as much as US$150,000 if proven to have committed software piracy in the U.S.
We began by subjecting the IoCs to DNS lookups, which led to the discovery of 500 IP addresses to which they resolved. Based on the results, most of the crack and keygen sites pointed to the U.S., Netherlands, Germany, Canada, China, and France.
Exhaustive threat intelligence can help security teams uncover more malicious web properties than those that appear on publicly available lists of IoCs. Our IoC expansion study also showed that cracks and keygens remain an issue given the thousands of domains pointing to websites that sell them registered just this year.
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Usando esta ferramenta, o processo é simples, pois ele pode ser. Para criar um time-lapse, tudo o que você precisa fazer é carregar suas fotos para o aplicativo, defina a taxa de quadros, juntamente com outras definições e você está pronto para exportar o filme. A interface é muito bem projetado, concedendo-lhe acesso rápido a todos os seus recursos para um fluxo de trabalho eficiente.
It has a decent list of ways you might try to do it. However, there is no guarantee that the desired amount of time would actually elapse until the "lock" was broken. In other words, significantly more or significantly less time might be required.
Most of the ways available depend on needing to run an operation on a computer that will take a certain amount of time before the final decryption key can be obtained. However, you have no control over hardware. Ergo, you have no real control over the amount of time that would elapse before the final decryption key is acquired.
Oh I suppose you could encode using a really really large key .The brute force crack techqnique might then have the expected crack time of 200 years. But the key is calculable, using a process that must be linearly done, so that no parallism is allowed, and it will take 20 years at 20 Gigaflops to process. Actually the speed limit is around 4 Ghz so recently cpu pwoer is coming from parallelism.. which cannot help a linear algorithm... But there is a risk that someone would divise a way to find the resulting key without doing all the intermediate calculations, and thus turn 20 years into a short time ..
This research is the first to map ocean microplastics over such a large area and is the first to map concentrations at a high temporal resolution, revealing seasonal variations in microplastic concentrations. In the Great Pacific Garbage Patch for example, microplastic concentrations are higher in the summer and lower in winter. They saw similar seasonal variation in garbage patches in other gyres too, due to more vertical mixing when the temperatures are cooler. Ruf and Evans also did a time-lapse of all of the major rivers in the world and saw a large amount of microplastics coming from the Yangtze and Ganges.
Voyager 2 succeeded on all counts. It returned spectacular photos of the entire Jovian system, and time-lapse movies made from its images of Jupiter showed how the planet had changed since Voyager 1's visit.
Natural disasters like tornadoes, forest fires, tsunamis, floods, or volcano eruptions are impossible to prevent, but timely tracking of the least changes can help mitigate losses. For a regular user, it might be interesting to see how their city looked like a century before. EOSDA LandViewer can provide either insight with the Change detection tool of the same AOI for different dates. Users can also embed the results on websites or share them on social media.
Mining operations generate large amounts of wastes which are usually stored into large-scale storage facilities which pose major environmental concerns and must be properly monitored to manage the risk of catastrophic failures and also to control the generation of contaminated mine drainage. In this context, non-invasive monitoring techniques such as time-lapse electrical resistivity tomography (TL-ERT) are promising since they provide large-scale subsurface information that complements surface observations (walkover, aerial photogrammetry or remote sensing) and traditional monitoring tools, which often sample a tiny proportion of the mining waste storage facilities. The purposes of this review are as follows: (i) to understand the current state of research on TL-ERT for various applications; (ii) to create a reference library for future research on TL-ERT and geoelectrical monitoring mining waste; and (iii) to identify promising areas of development and future research needs on this issue according to our experience. This review describes the theoretical basis of geoelectrical monitoring and provides an overview of TL-ERT applications and developments over the last 30 years from a database of over 650 case studies, not limited to mining operations (e.g., landslide, permafrost). In particular, the review focuses on the applications of ERT for mining waste characterization and monitoring and a database of 150 case studies is used to identify promising applications for long-term autonomous geoelectrical monitoring of the geotechnical and geochemical stability of mining wastes. Potential challenges that could emerge from a broader adoption of TL-ERT monitoring for mining wastes are discussed. The review also considers recent advances in instrumentation, data acquisition, processing and interpretation for long-term monitoring and draws future research perspectives and promising avenues which could help improve the design and accuracy of future geoelectric monitoring programs in mining wastes.
The recent reviews from Loke et al. (2013), Binley et al. (2015) and Slater and Binley (2021) have highlighted the emergence of time-lapse electrical resistivity tomography (TL-ERT) as a promising technique for monitoring of various subsurface processes across multiple scales. This non-destructive imaging approach has been combined with surface observations and point sensors measurements for long-term monitoring of landslides (Whiteley et al. 2019), permafrost (Mollaret et al. 2019), infrastructure (Chambers et al. 2014) and many other fields (Falzone et al. 2019). Although several other geophysical methods such as self-potential (Jougnot et al. 2015; Soupios and Kokinou 2016), induced polarization (Abdulsamad et al. 2019; Saneiyan et al. 2019), active and passive seismic (Grandjean et al. 2009; Olivier et al. 2017) or ground-penetrating radar (Giertzuch et al. 2021; Steelman et al. 2017) have been applied in similar contexts, the focus of this review is on TL-ERT since this technique is cost-efficient, robust and readily deployable for large-scale monitoring. Furthermore, TL-ERT is one of the most well understood near surface geophysical techniques, and is particularly sensitive to moisture driven processes, which play a key role in mining waste stability.
In this regard, the present review summarizes the state of the art and the development of time-lapse ERT over the last 30 years. A database of TL-ERT studies since 1990 is used to identify and describe the different types of application, and review the recent developments that made TL-ERT a recognized and complementary tool for long-term remote monitoring. In the meantime, a database of studies using ERT for mining waste characterization and monitoring allows to identify promising avenues for long-term monitoring of TSFs and WRPs. The article reviews some lessons learned from three decades of TL-ERT development in other domains. Finally, suggestions are proposed to overcome the challenges that could arise from a more widespread application of TL-ERT for long-term mining waste monitoring. In particular, several research perspectives are suggested to improve the accuracy of future ERT monitoring programs and upscale stability assessment in mining waste storage facilities.
Monitoring period represents the duration of the time-lapse survey (i.e., time difference between the first and the last ERT snapshot). Monitoring periods found in the literature vary from a few hours for short surveys (Kuras et al. 2009), a few months for seasonal dynamics (Jodry et al. 2019; Mojica et al. 2013) to several years for long-term studies (Caterina et al. 2017; Palis et al. 2017) (e.g., more than 20 years for permafrost monitoring (Mollaret et al. 2019)).
Time-constrained inversions. More recent time-lapse inversion strategies impose a similarity between consecutive distributions of resistivity to mimic smooth evolution in time of the medium and discard non-realistic changes of resistivity (Hayley et al. 2011). By analogy with the model constraint presented in Eq. 6, the time constraint \(\Phi _\text t(\textbf m^t)\) can be added to the cost function \(\Phi (\textbf m^t)\) to penalize resistivity distributions \(\textbf m^t\) that differ from the previous one \(\textbf m^t-1\). The general expression of \(\Phi _\text t(\textbf m^t)\) is (Loke et al. 2014a; Singha et al. 2015): 2ff7e9595c
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