Known Vulnerabilities for products from Naigos

Listed below are 2 of the newest known vulnerabilities associated with the vendor "Naigos".

These CVEs are retrieved based on exact matches on listed vendor information (CPE data) as well as a keyword search to ensure the newest vulnerabilities with no officially listed vendor information are still displayed.

Data on known vulnerable products is also displayed based on information from known CPEs, each product links to its respective vulnerability page.

Known Vulnerabilities

CVE Shortened Description Severity Publish Date Last Modified
CVE-2021-35479 Nagios Log Server before 2.1.9 contains Stored XSS in the custom column view for the alert history and audit log function thr... 5.4 - MEDIUM 2021-07-30 2021-08-06
CVE-2021-35478 Nagios Log Server before 2.1.9 contains Reflected XSS in the dropdown box for the alert history and audit log function. All p... 5.4 - MEDIUM 2021-07-30 2021-08-06

Popular searches for "Naigos"

Naigos

www.youtube.com/channel/UC9rqQmUoCV3OjpDPBCrCTiQ

Naigos Bienvenido a mi EPICO y Estupido mundo soy naigos

www.youtube.com/user/TheWatchplay www.youtube.com/c/TheWatchplay Twitter Playlist Google URL Shortener Humour Freescale DragonBall Subscription business model YouTube Web browser Video Anime Apple Inc. Nintendo Switch Facebook Share (P2P) Minecraft Information Camera NaN Aspect ratio (image) Television

NAIGO: An Improved Method to Align PPI Networks Based on Gene Ontology and Graphlets

doi.org/10.3389/fbioe.2020.00547

X TNAIGO: An Improved Method to Align PPI Networks Based on Gene Ontology and Graphlets With the development of high throughput technologies, there are more and more proteinprotein interaction PPI networks available, which provide a need for efficient computational tools for network alignment. Network alignment is widely used to predict functions of certain proteins, identify conserved network modules, and study the evolutionary relationship across species or biological entities. However, network alignment is an NP-complete problem, and previous algorithms are usually slow or less accurate in aligning big networks like human vs. yeast. In this study, we proposed a fast yet accurate algorithm called Network Alignment by Integrating Biological Process NAIGO . Specifically, we first divided the networks into subnets taking the advantage of known prior knowledge, such as gene ontology. For each subnet pair, we then developed a novel method to align them by considering both protein orthologous information and their local structural information. After that, we expanded the

www.frontiersin.org/articles/10.3389/fbioe.2020.00547/full Sequence alignment Protein Pixel density Subnetwork Computer network Gene ontology Algorithm Saccharomyces cerevisiae Sequence homology Similarity measure Human Homology (biology) Protein–protein interaction Function (mathematics) Vertex (graph theory) Conserved sequence Greedy algorithm Graph (discrete mathematics) Matrix (mathematics) Yeast