β-Glucosidase (EC 3.2.1.21) is a prominent member of the GH1 family of glycoside hydrolases. The properties of this β-glucosidase appear to include resistance to temperature, urea, and iodoacetamide, and it is activated by 2-ME, similar to other members. β-Glucosidase from chayote (Sechium edule) was purified by ionic-interchange chromatography and molecular exclusion chromatography. Peptides detected by LC-ESI-MS/MS were compared with other β-glucosidases using the BLAST program. This enzyme is a 116 kDa protein composed of two sub-units of 58 kDa and shows homology with Cucumis sativus β-glucosidase (NCBI OPEN ACCESSMolecules 2015, 20 19373 reference sequence XP_004154617.1), in which seven peptides were found with relative masses ranging from 874.3643 to 1587.8297. The stability of β-glucosidase depends on an initial concentration of 0.2 mg/mL of protein at pH 5.0 which decreases by 33% in a period of 30 h, and then stabilizes and is active for the next 5 days (pH 4.0 gives similar results). One hundred μg/mL β-D-glucose inhibited β-glucosidase activity by more than 50%. The enzyme had a Km of 4.88 mM with p-NPG and a Kcat of 10,000 min −1. The optimal conditions for the enzyme require a pH of 4.0 and a temperature of 50 °C.

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This study presents a methodology to evaluate and prevent security vulnerabilities issues for web applications. The analysis process is based on the use of techniques and tools that allow to perform security assessments of white box and black box, to carry out the security validation of a web application in an agile and precise way. The objective of the methodology is to take advantage of the synergies of semi-automatic static and dynamic security analysis tools and manual checks. Each one of the phases contemplated in the methodology is supported by security analysis tools of different degrees of coverage, so that the results generated in one phase are used as feed for the following phases in order to get an optimized global security analysis result. The methodology can be used as part of other more general methodologies that do not cover how to use static and dynamic analysis tools in the implementation and testing phases of a Secure Software Development Life Cycle (SSDLC). A practical application of the methodology to analyze the security of a real web application demonstrates its effectiveness by obtaining a better optimized vulnerability detection result against the true and false positive metrics. Dynamic analysis with manual checking is used to audit the results, 24.6 per cent of security vulnerabilities reported by the static analysis has been checked and it allows to study which vulnerabilities can be directly exploited externally. This phase is very important because it permits that each reported vulnerability can be checked by a dynamic second tool to confirm whether a vulnerability is true or false positive and it allows to study which vulnerabilities can be directly exploited externally. Dynamic analysis finds six (6) additional critical vulnerabilities. Access control analysis finds other five (5) important vulnerabilities such as Insufficient Protected Passwords or Weak Password Policy and Excessive Authentication Attacks, two vulnerabilities that permit brute force attacks.

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