Dynatrace

Technologies are disclosed herein that are directed to the improvement of vulnerability assessment process by avoiding false positive vulnerabilities caused by vendor specific backports of vulnerability fixes that are not considered by conventional vulnerability assessment systems. To secure their software products, vendors identify components that are affected by vulnerabilities used by their products and apply vulnerability fixes introduced by later component versions to those component versions used in their products. This created "gaps" in vulnerable component version ranges provided by public vulnerability intelligence data streams. Vulnerability assessment processes that solely rely on public vulnerability intelligence data incorrectly report vulnerabilities for component versions containing such backported vulnerability fixes. An integrated vulnerability intelligence database that combines public vulnerability intelligence data with vendor specific vulnerability backport data provides a more complete basis for vulnerability assessments that are not prone to fix backport caused false positives.

The disclosure relates to a computer-implemented method for extracting data from textual records. The technical problems solved by the disclosure are i) to generate an extraction pattern for extracting a selected data field from a reference record, ii) to improve the robustness of the extraction pattern by reducing its length, and iii) to extract the selected field from a set of records. The solution comprises determining whether the extraction pattern is disjoint to any segment of the preceding pattern; forming a new extraction pattern by inserting the data type for last data field in the preceding pattern at the beginning of the extraction pattern; and repeating the previous steps with the new extraction pattern until the new extraction pattern is disjoint to all segment comprising the preceding pattern. (Fig. 6)

A computer-implemented method for storing and querying application performance monitoring (APM) data in a database, includes receiving data records of APM data, each data record associated to a key; storing the data records in storage containers in the database, each record stored in one storage container and each storage container identified by a unique storage identifier; assigning a unique index value to each unique key; defining a distribution function mapping the keys to the index values; generating a secondary function to approximate the distribution function; defining a mapping function to map the index values to lists of storage identifiers; and in response to a request to retrieve data records for a specified key or keys, querying the database to identify a list of storage identifiers based on the secondary function and the mapping function and retrieving the data records for the specified key or keys.

A computer-implemented method is presented for extracting data from textual records. The objective of the disclosure is to identify the most appropriate pattern in a set of patterns for extracting data from data records and by applying the most appropriate pattern to a plurality of data records, to robustly extract data from textual records.

A unified storage format is presented for received observation data records of various formats, including individual observations or histograms and pre-sampled records describing multiple observations. The proposed storage format also supports various data reduction technologies, including coarsening of time and observation value resolutions, where the proposed data reduction technologies retain data describing the quantity of observations. In addition, sampling-based data reduction approaches are described, which at least retain the statistical expectancy value for the number of observations. Further, a definition and storage format for histogram buckets is provided with guaranteed relative error behavior over the whole value range of observation data, that only requires the definition of a number of significant bits for the recording and interpretation of histogram data. The proposed histogram storage scheme is applicable to integer and floating-point observation data. (Fig. 1)

The present disclosure relates to the detection of cross-site scripting vulnerabilities in a web application. The objective of the disclosure is to find a computer-implemented method for detecting cross-site scripting vulnerabilities in a web application. The detection of XSS vulnerabilities shall be performed automatically and the number of false positives shall be reduced compared to the prior art.

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Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

A technology is disclosed for automated risk analysis for the deployment of software component updates in complex microservice architectures. Dependencies and versions of deployment situations in test setup environments and in a target environment are analyzed and compared to identify a version delta between tested and production deployments. Further, test results for test deployments are used to identify and remove unsuccessful test setups. Successful test setups are ranked according to extend of their version delta against the target environment and one of the successful test setups is selected according to a deployment strategy. After a test setup is selected, a deployment plan considering service versions and dependencies is generated that guarantees a tested and functional state of the target environment after each deployment step.