Dynatrace

A computer-implemented method is provided for detecting cloned websites. The method includes: instrumenting a webpage with a detection agent, a token and a network address of an interested party; upon loading of the webpage, determining whether a current domain hosting the webpage matches an expected domain for the webpage (or a listing of expected domains for the webpage), where the expected domain is known to the detection agent; and sending an alert message across a network to the interested party, where the alert message includes the token and is sent in response to a mismatch between the current domain and the expected domain. The detection agent is computer-executable instructions (e.g., a script) that execute in response to loading of the webpage.

Systems and methods for monitoring database queries in a distributed computing environment are provided. An agent instrumented in an application executing a computer transaction receives a database statement and modifies it by adding metadata. The agent sends the modified database statement to a database system and sends monitoring data, including the metadata, to a remotely located monitor server. In response to execution of the database statement, the database system generates diagnostic data. The monitor server retrieves the diagnostic data from the database system and correlates the retrieved diagnostic data with the monitoring data using the metadata. This allows for automated, end-to-end performance correlation extending from the application layer down to the database layer without interfering with database statement behavior. (Fig. 1)

A computer-implemented method is presented for implementing cyber deception in a container orchestration system. As a starting point, a deception manager is installed on a cluster of a container orchestration system. The method includes: receiving a deception policy, where the deception policy identifies at least one trap, specifies a match rule for HTTP requests, specifies a response rule for responding to matched HTTP requests, specifies criteria for where to deploy traps, and specifies criteria for how to deploy the traps; and creating a set of traffic routing rules for a service mesh in the cluster, where the set of traffic routing rules implements the traps and is created according to the criteria for how to deploy the traps as defined in the deception policy.

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 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)

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.

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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