Data Search

Enter some data into the searchbox and we'll try our best to classify the data into a meaningful category.

Input Provide any data set for examination.

Operation We'll process the data, identifying distinct categories and patterns within.

Result You'll receive a detailed classification of the data's content, complemented by an analysis of its entropy and inherent structure.

API Overview | 1,000 free daily requests

Make a HTTP POST request (content-type application/json) to https://srcport.com/api/free/[module]

POST

Add a Authorization: Bearer [token] header to the request including your personal API token viewable in your account profile.

Header

The HTTP POST request payload should contain a JSON formatted prompt and options field. The prompt field is typically the target of the scan, e.g., 'example.com'. The buttons below can be used to view the available options.

The prompt is the main searchterm provided to the tool. This needs to be in a format required by the tool otherwise an error may be returned. For example some tools may require URLs while others may require IP addresses.

Some options may be required while others are optional. If there are no options, an empty object should be provided.

The default API key is provided as an example only. This will not work in your own applications. Register for a free account to get an API key.

Example CURL Request

Data Classifier

The Classifier tool categorizes inputs based on their data types, organizing them into relevant data categories or types. By examining the characteristics or properties of the input data, it classifies them into appropriate categories such as text, numbers, dates, images, or other specific data types. This classification aids in data organization, structuring, and analysis, enabling efficient handling and processing of diverse data sets.

Match Type - Select the type of match to perform.

Fuzzy Match Exact Match

Entropy Block Size - Select the length (in characters) for the blocks size to use while analysing entropy.

8 Chars 16 Chars 32 Chars 64 Chars 128 Chars 256 Chars

Low Risk Data Classifier

Entropy Analysis

Entropy is a useful analysis technique in cyber security as it can be used to identify encrypted or compressed data, detect malware, and identify data types. It is a measure of the uncertainty or information content in a set of data. It quantifies the average amount of information needed to describe the data. The entropy value ranges from 0 to 7. When the entropy is 0, it means the data is perfectly predictable or has no uncertainty, as all the values in the dataset are the same. Conversely, when the entropy is 7, it indicates maximum uncertainty or randomness, where all possible values are equally likely to occur. In general, higher entropy values signify greater complexity or information diversity in the dataset.

Entropy

Shannon entropy, named after mathematician Claude Shannon, is a measure of the uncertainty or information content in a set of data. It quantifies the average amount of information needed to describe the data. The entropy value ranges from 0 to 7. When the entropy is 0, it means the data is perfectly predictable or has no uncertainty, as all the values in the dataset are the same. Conversely, when the entropy is 7, it indicates maximum uncertainty or randomness, where all possible values are equally likely to occur. In general, higher entropy values signify greater complexity or information diversity in the dataset.

Block Size

The block size is the number of characters used to calculate the entropy of the input data. For example, if the block size is 8, the input data is divided into blocks of 8 characters each, and the entropy is calculated for each block.