Getting started
Knowledge hub
- Overview
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- 34 M Wordlist Subdomain Brute Force
- Asn Based Network Scan
- Asset Discovery and Vulnerability Scanning
- Custom Subdomain Brute Force Wordlist From Ip Ranges
- Enumerate Cloud Resources
- Full Subdomain Enumeration
- Get Ips and Cnames
- Getdns
- Github Recon and Scanner
- Hostnames S3 Bucket Finder
- Simple Content Discovery
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- amass
- anew
- apkurlgrep
- assetfinder
- cent
- cero
- cewl
- cloudenum
- crosslinked
- dnsdumpster-dns-lookup
- dnsdumpster-host-search
- dnstwist
- dnsvalidator
- dsieve
- dumpsterdiver
- eyeballer
- ffuf
- find-gh-poc
- findomain
- gau
- generate-yaml-report
- get-asn-prefixes
- get-trickest-output
- gf
- github-subdomains
- goaltdns
- gospider
- gotator
- hakcheckurl
- httprobe
- httpx
- infoga
- ipinfo
- jldc-subdomains
- katana
- mapcidr
- mass-linkfinder
- masscan
- massdns
- meg
- mksub
- naabu
- notify
- nrich
- nuclei
- oneforall
- puredns
- pymeta
- s3scanner
- securitytrails-subdomains
- spiderfoot
- sslyze
- subdomainizer
- subfinder
- tlsx
- uncover
- unfurl
- uro
- vita
- webanalyze-1
- webanalyze
- x8
Tutorials
- Creating a Workflow
- Downloading a Result
- Executing a Workflow
- How Do Machines Work
- Keeping Track of a Run
- Navigating in Workflow Editor
- Overview
- Saving a Workflow and History
- Scheduling a Workflow
- Using Workflows From Library
Concepts
Machines
Machines represent cloud resources required for executing workflows.
Trickest provides a fixed number of virtual machines to each user, available to be used in workflow executions. Number of machines is predefined by user’s subscription package.
Machines Availability
To take an insight into your machines availability check Fleet page.Machine types
Trickest provides several types of machines. Different machine types have different allocations of CPU and memory, so are suited for workloads with different computational requirements.
Following 3 types of machine are provided:
Machine | CPU | RAM |
---|---|---|
Machine | CPU | RAM |
Small | 1 | 1GB |
Medium | 3 | 15GB |
Large | 7 | 24GB |
Machine states
Every machine goes through several stages in its computation lifecycle:
Status | Description |
---|---|
Down | Machine is not dedicated to any workflow execution. It is on the rest and it is available to be dedicated to some run. |
Up | Machine is activated (from Down to Up activation) and it is ready to perform some computation. It is used in some run, or available to be dedicated to some run - learn more about availability of Up machine. |
Running | Machine is performing some computation. It isn't available, it is used in some run. |
Error | Some error occurred in machine's work, and it is necessary to contact support@trickest.com. It isn't able to do any computation at the moment. |
Machine utilization
Every Running machine tends to go to Down state when it is finish with dedicated work, and the scale down is done automatically by the platform (a few minutes needed for this process).
For both time and cost optimisation, when Running machine is just finished with dedicated work, it will stay Up, instead of down scaled, until the end of the last started hour. This enables using already ready Up machine for next workflow execution.
This produces two types of machine startup within a run:
- Down -> Up -> Running** -** cold start where machine needs some time to be activated, from Down to Up state, then becomes Running by starting its work.
- Up -> Running** -** warm start where machine is already activated, it is already Up, and can starts with work immediately.
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