Gordon quickly provides threat & risk information about observables
Gordon is a great website for security analysis and threat intelligence practitioners courtesy of Marc-Henry Geay of France.
It’s a fine offering that quickly provides threat and risk information about observables such as IPv4 addresses, URLs, Domains/FQDNs, MD5, SHA-1, SHA-256 hashes, or email addresses.
All aspirations and architecture for Gordon are available in Marc-Henry’s Medium post, as well as his About content.
You really need only know the following in any detail:
- Gordon submits your observables (IOCs) to multiple sources (30+ engines) to ensure good coverage.
- Observables are only searched in open security databases’ existing records (passive).
- Results can be viewed and shared for up to 3 days, thereafter they are deleted, Marc-Henry has EU privacy regulations to contend with.
- Results are available as Summary Reports with risk-based coloration for some engines, and can be exported as PDF, CSV, and XLSX.
I gave Gordon a quick test using IPv4 IOCs from the Cisco Talos Threat Advisory: SolarWinds supply chain attack. Gordon limits you to 15 observables at most, and note that it favors non-Microsoft browsers, so I experimented via Firefox. Using ten IP IOCs, separated one per line, I received swift results as seen in Figure 1.
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Figure 1: Gordon IPv4 SUNBURST results
As noted, Figure 1: shows IPvs SUNBURST IOC results that are precise and color coded by risk.
Using ten SHA-256 hashes from the Talos report for my next query I opted to export the results as an Excel document, then sorted by malicious results only.
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Figure 2: Gordon SHA-256 query results
Again, the SUNBURST SHA-256 IOC results are robust and detailed. I’ve certainly added Gordon to my favorites list and suggest you consider doing the same.
Cheers…until next time.
(c) SANS Internet Storm Center. https://isc.sans.edu Creative Commons Attribution-Noncommercial 3.0 United States License.=============== Rob VandenBrink
(c) SANS Internet Storm Center. https://isc.sans.edu Creative Commons Attribution-Noncommercial 3.0 United States License.