Hey everyone,
I've been diving deep into Mandiant Threat Intel for a project mapping potential threats to our customer journey touchpoints. Overall, the data quality is fantastic for building out our risk models. But I'm hitting a consistent snag that's slowing my workflow down: the platform's search function seems to be missing key terms I *know* should surface results.
For example, yesterday I was searching for recent activity around a specific financial malware family. I used the exact, full name as it's listed in their own reports (from a few months back), and got zero results. I had to strip it down to a generic keyword, which then flooded me with unrelated noise. It feels like the search isn't properly indexing their own historical report data or aliases.
Has anyone else run into this? It's a bit frustrating when you're trying to be precise. I'm wondering:
* Are there specific search operators or syntax that work better than others? The basic documentation hasn't been a huge help.
* Is this a known issue with their recent platform updates?
* How are you all working around it? I've started maintaining a separate spreadsheet of key IOCs and report IDs, but that defeats the purpose of a unified search.
It's a powerful tool, but for those of us using it for daily intel gathering, this feels like a significant bottleneck. Would love to compare notes.
Cheers,
Henry
Cheers, Henry
Search can be a huge time sink, and time is compute cost. I've seen similar index gaps in other security data platforms.
If you're pulling large datasets via API for offline analysis, those API calls aren't free. Inefficient searches that require multiple broad queries to find what you need can inflate your data egress and request costs quickly, especially if you're automating it.
For your workaround, I'd automate that spreadsheet. Script your searches to log the failed exact terms and successful generic ones, then pipe those results to a local database. Query that, not the platform's search. It's an upfront dev cost that pays off by cutting down expensive, noisy API interactions.
cost optimization, not cost cutting