Hey everyone! I've been trying to get more hands-on with threat intel at work, and my manager suggested I explore the Mandiant Threat Intelligence APIs. The goal was to build a super simple internal tool so our team can quickly search for indicators or threat reports without everyone needing to be an API expert.
I found their Python SDK on GitHub and dove in. Honestly, I got a bit stuck at first. The SDK is powerful, but the examples are more about pulling raw data feeds. I wanted a basic, one-script search tool. After a lot of trial and error (and StackOverflow!), I got something working. Can you guys check my approach and tell me if I'm on the right track?
My main hurdle was authentication and then structuring the search. I used the `mandiant-threat-intelligence` library and focused on the `IndicatorsAPI` and `MalwareAPI` clients. The script asks for a search term, then tries to find matching indicators (like file hashes or domains) and malware families. It prints out a brief summary.
One thing I'm unsure about: I'm handling the API response as a big dictionary and picking out fields like `mscore` and `last_updated`. Is there a better, more object-oriented way to do this using the SDK's own models? Also, I feel like my error handling is probably too basic for a real tool.
My next step is to maybe put this in a simple Flask app so the team can use it, but I wanted to nail the core logic first. Any advice from folks who've built similar things? Especially on structuring the code, pagination for large results, and maybe caching? I'm used to ETL pipelines, but building a little app like this is new to me!
-- rookie
rookie
Authentication is definitely the trickiest part when you're just getting started with these SDKs. Your approach of pulling out specific fields from the response dictionary is actually fine and very common, especially for a quick internal tool. The SDK's models should provide those fields as attributes if you wanted to explore a more object-oriented style, but it often adds complexity you might not need yet.
The one thing I'd double-check is error handling, particularly around rate limits or expired tokens, since that's what usually breaks a simple script in a team setting. Adding a try-except for the main API calls can save your colleagues from cryptic errors.
Could you share a bit about how you're presenting the results? I'm curious if you're formatting the `mscore` and `last_updated` info in a way that's immediately actionable for your team, or if you found some fields more useful than others.
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