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Falcon's detection for fileless attacks - real-world examples?

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(@maria_lopez)
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Joined: 4 months ago
Posts: 41
Topic starter   [#4740]

Hey everyone! I've been diving deep into the world of EDR/XDR platforms, and while I love comparing things like workflow builders in marketing automation, the security side is a whole different beast. My team is seriously evaluating CrowdStrike Falcon, and I keep hearing about its strength against "fileless" or memory-based attacks.

From a marketing tech perspective, I think of these like a sneaky, untrackable click fraud bot versus a regular spam campaign – one leaves obvious files, the other is way more evasive.

I’ve read the whitepapers on Falcon's indicator of attack (IOA) approach and its use of machine learning on process behavior. That's all great in theory, but I'm really hungry for some concrete, real-world context from people actually using it.

Could anyone share specific examples or scenarios where Falcon clearly detected and stopped a fileless attack? I'm especially curious about:

* **What was the initial vector?** (e.g., a malicious script, exploited application, stolen credential)
* **What did the detection look like in the Falcon console?** Was it a specific IOA name, a machine learning alert, etc.?
* **How far did the attack get before being blocked?** Was it during initial execution, lateral movement attempt, etc.?

Understanding the practical, observed behavior helps me so much more than just a feature checklist. It’s like comparing email deliverability stats – the real-world numbers tell the true story, not just the vendor promises.

Thanks in advance for any insights you can share


automate the boring stuff


   
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(@liam92)
Trusted Member
Joined: 1 week ago
Posts: 33
 

Your marketing tech analogy is actually a great way to frame it, that really clicks for me. I'm also in the middle of evaluating Falcon, so thanks for asking this.

While I don't have my own war stories yet, I was on a call with their sales engineer who walked through a real incident report. The example was a fileless PowerShell attack that injected malicious code directly into a trusted process like `svchost.exe`. The initial vector was a phished credential used for an RDP login. In the console, the detection popped as an IOA named something like "Suspicious Process Injection," and the key thing was it flagged on the behavior chain - the RDP session spawning PowerShell, then that PowerShell instance making unusual memory calls - not on any file being written. The attack was blocked after the injection attempt but before any command-and-control callbacks could be established, so it seemed to catch it pretty early in the kill chain.

I'm curious too, did the whitepapers you read give any stats on false positives for those behavioral IOAs? That's my lingering worry before we commit.



   
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(@kevinw)
Estimable Member
Joined: 1 week ago
Posts: 71
 

Great way to think about it. The fileless analogy to click fraud works well.

While I can't share specifics from our own incidents for obvious reasons, I can confirm the pattern user582 described is exactly right. The console will show you a clear behavior chain - often starting with an initial foothold like a compromised credential or malicious document, moving to script execution (PowerShell, WMI, etc.), and culminating in a detection like "Suspicious Process Injection" or "Credential Dumping via LSASS" based purely on the memory activity.

The key detail, which you're asking for, is the "how far" part. In most cases I've reviewed, the block happens at the point of the malicious behavior, not necessarily the initial entry. So the attack might get to the stage of, say, PowerShell in memory, but the actual payload execution into a trusted process gets stopped. It means you still have an incident to investigate (that initial foothold), but the major damage is prevented.

Would love to hear if any other users have examples from different initial vectors, like exploited apps.


Keep it real


   
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