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2023-10-02 17:05:46 | L'industrie cryptographique a perdu 685 millions de dollars au troisième trimestre 2023, 30% par le groupe Lazare Crypto Industry Lost $685 Million in Q3 2023, 30% by Lazarus Group (lien direct) |
> Par waqas
Rapport des pertes de crypto immunufi: T1 2023 voit les plus hautes pertes de l'année.
Ceci est un article de HackRead.com Lire le post original: L'industrie cryptographique a perdu 685 millions de dollars au troisième trimestre 2023, 30% par le groupe Lazare
>By Waqas Immunefi Crypto Losses Report: Q3 2023 Sees Highest Losses of the Year. This is a post from HackRead.com Read the original post: Crypto Industry Lost $685 Million in Q3 2023, 30% by Lazarus Group |
Studies | APT 38 | ★★★★ |
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2019-07-25 13:00:00 | Can you trust threat intelligence from threat sharing communities? | AT&T ThreatTraq (lien direct) | Every week the AT&T Chief Security Office produces a series called ThreatTraq with helpful information and news commentary for InfoSec practitioners and researchers. I really enjoy them; you can subscribe to the Youtube channel to stay updated. This is a transcript of a recent feature on ThreatTraq. The video features Jaime Blasco, VP and Chief Scientist, AlienVault, Stan Nurilov, Lead Member of Technical Staff, AT&T, and Joe Harten, Director Technical Security. Stan: Jaime. I think you have a very interesting topic today about threat intelligence. Jaime: Yes, we want to talk about how threat intelligence is critical for threat detection and incident response, but then when this threat intelligence and the threat actors try to match those indicators and that information that is being shared, it can actually be bad for companies. So we are going to share some of the experiences we have had with managing the Open Threat Exchange (OTX) - one of the biggest threat sharing communities out there. Stan: Jaime mentioned that they have so many threat indicators and so much threat intelligence as part of OTX, the platform. Jaime: We know attackers monitor these platforms and are adjusting tactics and techniques and probably the infrastructure based on public reaction to cyber security companies sharing their activities in blog posts and other reporting. An example is in September 2017, we saw APT28, and it became harder to track because we were using some of the infrastructure and some of the techniques that were publicly known. And another cyber security company published content about that and then APT28 became much more difficult to track. The other example is APT1. If you remember the APT1 report in 2013 that Mandiant published, that made the group basically disappear from the face of earth, right? We didn't see them for a while and then they changed the infrastructure and they changed a lot of the tools that they were using, and then they came back in 2014. So we can see that that threat actor disappeared for a while, changed and rebuilt, and then they came back. We also know that attackers can try to publish false information in this platform, so that's why it's important that not only those platforms are automated, but also there are human analysts that can verify that information. Joe: It seems like you have to have a process of validating the intelligence, right? I think part of it is you don't want to take this intelligence at face value without having some expertise of your own that asks, is this valid? Is this a false positive? Is this planted by the adversary in order to throw off the scent? I think it's one of those things where you can't automatically trust - threat intelligence. You have to do some of your own diligence to validate the intelligence, make sure it makes sense, make sure it's still fresh, it's still good. This is something we're working on internally - creating those other layers to validate and create better value of our threat intelligence. Jaime: The other issue I wanted to bring to the table is what we call false flag operations - that's when an adversary or a threat actor studies another threat actor and tries to emulate their behavior. So when companies try to do at | Malware Threat Studies Guideline | APT 38 APT 28 APT 1 |
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