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2023-11-28 00:00:00 | Enquêter sur le risque de références compromises et d'actifs exposés à Internet explorez le rapport révélant les industries et les tailles d'entreprise avec les taux les plus élevés d'identification compromises et d'actifs exposés à Internet.En savoir plus Investigating the Risk of Compromised Credentials and Internet-Exposed Assets Explore the report revealing industries and company sizes with the highest rates of compromised credentials and internet-exposed assets. Read More (lien direct) |
IntroductionIn this report, Kovrr collected and analyzed data to better understand one of the most common initial access vectors (1) - the use of compromised credentials (Valid Accounts - T1078) (2) to access internet-exposed assets (External Remote Services - T113) (3). The toxic combination of these two initial access vectors can allow malicious actors to gain a foothold in company networks before moving on to the next stage of their attack, which can be data theft, ransomware, denial of service, or any other action. There are numerous examples of breaches perpetrated by many attack groups that have occurred using this combination, for example, breaches by Lapsus (4) and APT39 (5), among others. âThis report seeks to demonstrate which industries and company sizes have the highest percentage of compromised credentials and number of internet-exposed assets and face a higher risk of having their networks breached by the toxic combination of the initial access vectors mentioned above.âIt should be noted that having an asset exposed to the internet does not inherently pose a risk or indicate that a company has poor security. In our highly digitized world, companies are required to expose services to the internet so their services can be accessed by customers, vendors, and remote employees. These services include VPN servers, SaaS applications developed by the company, databases, and shared storage units. However, there are some common cases when having an asset exposed to the internet can be extremely risky, for example:âWhen a company unintentionally exposes an asset due to misconfiguration.When a malicious third party obtains compromised credentials of a legitimate third party and accesses an exposed asset.  âTo limit unnecessary internet exposure, companies should employ the following possible mitigations:âUse Multi-Factor Authentication (MFA) for any services or assets that require a connection so that compromised credentials on their own will not be enough to breach an exposed asset.Limit access to the asset to only specific accounts, domains, and/or IP ranges.Segment the internal company network and isolate critical areas so that even if a network is breached through access to an external asset, attackers will not be able to use that access to reach wider or more sensitive areas of the company network. âSummaryâThe following are the main findings from the collected data:âThe Services industry is by far the most exposed to attackers. Companies from that industry have the highest percentage of compromised credentials (74%). However, they have a relatively low amount of internet-exposed assets per company (34%). However, given that an average cyber loss in this industry has been shown to be about $45M, this is highly concerning (6). The Services industry (SIC Division I) is followed by Division E (Transportation, Communications, Electric, Gas, and Sanitary Services, with an average loss of around $58M), which is followed by Division D (Manufacturing, with an average loss of around $25M). The revenue range for companies with the highest number of compromised credentials is $1M-$10M, followed by $10M-$50M. A similar trend is also observed when evaluating company size by the number of employees. Indeed, companies with fewer employees have a higher share of compromised credentials. On average, the larger the company (both in terms of revenue and number of employees (7)), the greater the number of internet-exposed assets.There is a correlation between the industries and revenue ranges of companies targeted by ransomware and those with the highest share of compromised credentials.   âMethodologyâThe data for this research was collected as follows:âData regarding compromised credentials was first collected from Hudson Rock, a provider of various cybercrime data. Data was collected for the previous six months, beginning March 2023. This data | Ransomware Threat Studies Prediction Cloud | APT 39 APT 39 APT 17 | ★★★ |
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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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