This is the RSS 2.0 feed from www.secnews.physaphae.fr. IT's a simple agragated flow of multiple articles soruces. Liste of sources, can be found on www.secnews.physaphae.fr. 2024-05-20T19:01:20+00:00 www.secnews.physaphae.fr Mandiant - Blog Sécu de Mandiant   APT42, an Iranian state-sponsored cyber espionage actor, is using enhanced social engineering schemes to gain access to victim networks, including cloud environments. The actor is targeting Western and Middle Eastern NGOs, media organizations, academia, legal services and activists. Mandiant assesses APT42 operates on behalf of the Islamic Revolutionary Guard Corps Intelligence Organization (IRGC-IO). APT42 was observed posing as journalists and event organizers to build trust with their victims through ongoing correspondence, and to deliver invitations to conferences or legitimate documents. These social engineering schemes enabled APT42 to harvest credentials and use them to gain initial access to cloud environments. Subsequently, the threat actor covertly exfiltrated data of strategic interest to Iran, while relying on built-in features and open-source tools to avoid detection. In addition to cloud operations, we also outline recent malware-based APT42 operations using two custom backdoors: NICECURL and TAMECAT. These backdoors are delivered via spear phishing, providing the attackers with initial access that might be used as a command execution interface or as a jumping point to deploy additional malware. APT42 targeting and missions are consistent with its assessed affiliation with the IRGC-IO, which is a part of the Iranian intelligence apparatus that is responsible for monitoring and preventing foreign threats to the Islamic Republic and domestic unrest. APT42 activities overlap with the publicly reported actors CALANQUE (Google Threat Analysis Group), Charming Kitten (ClearSky and CERTFA), Mint Sandstorm/Phosphorus (Microsoft), TA453 (Proofpoint), Yellow Garuda (PwC), and ITG18 (]]> 2024-05-01T14:00:00+00:00 https://cloud.google.com/blog/topics/threat-intelligence/untangling-iran-apt42-operations/ www.secnews.physaphae.fr/article.php?IdArticle=8500390 False Malware,Tool,Threat,Cloud APT 35,APT 42,Yahoo 2.0000000000000000 CISCO Talos - Cisco Research blog By Abhishek Singh.BEC is a multi-stage attack. Adversaries first identify targets, then they establish rapport with the victim before exploiting them for whatever their end goal is. In the case of BEC, a threat actor can impersonate any employee in the organization to trick targets.  A policy that checks for authorized email addresses of the sender can prevent BEC attacks. However, scaling the approach for every employee in a large organization is a challenge.  Building an executive profile based on email analysis using a machine learning model and scanning emails against that profile will detect BEC. Data collection for building and training machine learning algorithms can take time, though, opening a window of opportunity for threat actors to exploit.  Detection of exploitation techniques such as lookalike domains and any differences in the email addresses in the "From" and "Reply-to" fields can also detect BEC messages. However, the final verdict cannot account for the threat actor's intent.  The intent-based approach detects BEC and then classifies it into the type of scam. It catches BEC messages, irrespective of whether a threat actor is impersonating a C-level executive or any employee in an organization. Classification based on the type of scam can help identify which segment of an organization was targeted and which employees were being impersonated by the threat actor. The additional information will further assist in better designing preventive features to stop BEC. Business email compromise (BEC) is one of the most financially damaging online crimes. As per the internet crime 221 report, the total loss in 2021 due to BEC is around 2.4 billion dollars. Since 2013, BEC has resulted in a 43 billion dollars loss. The report defines BEC as a scam targeting businesses (not individuals) working with foreign suppliers and companies regularly performing wire transfer payments. Fraudsters carry out these sophisticated scams to conduct the unauthorized transfer of funds. This introduces the challenge of how to detect and block these campaigns as they continue to compromise organizations successfully. There are a variety of approaches to identifying BEC email messages, such as using policy to allow emails from authorized email addresses, detecting exploitation techniques used by threat actors, building profiles by analysis of emails, and validating against the profile to detect BEC. These approaches have a variety of limitations or shortcomings. Cisco Talos is taking a different approach and using an intent-based model to identify and block BEC messages. Before we get too deep into the intent-based model, take a deeper look at the commonly used approaches to block BEC from the simplistic through machine learning (ML) approaches. Policy-based detection The first place to start is with policy-based detection as it is one of the most common and simplistic approaches to blocking BEC campaigns. Let's start by looking at an example of a BEC email. ]]> 2022-10-18T08:41:18+00:00 http://blog.talosintelligence.com/2022/10/the-benefits-of-taking-intent-based.html www.secnews.physaphae.fr/article.php?IdArticle=7540074 False Threat,Medical,Cloud APT 38,APT 19,APT 29,APT 10,APT 37,Uber,APT 15,Yahoo None