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2024-10-14 21:26:20 |
Faits saillants hebdomadaires, 14 octobre 2024 Weekly OSINT Highlights, 14 October 2024 (lien direct) |
## Snapshot
Last week\'s OSINT reporting highlights a complex landscape of cyber threats with a focus on APT groups, sophisticated malware, and exploitation of vulnerabilities. Many attacks are espionage-focused, with China-aligned groups like CeranaKeeper, Iran\'s Hazel Sandstorm, and Russia\'s Midnight Blizzard (SVR) leveraging spearphishing and vulnerability exploitation for intelligence gathering. Ransomware also remains a dominant attack type, with threat actors leveraging double extortion tactics to maximize pressure on victims. A surge in reporting on malware distribution was also observed, including Lua-based malware in the education sector and Pronsis Loader delivering Lumma Stealer. Additionally, multiple reports detail widespread campaigns leveraging phishing, malvertising, and cryptomining, with key targets being government institutions, financial services, and critical infrastructure. Attackers employ diverse techniques such as DNS tunneling, USB-based malware, and exploit known vulnerabilities like EternalBlue (CVE-2017-0144) and FortiOS (CVE-2024-23113).
## Description
Last week\'s OSINT reporting highlights a complex landscape of cyber threats with a focus on APT groups, sophisticated malware, and exploitation of vulnerabilities. Many attacks are espionage-focused, with China-aligned groups like CeranaKeeper, Iran\'s Hazel Sandstorm, and Russia\'s Midnight Blizzard (SVR) leveraging spearphishing and vulnerability exploitation for intelligence gathering. Ransomware also remains a dominant attack type, with threat actors leveraging double extortion tactics to maximize pressure on victims. A surge in reporting on malware distribution was also observed, including Lua-based malware in the education sector and Pronsis Loader delivering Lumma Stealer. Additionally, multiple reports detail widespread campaigns leveraging phishing, malvertising, and cryptomining, with key targets being government institutions, financial services, and critical infrastructure. Attackers employ diverse techniques such as DNS tunneling, USB-based malware, and exploit known vulnerabilities like EternalBlue (CVE-2017-0144) and FortiOS (CVE-2024-23113).
1. [CeranaKeeper Targets Thai Government](https://sip.security.microsoft.com/intel-explorer/articles/b3aa72ef): ESET uncovered a new China-aligned APT, CeranaKeeper, targeting government institutions in Thailand, using unique tools for data exfiltration via cloud services. The group adapts its malware for stealth and has been mistakenly linked to Mustang Panda due to some shared methods.
2. [Largest DDoS Attack Mitigated](https://sip.security.microsoft.com/intel-explorer/articles/74f06d55): Cloudflare mitigated the largest publicly disclosed DDoS attack, peaking at 3.8 Tbps, which targeted financial services, internet, and telecom organizations globally. Akamai also identified a critical vulnerability in CUPS servers, potentially creating a new vector for DDoS amplification.
3. [Cuckoo Spear\'s Sophisticated Tools](https://sip.security.microsoft.com/intel-explorer/articles/d47fc595): Cybereason exposed the Cuckoo Spear campaign by APT10, using NOOPLDR and NOOPDOOR to conduct espionage against Japanese industries and governments. These advanced tools employ anti-detection techniques and facilitate network pivoting for exfiltration.
4. [Mamba 2FA Phishing Campaign](https://sip.security.microsoft.com/intel-explorer/articles/bfcb80ed): Sekoia identified a phishing campaign using Mamba 2FA, a PhaaS platform, to steal credentials and session cookies from Microsoft services. Attackers exploited MFA weaknesses and used Telegram bots for data exfiltration.
5. [Golden Jackal\'s Air-Gapped System Attacks](https://sip.security.microsoft.com/intel-explorer/articles/f0234a25): ESET researchers discovered Golden Jackal targeting European government organizations with tools designed to breach air-gapped systems. The group uses USB-based malware for espionage and data exfiltration.
6. [Awaken Likho Targets Russian Agencies](https://sip.security.microsoft.com/in |
Ransomware
Malware
Tool
Vulnerability
Threat
Patching
Industrial
Medical
Cloud
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APT 29
APT 10
GoldenJackal
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★★
|
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2022-10-18 08:41:18 |
The benefits of taking an intent-based approach to detecting Business Email Compromise (lien direct) |
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. |
Threat
Medical
Cloud
|
Yahoo
Uber
APT 38
APT 37
APT 29
APT 19
APT 15
APT 10
|
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2022-08-06 10:46:21 |
CISO workshop slides (lien direct) |
A glossy, nicely-constructed and detailed PowerPoint slide deck by Microsoft Security caught my beady this morning. The title 'CISO Workshop: Security Program and Strategy' with 'Your Name Here' suggests it might be a template for use in a workshop/course bringing CISOs up to speed on the governance, strategic and architectural aspects of information security, but in fact given the amount of technical detail, it appears to be aimed at informing IT/technology managers about IT or cybersecurity, specifically. Maybe it is intended for newly-appointed CISOs or more junior managers who aspire to be CISOs, helping them clamber up the pyramid (slide 87 of 142): |
Malware
Vulnerability
Threat
Patching
Guideline
Medical
Cloud
|
Uber
APT 38
APT 37
APT 28
APT 19
APT 15
APT 10
APT 34
Guam
|
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