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Threat Brief: Maze Ransomware
Unit 42 issued a threat brief on Maze ransomware, noting an uptick across industries and exploitation of Pulse VPN and IE flaws for initial access.
Palo Alto Networks detected an uptick in Maze ransomware samples across finance, healthcare, government, and other sectors. Maze, a variant of ChaCha ransomware first seen in May 2019, is distributed via weaponized Word/Excel attachments and the Spelevo exploit kit leveraging CVE-2018-15982 and CVE-2018-4878, and has used CVE-2019-11510 (Pulse VPN) and CVE-2018-8174 (Internet Explorer). Operators establish a foothold, escalate privileges, move laterally, and exfiltrate files before encryption for extortion leverage.
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Threat Brief: CVE-2022-41040 and CVE-2022-41082: Microsoft Exchange Server (ProxyNotShell)
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Cybersecurity jobs available right now: September 8, 2026
Help Net Security's September 8 job roundup lists open cybersecurity roles at AudioCodes, Garmin, Scotiabank, GDIT, Subway and others across seven countries.
The listing includes a CISO role at AudioCodes in Israel, a Combat Systems Cyber Engineer at Johns Hopkins Applied Physics Laboratory, cloud security engineering at Garmin, and an IAM Architect at Scotiabank. Other openings span penetration testing for NATO exercises at Spektrum in Belgium, SOC analyst at Orro Group in Australia, threat hunting at GDIT, and security operations at Subway in the USA. Roles range from CISO and architect to SOC analyst and penetration tester.
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Harnessing LLMs for Automating BOLA Detection
Unit 42's BOLABuster methodology uses LLMs to automate detection of broken object-level authorization vulnerabilities, uncovering flaws in Grafana, Harbor, and Easy!Appointments.
Palo Alto Unit 42 details BOLABuster, a methodology combining large language models with heuristics to automate detection of broken object-level authorization (BOLA) flaws, which traditional fuzzing and static analysis struggle to find. The approach uses LLM reasoning to understand application logic, map endpoint dependency relationships, and generate and interpret test cases. It found CVE-2024-1313 in Grafana, CVE-2024-22278 in Harbor, and 15 CVEs in Easy!Appointments. The team is continuing to hunt for BOLAs in open-source and internal projects.
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ApateWeb: An Evasive Large-Scale Scareware and PUP Delivery Campaign
Unit 42 uncovers ApateWeb, a campaign using over 130,000 domains and multilayered redirects to deliver scareware, adware and PUPs to millions of users.
Unit 42 discovered ApateWeb, a large-scale campaign using a network of more than 130,000 domains to deliver scareware, potentially unwanted programs, adware including a rogue browser and browser extensions, and scam pages. The campaign uses a three-layer structure with deceptive emails as the entry point, centralized victim tracking via UUIDs, intermediate adware or anti-bot redirections, and evasion tactics such as cloaking, bot detection error pages, and wildcard DNS abuse. Activity spiked since August 2022, with several hundred attacker-controlled sites remaining in Tranco's top 1 million rankings and millions of monthly hits; Unit 42 blocked an estimated 3.5 million sessions across 74,711 devices in November 2023.
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Almost Half of Malware Samples Communicate Direct to IP
Unit 42 analysis of 4 million malware reports finds 45% of C2-active samples connect directly to hard-coded IPs, bypassing DNS defenses.
Palo Alto Unit 42 analyzed over 4 million Advanced WildFire dynamic analysis reports and found that 45.32% of malware samples with C2 activity made at least one direct-to-IP connection, accounting for 23.17% of all C2 connection attempts. The firm proposes zero trust IP (ZT-IP), an enforcement approach that verifies whether outbound destinations were ever sanctioned by a DNS response. ZT-IP analysis surfaced Phorpiex ransomware droppers fetching payloads directly from C2 IPs, a persistent data exfiltration campaign using an obfuscated \GET protocol, and Mozi P2P botnet payloads delivered to IoT devices without DNS. Only 1% of benign samples connected directly to untrusted IP addresses.
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