Microsoft tracked over 30 MacSync Stealer domains by focusing on behavioral patterns, revealing a campaign targeting passwords, keys, wallets and other data. Domain blocking is a losing game when the thing you’re blocking can register a new domain faster than you can add it to a list. That’s the exact problem Microsoft Defender Experts ran into while tracking MacSync Stealer, a macOS-focused information stealer that RST Cloud first flagged for swapping out its command-and-control infrastructure almost immediately after getting publicly outed. Microsoft detailed how its experts stopped chasing individual domains and started tracking the behaviors that stayed constant underneath them. Instead of tracking individual domains, Microsoft looked at recurring request patterns, HTTP headers and other behaviors. This allowed its researchers to link more than 30 domains to the same campaign and determine that the infrastructure was doing more than just sending commands to infected Macs. It was also being used to collect, stage and exfiltrate stolen data. “MacSync Stealer is a macOS-focused information stealer that relies on changing infrastructure to deliver payloads, communicate with compromised devices, and exfiltrate data. Earlier reporting by RST Cloud identified the threat through a limited set of domains and documented rapid command-and-control (C2) replacement after public disclosure.” reads the report published by Microsoft. “Microsoft Defender Experts expanded that view by correlating recurring endpoints and network behaviors across the activity. This behavior-led approach connected more than 30 domains and showed that the infrastructure supported more than C2 communication, extending into active collection, staging, and exfiltration.” The infection chain starts with a trick rather than an exploit. Victims get social-engineered through a technique known as ClickFix, tricked into pasting or running commands directly in macOS Terminal, and once that shell session fires, curl pulls down attacker-controlled payload content from a path formatted as /curl/[token]. Then, native macOS tools decode and unpack the payload, and an AppleScript-driven layer takes over, blending Unix commands like sh, cp, rm, and killall with osascript calls that make the whole chain look more like ordinary system scripting than malware. Once active, the stealer focuses on valuable data. The malicious code looks for macOS Keychain data, saved browser passwords and cookies, SSH keys, AWS credentials, Kubernetes configurations and files in common user folders. It also searches for Ledger and Trezor wallet data, showing that the malware targets users with valuable credentials and assets rather than simply collecting random browser history. What actually confirms exfiltration, rather than just suspicious traffic, is the upload mechanism itself. Collected data gets staged under temporary paths, compressed into an archive, split into chunks, and pushed out through HTTP PUT requests carrying parameters like upload_id, chunk_index, and total_chunks. “The staged archive was uploaded through rotating infrastructure using curl and HTTP PUT requests. Observed requests included –data-binary, API-key headers, macOS User-Agent string, upload_id values, chunk_index values, and total_chunks parameters.” states Microsoft. “These upload traits confirmed active data exfiltration and provided durable hunting pivots even when domains rotated. “ The researchers pointed out that the exfiltration method stays recognizable even when the destination keeps changing. RST Cloud’s follow-up work backs up how consistent this infrastructure actually is under the surface. Using the same recurring URI patterns, RST Cloud surfaced eleven additional candidate domains and found a static API-key value shared across four confirmed command-and-control domains, even while the build token attached to each deployment kept rotating. A shared static key sitting inside otherwise rotating infrastructure is exactly the kind of detail that makes automated evasion look less impressive up close. The attack wraps up with cleanup, deleting temporary archives, staging folders, and lock files after the upload completes. Microsoft notes this reduces what’s left sitting on disk, but it doesn’t erase the behavioral sequence itself. “After exfiltration, the malware removed temporary archives, staging folders, lock files, and other artifacts. Although this cleanup reduced on-disk evidence, the sequence of archive creation, chunked upload, and deletion can still provide a useful behavioral correlation for defenders.” concludes Microsoft. For anyone defending Mac fleets, the practical takeaway here isn’t a list of domains to block, since that list will be stale within days. It’s building detection around the recurring shape of the attack itself: shell sessions spawning curl with those specific flag patterns, osascript chaining rapidly into network activity, and archives appearing under /tmp/sync* right before outbound PUT traffic starts. Chase the pattern, not the address, because the address was never going to sit still long enough to matter. Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, malware)
Over 50,000 exposed Stripe API keys show how leaked secrets can enable fraud, data access and account abuse within hours. Ransomnews researchers have documented a large-scale leak of Stripe merchant API keys found exposed in public code repositories, GitHub Actions logs, and misconfigured web servers, with over 50,000 unique keys identified in total. The research is practical rather than theoretical: the team tested a sample of the keys, found a meaningful portion still active, and documented exactly how quickly a fraudster could exploit them. The answer is fast. “A dataset published on a data-trading forum on 18 August 2026 contains live Stripe API keys for 659 merchant accounts, along with roughly 35 GB of customer and payment data pulled from them.” reads the report published by Ransomnews. “Ransomnews analysed the files offline and reported the exposure to Stripe before publishing. Stripe itself was not compromised. The keys belong to merchants.” Researchers said that after finding an active Stripe API key, they were able to access a merchant’s customer list, create a fraudulent payment link and make a $1 test charge within 17 hours. The key alone was enough to perform these actions, highlighting the risks of exposed credentials and insufficient API protections. The operations a live Stripe secret key unlocks are extensive: listing customers and their stored payment methods, creating charges and payment intents, issuing refunds to attacker-controlled accounts, modifying webhook endpoints to intercept future payment notifications, and in some cases accessing connected accounts if the merchant had enabled Stripe Connect. A secret key is not a partial credential. It’s full API access. The sources of the leaked keys are unsurprising to anyone who has done developer security work. GitHub repositories — both public and accidentally made public, account for the largest share, typically through hardcoded keys in configuration files, .env files committed without a corresponding .gitignore entry, or keys left in code comments. GitHub Actions build logs are the second major source: when a workflow prints environment variables for debugging, any secret that wasn’t properly masked ends up in a log that anyone with repository access can read. Misconfigured web servers are another major source of exposed Stripe API keys. Researchers found over 3,000 servers revealing Stripe-related strings, with about 12% containing keys that worked against the Stripe API. The source of the 659 exposed merchant keys is unclear, but likely includes infostealer logs, public repositories, exposed environment files and misconfigured backups. The collector’s real advantage was systematically validating the keys, accessing each account and organizing the stolen data. “The dataset doesn’t say, and we are not going to guess at a single source for 659 separate merchants. The realistic candidates are the ordinary ones: secret keys sitting in infostealer logs lifted from developer machines, keys committed to public repositories, keys left in exposed environment files, keys pulled out of misconfigured backups. Stripe’s own documentation says the company scans for exactly this, and describes finding merchant keys on repositories and package registries.” concludes the report. “What the collector added was patience. Gathering keys is common. Validating several hundred of them, then systematically walking the API for each account and archiving the results into a consistent folder structure, is a different level of effort.” Stripe does provide automatic secret scanning through GitHub’s partner program, which flags Stripe keys found in public repositories and can trigger automatic revocation when a merchant opts in. The problem is that opt-in rate is low, the scanning doesn’t cover private repositories, and it has no coverage over build logs, web server misconfigurations, or other platforms where keys surface. Ransomnews also found that some merchants had rotated their keys after a GitHub exposure but left the old keys active, possibly because Stripe doesn’t revoke keys on rotation unless you explicitly delete the old one. The remediation is not complicated. Audit your current Stripe keys against your version control history to see if any have ever been committed. Rotate any key that has touched a public repository, a build log, or a configuration file that wasn’t explicitly protected. Enable Stripe’s restricted keys for any integration that doesn’t need full account access — a webhook handler doesn’t need the ability to create charges. And enable Stripe Radar rules to flag unusual charge patterns that might indicate someone else is using your key before you’ve noticed it’s gone. Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, data leak)
The Cybersecurity and Infrastructure Security Agency (CISA) said Tuesday that the Medusa ransomware gang has breached more than 500 critical infrastructure organizations in the United States since June 2021. This was revealed in a joint advisory in coordination with the Department of Health and Human Services (HHS) and the Federal Bureau of Investigation (FBI). "As of April 2026, Medusa actors have impacted more than 500 victims across multiple critical infrastructure sectors, including Healthcare and Public Health, Defense Industrial Base, Critical Manufacturing, Government Services and Facilities, Information Technology, and Financial Services," they said. "Other victims include organizations in the medical, education, legal, insurance, technology, and manufacturing industries." This is an update to a joint report published in March 2025, which said the Medusa ransomware operation had impacted an estimated over 300 critical infrastructure organizations.
A Heights Finance breach exposed personal and financial data of over 1.2 million people after hackers compromised a third-party cloud platform. Heights Finance is a U.S. consumer finance company that provides personal loans and related lending services, mainly to customers who may have limited access to traditional bank credit. It is part of Heights Finance Holdings Co. Heights Finance Holdings is notifying more than 1.2 million people that on May 7, 2026, Heights Finance discovered unauthorized access to a third-party cloud platform storing customer data. The company launched an investigation with external cybersecurity experts and notified federal law enforcement. “On May 7, 2026, Heights discovered that an unauthorized actor gained access to a cloud-based platform hosted by a third party that we use to store certain customer data. This activity was limited to the cloud-based platform only—it did not affect any of our loan management systems or other computer systems or networks. We immediately activated our incident response protocols, brought in outside cybersecurity specialists to investigate, and reported the incident to federal law enforcement.” reads the notice of data breach. “We have since confirmed that the cloud-based platform is secure and that there is no ongoing security threat. Our operations were not impacted by this incident and have continued safely and securely.” Heights said its internal systems and operations were not affected, the platform has been secured, and there is no ongoing threat. The compromised customer information included contact details, financial and bank account data, government IDs and dates of birth. The affected data varies by person and may involve Heights Finance customers, loan applicants, people who inquired about its products, or former borrowers of Curo Management and related brands. Heights Finance is offering affected individuals 24 months of free credit monitoring and identity protection. The company said dark web monitoring has found no evidence that the stolen data has been published. No threat actor has claimed responsibility, and no known ransomware or extortion group has been linked to the breach so far. Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, Heights Finance)
A custom Java web shell likely linked to the Clop ransomware gang was designed specifically for PTC Windchill and FlexPLM servers, with built-in features to decrypt credentials, enumerate file repositories, and steal files. Cybersecurity company ReliaQuest analyzed the web shell after it is believed to have been deployed in recent data theft attacks exploiting CVE-2026-12569, a critical remote code execution vulnerability affecting PTC Windchill. ReliaQuest says the implant is not a generic web shell repurposed for the attacks, but was instead built with detailed knowledge of Windchill's internal APIs, database schema, keystore, and file-vault structure. "This appears to be an application-specific evolution of Clop's established mass-exploitation playbook," ReliaQuest said in a report shared with BleepingComputer.
Researchers tested 31 million patterns to disrupt surveillance AI, with promising results but significant gaps between simulation and real-world use. The Kansas City-based cybersecurity researcher Bill Swearingen spent the past year doing something that sounds almost too simple to work: printing patterns, watching cameras fail to detect them, and repeating. TechCrunch reports that after roughly 31 million tests, he can now generate patterns on demand that block license plate readers and surveillance cameras from recognizing whatever the pattern covers, whether that’s a person or a vehicle. The project is called noRecognition, and the core idea isn’t stealth in the traditional sense. The camera still records everything just fine. What breaks is the detection layer sitting on top of the footage, the software that flags license plates, tracks faces, or spots “activity of interest” across thousands of hours of video. Swearingen’s patterns don’t hide you from the lens; they make the algorithm looking through that lens shrug and move on. Swearingen, co-founder of the SecKC meetup, said his project started for personal reasons. He became concerned about the growing number of surveillance cameras in his town and the possibility of being tracked while attending a protest. What started as a simple experiment later became a reinforcement learning system. He taught the model to create patterns, learn from failures and keep improving. Over time, it learned how to avoid detection by several camera systems. Every time a pattern failed and got detected, the system adjusted and tried again, eventually learning to defeat multiple detection algorithms simultaneously rather than just one at a time. The research dashboard behind the project, published at sandbox.norecognition.org, goes considerably deeper into the numbers than the headline claim suggests, and it’s refreshingly upfront about what’s proven versus what isn’t. The team states its overall objective plainly as “one pattern that defeats every detector,” and by their own account that goal remains only partially met. Their strongest validated result against a detector extracted directly from a real deployed surveillance camera sits at 61.7% non-detection across held-out test subjects, a solid number, but nowhere near total, and still a digital simulation rather than a real-world fabric test. That distinction matters more than it might seem. Most of the dashboard’s headline figures are explicitly labeled as digital, simulated results, meaning the pattern was tested against a virtual camera and printed ink model rather than an actual garment photographed by an actual camera in the field. The gap between “works in simulation” and “works when Donut Media wraps a real 2009 Toyota Yaris in it,” which is the physical test Swearingen ran live at DEF CON, is exactly the gap this kind of research has to close before anyone should treat it as a reliable, everyday privacy tool. “On Friday at the Def Con cybersecurity conference in Las Vegas, Swearingen ran his first real-world test. With help from Donut Media, the test involved covering a 2009 Toyota Yaris with one of Swearingen’s newest patterns to see if the car would be invisible to detection by a Flock camera.” reports TechCrunch. “We proved it was effective,” said Swearingen, though the wheels were a challenge. The video of the demo will be out in the next few weeks, said Donut Media.” That DEF CON demo is where things got concrete. Swearingen covered a car in one of his newest patterns and tested it against a Flock Safety camera, the kind widely deployed for automated license plate reading across the US. He said the test proved effective, though the vehicle’s wheels turned out to be a persistent weak point, curved surfaces apparently don’t cooperate with flat printed patterns the way a car door does. Source Tech Crunch – A photo of a 2009 Toyota Yaris at the Def Con conference in Las Vegas, covered in a pattern made by Bill Swearingen, as part of a test to see if it can defeat surveillance camera detection. Image Credits:Bill Swearingen / Donut Media Swearingen is not publishing his best patterns because he does not want camera makers to easily find and block them. Instead, he is using crowdfunding to develop and sell printed products such as T-shirts and hoodies, with vehicle wraps possibly coming later. It is still unclear whether the project will become a practical privacy tool for everyday users or remain mainly a DEF CON demonstration. Its real effectiveness will depend on how well the patterns work on real clothing, in different weather and camera conditions. Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, Surveillance camera)
Microsoft has started testing a faster File Explorer and a less cluttered and more customizable context menu in Windows 11 preview builds rolling out to Insiders this week. As the File Explorer team explained in a Monday blog post, the changes focus on improving File Explorer speed, performance, and reliability and addressing customer-reported issues. The redesigned context menu experience also aims to make it faster, reduce clutter, and make it more customizable than ever before. At the bottom of the new right-click menu, Microsoft also added a "Customize menu" shortcut to the Settings page, where users can tweak the context menu to suit their preferences. "We've continued refining File Explorer based on that feedback, removing friction and improving the details that help make everyday tasks feel more natural and predictable. For example, file renames no longer get interrupted by background file synchronization, and case-only filename changes now appear immediately," Microsoft said.
The U.S. Cybersecurity and Infrastructure Security Agency (CISA) has confirmed that ransomware gangs are also exploiting a high-severity Windows Task Host vulnerability that was flagged as actively exploited in April. Task Host is a core Windows system component that allows DLL-based processes to run in the background and prevents data corruption by ensuring they close properly during shutdown. Tracked as CVE-2025-60710, this Windows privilege escalation security flaw was patched by Microsoft in November 2025 and stems from a link following weakness that affects Windows 11 and Windows Server 2025 devices. Following successful exploitation, local attackers with basic user permissions can gain SYSTEM privileges and take full control of unpatched devices. While it didn't share any details regarding ongoing attacks and Microsoft has yet to update its security advisory to confirm in-the-wild exploitation, CISA added CVE-2025-60710 to its list of actively exploited vulnerabilities on April 13 and gave Federal Civilian Executive Branch (FCEB) agencies two weeks to secure their systems.
A ransomware affiliate calling itself Ransom Busters has been spotted proactively sending emails to victim organizations and claims to delete stolen data from ransomware groups' servers in exchange for a fee ranging from $20,000 to $60,000. "In these messages, the third-party offers to help the victim recover from ransomware attack. This immediately stands out as anomalous," GuidePoint Research
A threat actor is selling employee databases allegedly stolen from the Microsoft Azure infrastructure of multiple Fortune 500 companies after gaining access using compromised credentials. Starting July 31st, multiple posts from someone using the alias “TheHatman” advertised data dumps from major organizations, including McDonald's, Gap Inc., Vodafone, Tata Consultancy Services, HCL Technologies, InterContinental Hotels (IHG), and Kyndryl. In total, the threat actor claims to have 3.64 million data records, with the most recent breach posted on Sunday, containing an alleged 1.7 million employee records from McDonalds. “I’m selling McDonald’s Corporation internal employee dump downloaded directly from Azure Tenant using compromised credentials,” the threat actor says in the post.
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