In a large-scale campaign that researchers dubbed CameraSwarm, hackers compromised more than 14,500 Dahua IP cameras mostly in Ukraine and Russia. The operation ran for at least 35 days between June 17 and July 22, compromising devices by exploiting vulnerabilities, brute-forcing logins, and using offline recovery codes from serial numbers for cloud-registered cameras. Researchers at threat intelligence company Hunt.io discovered the campaign after finding a working directory on an HTTP server that the operator left unprotected. Hunt.io recovered 407 MB of data comprising 2,616 files across 234 directories, including source code, logs, credentials, captured camera images, shell history, and exploitation results, which helped them map an impressive operation. According to their findings, the 35-day CameraSwarm campaign compromised 14,530 Dahua IP cameras using three attack methods in parallel:
U.S. cybersecurity agencies warn that threat actors are using AI-generated scripts to exploit Siemens S7 Series programmable logic controllers (PLCs) in U.S. critical infrastructure. PLCs are industrial computers used to automate and control machinery and physical processes in factories and other critical infrastructure. The NSA, CISA, FBI, Department of Energy, and Environmental Protection Agency issued the joint advisory Wednesday, saying the attacks are ongoing. "This advisory relates to an active threat to Siemens S7 Series programmable logic controllers (PLCs)," reads the advisory. "However, ongoing PLC targeting activity is broader than Siemens PLCs. All PLC owners and operators should apply relevant mitigations to reduce the risk to their devices and systems." The critical infrastructure sectors most targeted include Critical Manufacturing, Energy, Water and Wastewater Systems, Chemical, Food and Agriculture, and Commercial Facilities. The agencies also note that Siemens S7 PLCs are used in the Defense Industrial Base, which could also be targeted.
Huntress observed a 155x increase in password spraying attacks in H1 2026, including a campaign that generated more than 81 million login attempts in two weeks. The attacks exploited legacy authentication and gaps in MFA policies that left some login flows unprotected.
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)
Cybersecurity researchers at Hunt.io have disclosed details of a campaign that they say compromised more than 14,530 Dahua devices between June 17 and July 22, 2026, using credential attacks, two authentication-bypass flaws, and a peer-to-peer (P2P) relay technique. The activity, codenamed Operation CameraSwarm, was reconstructed from a 407 MB exposed working directory containing 2,616 files
Two critical vulnerabilities impacting MLflow, an open-source artificial intelligence (AI) platform, and FUXA, an open-source, web-based SCADA / HMI software built for operational technology (OT) and industrial automation, are witnessing malicious scanning and exploitation efforts. According to independent reports from watchTowr and VulnCheck, the vulnerabilities in question are as follows -
The SANDCLOCK LiteLLM supply-chain attack exposed credentials across 2,038 repositories, affecting technology, finance, healthcare, retail and more. Resecurity (USA) estimated the most affected sectors by the “SANDCLOCK” backdoor, which was planted as a result of the code repository compromise. According to cybersecurity experts, LiteLLM / TeamPCP Supply-Chain Attack will have long-lasting consequences. By compromising a well-known component in AI applications, adversaries will multiply the blast radius—some of the victim organizations are still unaware of the backdoor and its impact. LiteLLM is a popular open-soure AI gateway and utility library that unifies API calls for over 100 large language model providers, such as OpenAI, Anthropic, Google Gemini, and local Ollama models. Such incidents involve substantial MTTD (Mean Time to Detect) and MTTR (Mean Time to Respond). The threat actor group “TeamPCP” compromised maintainer credentials for LiteLLM and published malicious package versions 1.82.7 and 1.82.8 to PyPI around March 2026 – creating a window of exposure lasting at least a few months. Over 2,500+ organizations and hundreds of thousands of CI/CD environments suffered full-credential exposure, compromising cloud infrastructure keys, repository access tokens, SSH credentials, Kubernetes secrets, and AI provider API keys (such as OpenAI and Anthropic). Resecurity has acquired the 150GB archive attributed to the LiteLLM supply-chain attack conducted by TeamPCP using the “SANDCLOCK” credential-stealer. Per published incident reporting — accompanying victim manifests enumerate 898 compromised GitHub owners (organisations/accounts) across 2,038 repositories. The affected owners include major global enterprises — among them Microsoft, Azure, IBM, NVIDIA, PayPal (Zettle), Deloitte, Bosch, S&P Global, Elevance Health, 84.51° (Kroger), Adeo (Leroy Merlin), Kärcher, Dräger, ID.me and 1inch. Top 10 the most impacted sectors (by victim organization profile): Technology / Software Banking / Finance / Insurance Healthcare / Pharma / Medtech Retail / E-Commerce Media / Gaming / Adtech Manufacturing / Industrial Professional Services Cybersecurity Crypto Government Resecurity enumerated 2,146 records by key name (values never inspected beyond structural masking). The composition is overwhelmingly GitHub CI-CD identity material, with a long tail of high-value cloud and registry credentials. Victim manifests (owners.txt, repos.txt) enumerate 898 distinct compromised GitHub owners across 2,038 repositories. The distribution is long-tailed: 631 owners have a single affected repo, while the most-affected owner (Cencosud-Cencommerce) has 64. Critically, the owner list includes major global enterprises and regulated organisations. Every organization affected by the LiteLLM incident should revoke or rotate GitHub App private keys, PATs, AWS/GCP/Firebase credentials, ECR/JFrog tokens, SSH keys, and signing passwords, and invalidate sessions. Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, newsletter)
GitHub is down for some users as a widespread outage is causing errors across the website, API, Actions, Pull Requests, and several other services. GitHub confirmed the outage at 9:40 AM EDT on August 17, 2026, when it said it was investigating reports of performance problems affecting some of its services. The problems quickly spread across several parts of GitHub that developers rely on, including API Requests, Actions, Webhooks, Issues, and Pull Requests. According to GitHub's status page, the company is seeing error rates of around 20% across its web experience and API traffic. GitHub says archive downloads and raw repository content downloads are experiencing error rates of approximately 50%. Likewise, authentication-related services are also having problems, with SAML and OIDC authentication, SCIM, and Team Sync affected by the incident.
Author: Len Noe, Solutions Architect, BeyondTrust Every mature Active Directory environment has a component that quietly holds more power than the people running it usually admit: the Certification Authority (CA). The thing your entire estate has agreed to believe. When it signs a certificate, every machine, service, and authentication flow downstream treats that signature as truth. That is an enormous amount of trust concentrated in one system, and most organizations manage it like a utility installed once and never thought about again. Certighost, tracked as CVE-2026-54121, is a reminder of what happens when that trust is misplaced. Researchers published a working proof-of-concept on July 24, 2026, demonstrating that a low-privileged Active Directory user (holding nothing more than a standard domain account) can coerce an Enterprise CA into issuing a valid authentication certificate for a Domain Controller, then use that certificate to become the Domain Controller.
A seller claims 1.7M McDonald’s employee records were stolen from Azure. An 8,000-row sample appears genuine, but its age and full size remain unconfirmed. A seller on a data-trading forum posted an 8,000-row sample this week claiming it came from McDonald’s own Azure tenant, part of a supposed 1.7 million-record employee directory obtained using stolen credentials. Ransomnews’s technical breakdown found the sample holds up as genuine on every test that can be run against it. What it can’t confirm, notably, is exactly how old the data is or whether the full 1.7 million figure is real. “The listing is a straightforward private sale, posted at 4:08 AM forum time under the title “McDonalds 1.7M+ Azure Internal Employee Dump”. The seller, an account called TheHatman, writes that the data was “downloaded directly from Azure Tenant using compromised credentials” and that it contains “employee accounts, service accounts, and other tenant account records”. No price is named. Buyers are invited to make offers.” reads the report published by Ransomnews. “To evidence the claim, the seller attached a free 8,000-record sample. That file is the entire basis for what follows. Ransomnews analysed it offline. We did not access, probe or authenticate against any McDonald’s system, and we have redacted the sample’s download location from the screenshot below because it still resolves to real people’s contact details.” The file’s structure gives away exactly what it is before you even read a single row. Column names like FacsimileTelephoneNumber and PhysicalDeliveryOfficeName aren’t something anyone invents; they’re the exact property names Microsoft’s own PowerShell directory tools return when an administrator exports a user list from Entra ID, the modern name for Azure Active Directory. Whoever produced this file ran a standard Microsoft export command and saved the output, nothing more exotic than that. Every one of the 50 email domains found in the sample is genuinely McDonald’s-controlled, spanning corporate staff, restaurant crew accounts, franchisee logins, and vendor guest access across more than thirty countries. Three rows even carry the tenant’s own built-in Microsoft address, mcdonaldscorp.onmicrosoft.com, something that’s invisible from outside the organization and simply isn’t guessable or scrapeable. Add in 233 rows with the exact kind of garbled text encoding that happens when someone forgets to specify UTF-8 during an export, plus 85 job titles cut off at precisely 30 characters mid-word, the unmistakable fingerprint of a fixed-width HR system field bleeding into the directory, and you get a picture consistent with a real export rather than something assembled from public sources. “The file is broken in the ways real exports are broken. 233 rows contain mangled characters: Königswinter appears as “Königswinter”, München as “München”, and Ukrainian job titles are rendered as unreadable strings of Cyrillic run through the wrong character set. This is what happens when somebody runs Export-Csv without specifying UTF-8 encoding.” continues the report. “It’s a mistake, and it is not the kind of mistake anybody makes on purpose. A fabricated dataset doesn’t come with authentic encoding damage.” One detail actually reaches outside the file entirely. A restaurant entry for “556 Upton” on Upton By-Pass in Wirral, complete with phone number, matches a real, publicly listed McDonald’s location down to the digit. That’s a small anchor, but it’s the kind of anchor fabricated data doesn’t usually survive contact with. What the sample genuinely can’t settle is timing. There isn’t a single date field anywhere in the schema, no creation date, no last login, nothing to age a row by. “We can say with confidence that the data came out of McDonald’s directory. We cannot say from the file alone when it came out.” The best clue available is McDonald’s own market footprint: no Russian records at all, consistent with the company’s 2022 exit, and no Kazakh ones either, which points to sometime in 2023 or later, a wide window rather than a firm date. The 1.7 million headline number also isn’t something 8,000 rows can verify. That sample is under half a percent of the claim, and while nothing in it looks implausible given McDonald’s global workforce size, plausible isn’t the same thing as confirmed. A seller running a volume trade across multiple companies has every incentive to round the number up in the listing title. This McDonald’s post wasn’t an isolated event either. The same account, going by TheHatman, posted nine listings in total over sixteen days, claiming roughly 3.6 million records combined across McDonald’s, Vodafone, Gap, two hotel chains, and four major IT outsourcing firms including Kyndryl and Tata Consultancy Services. Every listing uses an identical 19-column schema and nearly identical wording, the kind of consistency you get from one person running the same export script against whatever tenant they currently hold a working login for, not from someone fabricating nine separate datasets by hand. That pattern points toward something fairly mundane and fairly common: infostealer malware harvesting saved credentials at scale, feeding a resale market that lets one operator walk into tenant after tenant using logins nobody bothered to protect with multi-factor authentication. Reading an entire company directory doesn’t require a sophisticated intrusion; it requires one working account in a tenant that hasn’t restricted user enumeration, which is Entra ID’s default setting unless an administrator has explicitly locked it down. For anyone at McDonald’s or one of the other eight listed companies, the real risk here isn’t account takeover, since there are no passwords or hashes in the sample at all. It’s social engineering: full names, job titles, direct phone numbers, and internal email formats are more than enough to make a fake helpdesk call or a fraudulent invoice sound completely legitimate. Treat unsolicited contact that already knows your role and your location with more suspicion than usual, because that’s precisely the kind of detail this file was built to hand someone. “For individuals named in the data, there is no action that removes the exposure.” concludes the report.”The realistic response is scepticism about unsolicited contact that arrives already knowing your role and your store, and a refusal to act on instructions that arrive by phone or email without out-of-band confirmation.” Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, McDonald’s)
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