A researcher chained two Unitree G1 flaws to gain root access remotely and showed how a compromised robot could attack others nearby.
Security researcher Olivier Laflamme spent about three months digging into the Unitree G1 humanoid robot and eventually found a way to fully compromise it without plugging in a single cable. In his technical write-up, he details two vulnerabilities, CVE-2026-76639 and CVE-2026-76640, that can be chained across Bluetooth, Unitree’s cloud infrastructure, the mobile app, and the robot’s firmware to gain unauthenticated root access to any G1 within Bluetooth range.
The first bug lives entirely inside the robot itself, no wireless attack surface needed if you can reach it over Ethernet. The G1’s AI chatbot service accepts a “knowledge” upload with almost no validation on the filename it writes to disk, and a classic path traversal payload lets an attacker write an arbitrary file anywhere on the filesystem, including into a directory that a separate service called bashrunner treats as trusted. Restart bashrunner, tell it to run the newly planted file, and you’ve got root-level shell execution with five DDS messages and zero authentication.
The second chain is the one that should worry anyone deploying these robots at scale. It starts with a Bluetooth characteristic that accepts writes without pairing, something The Hacker News also covered in its own report on the disclosure. An unpaired device can request the robot’s encrypted key bootstrap blob, and Unitree’s cloud API would decrypt that blob for any free, logged-in Unitree account without ever checking whether the account actually owned that specific robot.
“The blob is RSA-encrypted & the corresponding RSA private key is held by Unitree’s cloud infrastructure. This, in theory, is safe.. This is the security boundary Unitree appears to have relied on. Nearby devices can request the bootstrap blob, but only Unitree owns the RSA private key capable of opening it.” reads Laflamme’s report. “However, the Unitree mobile app reassembles the BLE notification chunks and slingshots that shit via a POST to Unitree’s cloud API /device/bindExtData on global-robot-api.unitree.com and the app stores the response body as gcmKey.”
That decryption oracle is the crux of the whole chain, and Laflamme doesn’t undersell how convenient it made everything.
“This single AES-128 key unlocks both the BLE protocol and the WebRTC signaling channels.” continues the report.
Once an attacker has obtained it, they can authenticate to the robot’s Bluetooth handshake and unlock WiFi configuration commands that were previously locked behind that same key. From there, an oversized WiFi password triggers a fallback code path in Unitree’s own configuration script that inserts attacker-controlled text directly into a config file without escaping it, letting the attacker force the robot to join a hotspot they control, no physical access needed at any point.
Going from “the robot connects to my Wi-Fi” to a full root shell required a buffer overflow in the G1’s Bluetooth server, and this is where the research gets particularly impressive. The server used a 500-byte buffer without proper bounds checking, allowing Laflamme to overwrite nearby memory with a carefully crafted 1,050-byte payload. He used that payload to create a fake cleanup structure that the program later interpreted as a legitimate function pointer, causing it to execute an attacker-controlled command with root privileges.
There was one more obstacle: randomized memory addresses. To make the exploit work reliably, Laflamme first needed to discover where the vulnerable program was loaded in memory. He solved that by turning the first vulnerability into an information leak and using the result to make the second exploit work. In other words, one bug effectively helped unlock the other.
The wormability is what turns this from an interesting security flaw into a much more serious operational risk. Once an attacker compromises one G1, that robot can use the same attack against other G1 robots within Bluetooth range, without requiring additional discovery or configuration.
Laflamme tested the technique on just two robots in the same room, so the real-world reach of a chain reaction remains unclear. In a warehouse, laboratory, or campus where dozens of these robots operate close to each other, however, the possibility of one compromised machine spreading the attack to others is difficult to ignore.
Unitree’s response gets genuine credit in the writeup, and it’s worth noting given how often vendor disclosure stories go badly. The company patched the cloud ownership-check flaw within about two months of the report, paid out a combined $5,000 bounty across both chains, and worked through verification quickly enough that Laflamme calls the collaboration close to ideal.
“July 1-6 August, 2026 — Unitree implemented an account-to-robot cloud binding ownership check before returning the AES-128 key. Patching the “cloud-oracle” vulnerability discovered back in May.“August 6, 2026 — a $5,000 USD bounty was paid out, $4,000 for the BLE RCE and $1,000 for the chat_go RCE.”
The BLE pairing and buffer overflow issues themselves, notably, sit deeper in the firmware and represent a harder, slower fix than a simple cloud-side ownership check.
None of this required exotic tools or some cutting-edge attack technique. That is probably the detail that should get the most attention from anyone who still sees robot security as a niche problem.
This was a $20,000 humanoid robot, the kind increasingly used in research labs and universities and likely to appear in more workplaces, compromised with a decompiled Android app, a firmware encryption scheme that researchers had already broken years ago, and a familiar class of buffer overflow that predates humanoid robots by decades.
If your organization has a G1 sitting in a lab, lobby, or workspace, checking its patch status should be a priority. A 90-pound robot losing its collision-detection capabilities is not the kind of security incident you want to discover the hard way.
“You could use the G1 to spy on people through audio and video, make it say obscene shit in public, swap out or backdoor the ResNet onboard AI models, tamper with perception and movement logic, disable collision detection and other safety checks (it weighs ~90lbs having that run into a kid, a wall, or even step on your toe will do some serious damage).” concludes the researcher. “They also cost a lot! I’d be pissed off if someone hacked into my G1, took control of it, and walked it off my factory/campus.”
Hoje, pode parecer que há uma câmera nos observando em cada canto: na campainha com vídeo na entrada, na webcam de um notebook no escritório de casa, na babá eletrônica IP no quarto das crianças, na smart TV com câmera e microfone no quarto, no robô aspirador com câmera de navegação… Até um alimentador inteligente para gatos pode estar espionando você! E qualquer uma dessas câmeras pode facilmente se transformar em uma ferramenta de extorsão, chantagem ou curiosidade mal-intencionada.
Neste artigo, analisamos exatamente de onde vem a ameaça e apresentamos cinco regras que podem reduzir bastante as chances de você virar a estrela do show de um voyeur.
Casos reais de vigilância
Pornografia de hotel por assinatura
Infelizmente, relatos sobre câmeras em miniatura encontradas em quartos de hotel e apartamentos alugados se tornaram quase rotineiros. Tecnicamente, elas pertencem a uma categoria diferente de dispositivos: “câmeras espiãs” disfarçadas de tomadas, detectores de fumaça ou despertadores. Mais adiante, explicaremos como detectá-las.
Os criminosos não se limitam a publicar imagens de câmeras espiãs. Também fazem transmissões ao vivo. O acesso a vídeos íntimos, naturalmente, não é gratuito. Em algumas regiões, criminosos montaram uma infraestrutura em torno das câmeras espiãs: uns instalam os dispositivos, outros processam as imagens e outros vendem o acesso pela dark web ou por aplicativos de mensagens. Em geral, as vítimas descobrem que havia uma câmera oculta no quarto do hotel por acaso, depois de se depararem com vídeos de si mesmas em sites pornográficos.
Caça a motoristas
Outro vetor de ataque comum é a invasão de câmeras veiculares conectadas à Internet. Esses dispositivos são alvos atraentes para invasores: a segurança é fraca, e as imagens mostram claramente placas de veículos, sinalização viária e endereços em prédios. As gravações também contêm metadados detalhados, incluindo datas exatas, coordenadas de GPS e outras informações.
Isso pode permitir que criminosos identifiquem as rotas habituais da vítima, descubram onde o carro fica estacionado ou até escutem conversas com passageiros. As informações podem ser suficientes para uma vigilância completa, o roubo do veículo ou até chantagem, caso a câmera grave conversas e imagens dentro do carro.
Stalking
Nem todas as imagens roubadas de câmeras resultam de ataques de cibercriminosos profissionais em busca de lucro. Às vezes, stalkers invadem webcams para espionar pessoas específicas, muitas vezes alguém que conhecem. Por exemplo, em 2025 veio à tona um caso em que um homem vinha espionando colegas de trabalho havia anos por meio das câmeras IP instaladas nas casas delas. Todas as vítimas eram mulheres, e não faziam ideia de que estavam sendo observadas.
Em outro caso, um homem monitorava a ex-esposa e a filha por meio de um sistema de interfone e câmeras IP. Ele nem tentava esconder que espionava a própria família e chegou a enviar à filha capturas de tela da webcam. Como consequência, ela acabou tendo que se mudar.
Por que isso acontece?
Negligância com regras básicas de cibersegurança
Esse é provavelmente o principal motivo pelo qual câmeras IP são invadidas. A maioria dos usuários não altera senhas padrão de roteadores, dispositivos inteligentes e aplicativos conectados a eles. Essas senhas são praticamente de conhecimento público. Muitas vezes, são usadas combinações simples, como “admin/admin” ou “root/1234”, que todos conhecem ou que podem ser adivinhadas em segundos sem um algoritmo sofisticado. Foi exatamente isso que permitiu aos invasores comprometer 120.000 câmeras na Coreia do Sul.
Fabricantes de câmeras irresponsáveis
Embora os fabricantes garantam que os dados das câmeras sejam armazenados apenas localmente, na prática, costuma ser bem diferente. Por exemplo, em 2022, pesquisadores descobriram que uma linha popular de câmeras de vídeo enviava capturas de imagem ao servidor do fabricante sempre que uma pessoa aparecia no quadro. E mais: o acesso remoto às gravações de todas as câmeras ficava disponível por URLs previsíveis, o que tornava essas URLs relativamente fáceis de reproduzir ou adivinhar.
Ao mesmo tempo, a empresa afirmava que suas câmeras usavam criptografia de ponta a ponta, armazenavam gravações apenas no dispositivo e não enviavam dados a servidores externos. Por sinal, a suposta “criptografia segura” era implementada com uma chave fixa idêntica para todos os usuários. E a própria chave podia ser facilmente encontrada no código-fonte publicado pelo fabricante.
Em resumo, se um dispositivo tem lente e Wi-Fi, considere a possibilidade de que, mais cedo ou mais tarde, uma falha grave de segurança seja descoberta nele.
Mecanismos de busca para dispositivos vulneráveis estão se tornando cada vez mais populares
Para acessar uma câmera, muitas vezes o invasor só precisa saber o endereço IP dela e testar algumas senhas comuns. Existem mecanismos de busca que indexam dispositivos e suas portas abertas, em vez de sites: webcams, roteadores, controladores industriais, equipamentos médicos e muito mais.
Se uma câmera IP não exigir nome de usuário e senha ou estiver “protegida” pelas credenciais padrão “admin/admin”, ela pode ser facilmente descoberta e adicionada ao banco de dados de um serviço de OSINT. Jornalistas e pesquisadores já usaram esses serviços para encontrar câmeras acessíveis ao público em quartos de crianças, escritórios, salas cirúrgicas de hospitais, bancos e lojas.
Então, o que fazer?
O que é possível fazer em casa ou em um pequeno escritório sem uma equipe dedicada à segurança? Estas cinco recomendações simples podem ajudar.
1. Pesquise sobre o fabricante
Ao escolher um modelo de câmera IP, verifique se câmeras daquele fabricante já foram invadidas. Por exemplo, pesquise por “invasão de câmera IP nome do fabricante“. Depois, acesse a seção de Suporte do fabricante e confira a data da atualização de firmware mais recente para o modelo considerado e para modelos mais antigos.
Se o firmware não tiver sido atualizado nos últimos seis meses ou se as atualizações forem lançadas de forma irregular, considere escolher outro modelo. A maioria das câmeras usa versões embarcadas especializadas do Linux, e mais de 2.300 vulnerabilidades foram registradas no kernel do Linux nos primeiros seis meses de 2026. Sem atualizações regulares de firmware, é quase certo que, mais cedo ou mais tarde, as câmeras de um fabricante apresentarão uma falha de segurança.
Considere modelos de grandes fabricantes para evitar uma coleção inteira de vulnerabilidades com praticamente nenhuma chance de que elas sejam corrigidas. Câmeras baratas de empresas pouco conhecidas, com recursos limitados e proteção fraca, podem acabar saindo caras.
2. Desative recursos desnecessários
Quanto menos serviços de armazenamento em nuvem de terceiros estiverem envolvidos no sistema de vigilância, melhor. Ao escolher uma câmera, procure um slot para cartão microSD ou compatibilidade com dispositivo de armazenamento conectado à rede (NAS), para que todas as gravações possam ser armazenadas localmente.
O ideal é que a câmera consiga funcionar na rede local, sem transmitir dados para a nuvem ou para os servidores do fabricante, com visualização pela LAN ou por meio de uma conexão segura com a rede doméstica ou do escritório.
Depois de comprar uma câmera IP, revise as configurações, geralmente disponíveis no aplicativo do fabricante ou pela interface Web da câmera, e desative tudo o que não for necessário.
Preste atenção aos recursos relacionados ao reconhecimento de pessoas, inteligência artificial, permissões do sistema, descoberta de outros dispositivos na rede e armazenamento em nuvem. Se você não usa um recurso, pode desativá-lo.
Nas configurações de rede, confirme que o UPnP (Universal Plug and Play) está desativado ou sequer disponível como opção. O UPnP pode permitir que a câmera se torne acessível a outros dispositivos pela Internet.
Verifique se o acesso P2P à webcam está desativado ou indisponível, para que a câmera não se conecte a servidores externos nem possa ser acessada pela Internet sem seu controle direto.
Crie o hábito de verificar quem está conectado à sua conta e quem ainda tem acesso às suas gravações. Se você concedeu acesso à webcam a um amigo para ficar de olho no seu cachorro durante uma viagem, lembre-se de revogar depois os acessos ou encerrar as sessões desnecessárias. E, se você terminou um relacionamento recentemente, verifique com atenção especial se a pessoa com quem se relacionava ainda tem acesso. Para saber mais, consulte Higiene digital após uma separação: o que verificar e desativar.
3. Altere as configurações padrão
As senhas padrão de fábrica são conhecidas pelos invasores há anos. Se você ainda não alterou o nome de usuário e a senha do roteador ou da câmera IP, um invasor pode conseguir acesso em questão de segundos.
Substitua o nome de usuário e a senha padrão de fábrica do roteador por credenciais exclusivas e longas. Isso pode ser feito pela interface Web do roteador. Explicamos abaixo como acessá-la. Para gerar e armazenar senhas fortes e exclusivas, recomendamos usar Kaspersky Password Manager.
Atualize o firmware do roteador e da câmera IP para as versões mais recentes, mesmo que você tenha acabado de comprar os dispositivos, e crie o hábito de fazer atualizações regularmente. Campanhas de invasão de câmeras IP em grande escala muitas vezes exploram vulnerabilidades conhecidas há muito tempo, que só podem ser corrigidas com a instalação de atualizações.
4. Coloque todas as câmeras e dispositivos inteligentes em uma rede Wi-Fi separada
Recomendamos segmentar o Wi-Fi doméstico em sub-redes separadas. Você provavelmente já viu essa configuração em cafés, que costumam ter uma rede Wi-Fi para a equipe e outra para visitantes.
O ideal é colocar todas as câmeras IP e outros dispositivos de casa inteligente em uma rede Wi-Fi separada e totalmente isolada de notebooks, celulares e outros dispositivos de trabalho. Melhor ainda, as câmeras IP devem ficar isoladas de todos os demais dispositivos em uma rede Wi-Fi dedicada exclusivamente a elas.
A maioria dos roteadores modernos permite criar pelo menos duas redes Wi-Fi, uma rede principal e uma rede para visitantes. Modelos mais avançados podem oferecer ainda mais opções. Assim, mesmo que a câmera seja invadida, o invasor não conseguirá chegar aos outros dispositivos nem acessar arquivos confidenciais.
Como abrir a interface Web do roteador
Digite o endereço IP do roteador na barra de endereços do navegador. Normalmente, ele está impresso em uma etiqueta na parte inferior do roteador. Entre os endereços IP comuns para roteadores domésticos estão 168.0.1, 192.168.1.1 e 10.0.0.1.
Na página que abrir, faça login. A maioria dos roteadores tem um nome de usuário e uma senha padrão, que normalmente também estão impressos na mesma etiqueta. Alguns roteadores podem solicitar a criação de um nome de usuário e de uma senha. Recomendamos escolher uma senha forte e armazená-la no Kaspersky Password Manager. As senhas padrão de fábrica são conhecidas pelos invasores há muito tempo e, se você não alterar a senha do roteador, eles podem entrar facilmente na sua rede doméstica.
Abra as configurações e procure seções relacionadas à segmentação da rede Wi-Fi ou à criação de sub-redes ou redes para visitantes.
Para obter instruções detalhadas de configuração, consulte o manual do roteador ou a seção de suporte do site do fabricante. Para mais dicas sobre como proteger sua casa inteligente, consulte nossa postagem Como proteger sua casa smart.
5. Aprenda a detectar câmeras ocultas, em casa e durante uma viagem
Nosso último conjunto de recomendações não trata da configuração da câmera em si, mas de boas práticas de segurança.
Crie o hábito de verificar a lista de clientes do roteador. Se você vir um dispositivo desconhecido com um nome estranho ou endereço MAC, investigue o que é e por que está conectado à sua rede doméstica. Nossa solução de segurança inclui um componente dedicado do Smart Home Monitor. Esse recurso pode alertar quando um novo dispositivo se conecta à rede doméstica com ou sem fio, fornecer recomendações simples para melhorar a segurança da rede e identificar senhas fracas do roteador e criptografia insegura.
Durante viagens, recomendamos verificar se há dispositivos de gravação ocultos em quartos de hotel e imóveis alugados:
inspecione locais que ofereçam um bom campo de visão do ambiente, como grades de ventilação, detectores de fumaça, tomadas e objetos decorativos;
no escuro, use o smartphone como detector óptico improvisado: ligue a lanterna e a câmera, examine lentamente o ambiente e procure reflexos característicos produzidos por lentes de câmeras;
use a câmera frontal para procurar fontes de luz infravermelha invisíveis ao olho humano. Isso pode ajudar a identificar a iluminação IR usada para “visão noturna”.
Discover how Microsoft expands its enterprise AI branding by renaming the Microsoft 365 Roadmap to the AI at Work Roadmap to track Copilot and AI agents.
The afterlife of our information is a recent phenomenon, and some of the companies with the most to sort through are still just figuring it out.
As far back as 2007, Facebook was forced to reckon with mass grief when users asked the company to maintain the profile pages of the 32 victims killed by a school shooter at Virginia Tech that year. Those pages became de facto memorials for loved ones to fill with comments, and today, memorialization has become a full-fledged feature on both Facebook and Instagram. Platforms like YouTube, Pinterest, and LinkedIn—launched with likely zero strategy for a user’s death—now have procedures for next-of-kin to request that a deceased person’s account be deactivated.
Now, think about all the other ways your data can linger after death.
Every year, people accumulate more and digital stuff—email addresses, social media profiles, contact lists, domain names, subscription services, online banking accounts, and the phones, laptops, and tablets that hold it all—and every year, as that digital stuff accumulates, it compounds into ever more problems for someone else to sort out. Here, a small industry of digital estate planners have cropped up, helping families retrieve and preserve anything valuable, no matter how digital, from Spotify playlists, to poignant social media posts that mattered, to the photos stored on a phone.
And where retrieval fails, artificial intelligence has offered an attempt at comfort. The chatbot service Replika launched in 2015 after its founder uploaded a dead friend’s text messages. HereAfter AI reportedly let users upload voice recordings to power a chatbot that sounded and spoke like the deceased. Film studios have pursued the same idea for entertainment, seeking to portray deceased actors in future films.
Surprisingly, almost none of this activity is governed by law, said Tamara Kneese, author of the 2023 book “Death Glitch: How Techno-Solutionism Fails Us in This Life and Beyond.”
“By and large, there is not a great legal mechanism for protecting the privacy rights of the dead,” said Kneese. “It may not be just that a grieving loved one decides to use a bunch of your data from all of your podcasts to create a chatbot to simulate interacting with you after you’re dead, but it may be that a company chooses, in some way, to use an aspect of your personality, of your demeanor, of your voice, of your likeness after your death without anyone really being aware.”
Today, on the Lock and Code podcast with host David Ruiz, we speak with Kneese—Senior Research Scientist at Partnership on AI—about who owns a person’s data after they die, why every platform has invented its own private policy for the dead, and how the technology built to keep the dead close can vanish just as suddenly as they did.
Or worse yet, as Kneese warned for those relying heavily on certain technologies in grief:
“The company gets sold to someone else or disappears, goes bankrupt, and you no longer have that outlet or place for interaction when you’re mourning another time.”
FortiGuard Labs discovered the Evooo1Bot Linux botnet. Read our Evooo1Bot Linux botnet analysis to learn how this malware turns devices into proxy nodes.
Purpose and Scope The July 2026 Threat Trend Report on APT Groups summarizes the trend in which state-sponsored threat actors and financially motivated attackers are employing a combination of supply chain attacks, account takeovers, cloud breaches, and social engineering techniques. Key targets include Microsoft 365, webmail accounts, cloud infrastructure, GitHub and development environments, VPN and […]
GitHub's postmortem reveals a service mesh overload triggered a retry storm across its infrastructure, while a Copilot bug sent authentication traffic to 10x normal levels.
Evooo1Bot is a Mirai-based Linux botnet that hijacks routers and IoT devices for DDoS attacks, credential theft and criminal proxy services.
Fortinet’s FortiGuard Labs disclosed Evooo1Bot in mid-August, a previously undocumented Linux botnet that’s been active since July 2026. The bot borrows Mirai‘s DDoS engine but adds encrypted command-and-control communications, an SSH brute-force scanner, a credential sniffer, and a SOCKS5 proxy module on top.
“FortiGuard Labs has been tracking a previously undocumented Linux botnet family, which we have named Evooo1Bot. The name derives from the hardcoded string “evooo1” found in every binary.” reads the report published by Fortinet. “While the malware reuses the DDoS engine from the publicly leaked Mirai source code, it extends the original framework with numerous capabilities, including encrypted C2 communications, an SSH brute-force scanner, a SOCKS relay module, a credential sniffer, and an integrated exploit arsenal targeting multiple known vulnerabilities.”
The botnet targets 18 known CVEs, some of them dating back to 2007, including:
The bot communicates exclusively over port 443, which is intentional: the traffic blends into expected HTTPS flows at the network perimeter. After gaining initial access through one of its exploit modules or via brute-forced SSH credentials, the bot runs a loader script that clears Bash history to erase evidence of the intrusion before pulling the architecture-appropriate binary from an external server.
The breadth suggests the operators are scanning opportunistically for anything unpatched rather than targeting specific organizations.
“This capability significantly increases the value of an infected host to attackers. The victim’s IP address can be used to disguise malicious traffic, bypass geographic restrictions, or provide access to internal networks through an already compromised machine.” continues the report. “In larger botnets, the same functionality could also be used to build a distributed proxy infrastructure, enabling anonymous traffic forwarding or monetization through residential and enterprise proxy services.”
Evooo1Bot stands out because of its proxy module. A network of compromised routers, cameras, and firewalls acting as SOCKS5 relays is a valuable commodity; operators can use it themselves to obscure attack traffic, or sell access to other criminals looking for residential or enterprise IP addresses that don’t trigger geographic blocks.
“Unlike typical botnet commands that focus on downloading payloads or launching attacks, the !socks module turns an infected host into a SOCKS5 proxy that the operator can use as a network relay. It supports two operating modes. In direct mode, it opens a SOCKS5 listener on the infected host on the default TCP port 1080 and waits for incoming client connections. The implementation first attempts to create a dual-stack IPv6 listener and falls back to IPv4 if that fails. Each accepted client is then passed to the session handler for proxying.” continues the report. “The botnet also implements a reverse relay mode. Instead of exposing a listening port, the bot establishes an outbound encrypted connection to an operator-specified relay server. This persistent control channel listens for commands such as RELAY_NEW:<session_id>, which indicate that a new proxy session should be created.”
After establishing C2 contact, the bot accepts commands covering the full post-compromise toolkit: file upload and download, interactive shell access, persistence installation, binary updates, HTTP Basic Auth and Cookie header interception, DDoS over DNS, TCP, and UDP, and the HTTP exploit dispatcher.
The credential sniffer intercepts authentication headers in transit, so any HTTP Basic Auth credentials passing through an infected device can be captured without any additional effort from the operator. If you’re still running devices with unpatched firmware from the CVE list above, or if any of your edge hardware is using default SSH credentials, Evooo1Bot is already scanning for you.
“Beyond traditional botnet functionality, it features encrypted C2 communications, multiple layers of string obfuscation using AES-256-CTR, ChaCha20, and XOR-based key derivation, as well as a 28-command remote administration interface.” concludes the report. “These capabilities place Evooo1Bot well beyond the technical baseline of conventional Mirai-derived malware.”
The Dysphoria botnet has expanded into a major Internet of Things threat, with a new Shadowserver Special Report identifying approximately 296,000 compromised devices. The campaign targets exposed routers, gateways, IP cameras and other embedded Linux systems, converting poorly secured equipment into a distributed platform for DDoS attacks and increasingly, residential proxy and relay operations. Dysphoria’s […]
Attackers breached a Polish CHP plant through a Fortinet device and private APN, reaching PLCs and disrupting turbine and water treatment systems.
Poland’s CERT has described a second attack on the country’s energy sector, and this one matters for a simple reason: it shows how an ordinary-looking network design can turn into a route into OT. The target was a smaller combined heat and power plant feeding heat to around 50,000 residents, and the attackers used a private APN as the path in, something CERT says it saw for the first time in this incident.
The report says the intrusion began at a wind farm, where the attackers hit a Fortinet VPN and firewall device exposed to the internet.
From there they found a Teltonika cellular router, used SSH to build a tunnel, reached the private APN managed by the distribution system operator, and then moved toward the plant’s OT network.
“On 29 December 2025, coordinated attacks targeted the energy sector in Poland, including 30 renewable energy facilities and a large combined heat and power (CHP) plant. These attacks were described in detail in the report published on 30 January 2026*. At the same time, another incident occurred at a smaller CHP plant supplying heat to 50,000 residents.” reads the report published by Poland’s CERT. “The analysis of this incident took more than three months to complete, which is why it was not included in the initial report. To the best of our knowledge, the attack vector used in this case has not previously been observed in any known incidents.”
Once inside, the attackers found a Wago PLC at the CHP plant and used SSH access on that controller to reach the operational network. After roughly a week of reconnaissance, they connected to Siemens PLCs, switched them to stop mode, and set a password that blocked operators from changing the controllers’ state and control logic.
That is where the physical impact started. The steam turbine and water treatment system shut down, the cogeneration process broke, and the plant lost service continuity for a while, though staff restored the affected systems quickly enough to avoid a heat or electricity outage.
“The attacker then damaged the WAGO controller that had been used as a gateway into the network by corrupting its partition table, preventing it from being read by the device. In an attempt to restore the controller, the affected entity performed a factory reset; however, this did not repair the partition table and the device remained unable to boot.” continues the report. “No valuable logs could be recovered from the device during the investigation.”
The report also shows how messy real intrusions get once the attacker is inside the control environment. Moxa serial device servers and Moxa network switches were reconfigured to block legitimate access, ABB and Schneider Electric variable frequency drives were touched as well, and some connection attempts failed or were only partially successful.
“An important aspect of this architecture is that DSOs require all communication between the DSO’s ICT network and the RTU to take place over a serial protocol, in this case DNP3.0. At the compromised facility, a Teltonika RUTX50 router was used, and the DSO’s requirements were met. However, no requirements had been defined regarding the handling of the cellular router’s administrative interface.” continues the report. “As a result, the router was configured with two physical interfaces: a serial link connected to the RTU and a second interface, Ethernet, connected to a VLAN managed by the central firewall that had been compromised by the attacker.”
That is the uncomfortable part. The attackers did not need some exotic zero-day chain to do damage. They used a reachable edge device, a private APN that was already in the path, weak or exposed access points, and enough patience to move from reconnaissance to disruption.
CERT notes that the attackers damaged some devices while trying to cover their tracks, and in the WAGO case the controller could not be brought back by a simple reset. The agency also says this kind of private APN setup is not rare, which is exactly why the finding matters beyond Poland.
“As maintenance work was being carried out at the facility, the entity initially assumed that the process interruption had been caused by an error made by the contractor’s engineers and reported the event for informational purposes only.” continues the report. “However, due to its awareness of other similar events, CERT Polska initiated incident handling under the assumption that the event may have resulted from a cyberattack. Further analysis confirmed this hypothesis.”
The practical lesson is not subtle. Private APNs, edge routers and OT gateways need the same discipline as any other exposed infrastructure, because once an attacker can pivot from a field device into control systems, the difference between “maintenance” and “incident” gets very thin.
“Based on our analysis of the malware and associated TTPs, we attribute the attack to the Russia-aligned Sandworm APT with medium confidence due to a strong overlap with numerous previous Sandworm wiper activity we analyzed,” said ESET researchers. “We’re not aware of any successful disruption occurring as a result of this attack,” ESET researchers said.
ESET researchers uncovered DynoWiper, a destructive wiper malware used in an attempted cyberattack against Poland’s energy sector on December 29, 2025. While no successful disruption has been confirmed, the malware’s architecture shows clear destructive intent. ESET attributes the operation with medium confidence to the Russia-aligned Sandworm APT group, citing strong overlaps in tactics, techniques, and behavior with previous Sandworm-linked wiper attacks analyzed by the team.
The attempted attack occurred during peak winter demand and coincided with the 10-year anniversary of Sandworm’s 2015 cyberattack on Ukraine’s power grid, the first malware-induced blackout that left around 230,000 people without electricity. ESET tracks the DynoWiper malware as Win32/KillFiles.NMO. Subscribers to ESET’s private Threat Intelligence APT reports have already received further technical details and indicators of compromise to aid rapid detection and incident response. The cybersecurity firm also shared an associated IoC hash for defensive use.
The statistics in this report are based on detection verdicts returned by Kaspersky products unless otherwise stated. The information was provided by Kaspersky users who consented to sharing statistical data.
Quarterly figures
In Q2 2026:
Kaspersky products blocked nearly 400 million attacks that originated with various online resources.
Web Anti-Virus responded to 52 million unique links.
File Anti-Virus blocked more than 16 million malicious and potentially unwanted objects.
There were 2538 new ransomware variants discovered.
More than 71,000 users experienced ransomware attacks.
15% of all ransomware victims whose data was published on threat actors’ data leak sites (DLS) were attacked by Qilin.
More than 213,000 users were targeted by miners.
Ransomware
Quarterly trends and highlights
Threat actor disruption
Microsoft has dismantled an illicit malware-signing service used by ransomware operators. Microsoft’s Digital Crimes Unit has shut down a malware-signing-as-a-service (MSaaS) operation run by the threat group Fox Tempest. The illicit service abused the Microsoft Artifact Signing platform to generate digital signature certificates for malicious software. Malware signed by these certificates was observed in campaigns conducted by such ransomware groups as Rhysida, Akira, INC, Qilin, and BlackByte. The service was also leveraged by operators of the Oyster loader as well as the Lumma and Vidar infostealers. To disrupt the operation, Microsoft seized the domain used by the MSaaS platform, revoked all associated certificates, and disabled the related accounts. Additionally, the company filed a lawsuit against Fox Tempest.
Vulnerabilities and attacks
CISA has confirmed that a Windows vulnerability known as BlueHammer is actively being exploited in ransomware attacks. On April 22, the agency updated its Known Exploited Vulnerabilities (KEV) catalog to note the ongoing ransomware exploitation of CVE-2026-33825. The local privilege escalation flaw in Microsoft Defender was originally disclosed earlier in April. Although Microsoft released a fix on April 14, unpatched systems remain vulnerable. CISA did not disclose further details or attribute the attacks to specific threat groups.
Check Point has linked zero-day exploitation of CVE-2026-50751 to the Qilin ransomware group. The critical vulnerability affects Check Point Remote Access VPN and Mobile Access. Attackers began exploiting the flaw as a zero-day on May 7, with activity spiking sharply in early June. While several dozen organizations have been targeted, at least one incident has been definitively tied to Qilin. Check Point also disclosed a related certificate validation flaw (CVE-2026-50752) that affects site-to-site VPN connections relying on the legacy IKEv1 key exchange protocol.
Researchers assess with high confidence that the PayoutsKing group is leveraging the legitimate QEMU emulator to deploy hidden, Alpine Linux-based virtual machines on compromised hosts. Because security solutions often lack visibility inside virtualized environments, the threat actors use this technique to evade detection. Inside the VM image, the operators deploy various tools — such as credential theft software — and configure the virtual machine as a backdoor managed via a reverse SSH tunnel to their command-and-control infrastructure. While the technique is not new, and we’ve detailed it before, it remains relatively rare in ransomware attacks.
The most prolific groups
This section highlights the most prolific ransomware gangs by number of victims added to each group’s DLS. Qilin reclaimed the top spot (accounting for 14.57% of total listings) after placing second last quarter. It is followed by the Akira ransomware (7.80%) and the DragonForce RaaS group (6.88%).
Number of each group’s victims according to its DLS as a percentage of all groups’ victims published on all the DLSs under review during the reporting period (download)
Number of new ransomware variants
In Q2, Kaspersky solutions detected four new ransomware families and 2538 new modifications. This signals a continued stabilization following spikes seen in Q1 and Q4 of last year.
Number of new ransomware modifications, Q2 2025 — Q2 2026 (download)
Number of users attacked by ransomware Trojans
Our solutions protected a total of 71,860 unique users from ransomware during Q2. Ransomware activity peaked in April, with 31,206 targeted users recorded during that month.
Number of unique users attacked by ransomware Trojans, Q2 2026 (download)
TOP 10 countries and territories attacked by ransomware Trojans
Country/territory*
%**
1
South Korea
0.87
2
Pakistan
0.76
3
China
0.71
4
Libya
0.49
5
Tajikistan
0.46
6
Turkmenistan
0.38
7
Cameroon
0.38
8
Indonesia
0.36
9
Bangladesh
0.36
10
Mozambique
0.34
* Excluded are countries and territories with relatively few (under 50,000) Kaspersky users.
** Unique users whose computers were attacked by ransomware Trojans as a percentage of all unique users of Kaspersky products in the country/territory.
* Unique Kaspersky users attacked by the specific ransomware Trojan family as a percentage of all unique users attacked by this type of threat.
Miners
Number of new miner variants
In Q2 2026, Kaspersky solutions detected 6067 new miner variants, almost twice the number for the previous reporting period.
Number of new miner modifications, Q2 2026 (download)
Number of users attacked by miners
In Q2, we detected attacks using miner programs on the computers of 213,003 unique Kaspersky users worldwide.
Number of unique users attacked by miners, Q2 2026 (download)
TOP 10 countries and territories attacked by miners
Country/territory*
%**
1
Mali
1.56
2
Senegal
1.54
3
Tanzania
1.32
4
Panama
1.04
5
Bangladesh
1.03
6
Ethiopia
0.87
7
Costa Rica
0.67
8
Bolivia
0.67
9
Côte d’Ivoire
0.65
10
Kazakhstan
0.62
* Excluded are countries and territories with relatively few (under 50,000) Kaspersky users.
** Unique users whose computers were attacked by miners as a percentage of all unique users of Kaspersky products in the country/territory.
Attacks on macOS
Quarterly highlights
In April, Aikido researchers reported a new attack by the GlassWorm stealer, which was distributed via malicious IDE extensions on the Open VSX Registry. The payload operated by installing a secondary malicious extension across all installed IDE environments on the host machine. Ultimately, this second-stage implant exfiltrated crypto wallet data, environment variables, and other secrets. It also installed a RAT on the infected device.
In May, Socket researchers uncovered a supply chain compromise involving the popular npm package art-template. As a result of the breach, the weaponized package injected the Coruna exploit kit into web applications it was used to build. Coruna targets iOS devices.
In June, Palo Alto Networks’ Unit 42 discovered FlutterShell, a new backdoor family that targets macOS devices. Developed with the Flutter framework, the malware leverages the WebView engine to load web pages that contain malicious JavaScript. On the client side, the backdoor registers bridge functions invoked by the loaded JavaScript that allow threat actors to execute arbitrary payloads on the victim’s device. Notably, the malicious applications successfully passed Apple notarization. Although the specific samples analyzed functioned primarily as adware, the underlying architecture permits the delivery of far more sophisticated malicious payloads.
TOP 20 threats to macOS
* Unique users who encountered this malware as a percentage of all attacked users of Kaspersky security solutions for macOS (download)
* Data for the previous quarter may differ slightly from previously published data due to some verdicts being retrospectively revised.
Detections of PasivRobber spyware continued their downward trend. Meanwhile, adware and traffic-routing utilities (categorized as NetTool) rose to the top of the rankings. Additionally, Q2 saw a noticeable spike in detections for the DirtyCow exploit frequently leveraged for iPhone jailbreaking.
TOP 10 countries and territories by share of attacked users
Country/territory
%* Q1 2026
%* Q2 2026
Brazil
1.13
1.13
China
1.04
1.28
Hong Kong
0.92
0.49
Singapore
0.85
0.19
France
0.62
1.18
Mexico
0.43
0.72
India
0.41
0.42
Thailand
0.40
0.24
Germany
0.33
0.71
The Netherlands
0.31
0.62
* Unique users who encountered threats to macOS as a percentage of all unique Kaspersky users in the country/territory.
IoT threat statistics
This section presents statistics on attacks targeting Kaspersky IoT honeypots. The geographic data on attack sources is based on the IP addresses of attacking devices.
In Q2 2026, the breakdown of attacking devices and sessions that targeted Kaspersky honeypots by protocol was as follows:
Distribution of attacked services by number of unique IP addresses of attacking devices (download)
The share of SSH attacks saw a slight uptick compared to the previous quarter.
Distribution of cybercriminal sessions in Kaspersky honeypots (download)
TOP 10 threats delivered to IoT devices
Share of each threat delivered to an infected device as a result of a successful attack, out of the total number of threats delivered (download)
As is typically the case, Mirai botnet variants continue to dominate the IoT threat landscape. Activity of another prominent botnet, Prometei, also saw an increase.
Attacks on IoT honeypots
the Netherlands, Germany, and The United States accounted for the highest proportions of SSH-based attacks during this period. While the top three countries remained the same as last quarter, their relative rankings shifted.
Country/territory
Q1 2026
Q2 2026
The Netherlands
17.57%
21.18%
Germany
10.34%
16.73%
United States
23.74%
6.76%
Bulgaria
1.10%
5.50%
Sweden
2.09%
4.93%
Panama
6.34%
4.67%
Luxembourg
0.16%
4.62%
Romania
5.82%
4.06%
Vietnam
3.50%
3.91%
India
6.05%
2.78%
The percentage of Telnet-based attacks originating from Pakistan continued to climb, knocking China down to second place.
Country/territory
Q1 2026
Q2 2026
Pakistan
27.31%
36.60%
China
39.54%
35.62%
Russian Federation
8.25%
8.75%
India
4.66%
4.19%
Brazil
3.30%
3.34%
United States
0.45%
3.03%
Indonesia
6.71%
1.52%
Philippines
0.36%
0.95%
France
0.17%
0.84%
Thailand
0.55%
0.66%
Attacks via web resources
The statistics in this section are based on detection verdicts by Web Anti-Virus, which protects users when suspicious objects are downloaded from malicious or infected web pages. These malicious pages are purposefully created by cybercriminals. Websites that host user-generated content, such as message boards, as well as compromised legitimate sites, can become infected.
TOP 10 countries and territories that served as sources of web-based attacks
The following statistics show the distribution by country/territory of the sources of internet attacks blocked by Kaspersky products on user computers (web pages redirecting to exploits, sites containing exploits and other malware, botnet C&C centers, and so on). One or more web-based attacks could originate from each unique host.
To determine the geographic source of web attacks, we matched the domain name with the real IP address where the domain is hosted, then identified the geographic location of that IP address (GeoIP).
In Q2 2026, Kaspersky solutions blocked 399,312,961 attacks launched from internet resources worldwide. Web Anti-Virus was triggered by 52,850,592 unique URLs.
Web-based attacks by country/territory, Q1 2026 (download)
Countries and territories where users faced the greatest risk of online infection
To assess the risk of malware infection via the internet for users’ computers in different countries and territories, we calculated the share of Kaspersky users in each location on whose computers Web Anti-Virus was triggered during the reporting period. The resulting data provides an indication of the aggressiveness of the environment in which computers operate in different countries and territories.
This ranked list includes only attacks by malicious objects classified as Malware. Our calculations leave out Web Anti-Virus detections of potentially dangerous or unwanted programs, such as RiskTool or adware.
Country/territory*
%**
1
Bangladesh
11.71
2
India
7.40
3
Tajikistan
7.13
4
Venezuela
7.05
5
New Zealand
6.58
6
Vietnam
6.34
7
Taiwan
6.28
8
Belgium
6.24
9
France
5.97
10
Hungary
5.92
11
Nepal
5.91
12
Portugal
5.86
13
Italy
5.77
14
Costa Rica
5.72
15
Canada
5.65
16
Qatar
5.61
17
Dominican Republic
5.52
18
Palestine
5.48
19
Greece
5.47
20
UAE
5.43
* Excluded are countries and territories with relatively few (under 10,000) Kaspersky product users.
** Unique users targeted by web-based Malware attacks as a percentage of all unique users of Kaspersky products in the country/territory.
On average during the quarter, 4.54% of users’ computers worldwide were subjected to at least one Malware web attack.
Local threats
Statistics on local infections of user computers are an important indicator. They include objects that penetrated the target computer by infecting files or removable media, or initially made their way onto the computer in non-open form. Examples of the latter are programs in complex installers and encrypted files.
Data in this section is based on analyzing statistics produced by anti-virus scans of files on the hard drive at the moment they were created or accessed, and the results of scanning removable storage media. The statistics are based on detection verdicts from the On-Access Scan (OAS) and On-Demand Scan (ODS) modules of File Anti-Virus and include detections of malicious programs located on user computers or removable media connected to the computers, such as flash drives, camera memory cards, phones, or external hard drives.
In Q2 2026, our File Anti-Virus detected 16,986,351 malicious and potentially unwanted objects.
Countries and territories where users faced the highest risk of local infection
For each country and territory, we calculated the percentage of Kaspersky users whose computers had the File Anti-Virus triggered at least once during the reporting period. These statistics reflect the level of personal computer infection in different countries.
Note that this ranked list includes only attacks by malicious objects classified as Malware. Our calculations leave out File Anti-Virus detections of potentially dangerous or unwanted programs, such as RiskTool or adware.
Country/territory*
%**
1
Turkmenistan
46.38
2
Cuba
29.70
3
Tajikistan
28.46
4
Afghanistan
28.19
5
Yemen
27.85
6
Burundi
26.82
7
Mozambique
25.01
8
Republic of the Congo
24.88
9
Syria
23.17
10
Uzbekistan
22.49
11
China
21.92
12
Nicaragua
21.60
13
Cameroon
21.47
14
Bangladesh
20.43
15
Democratic Republic of the Congo
20.25
16
Algeria
19.78
17
Uganda
19.48
18
Ethiopia
18.57
19
Tanzania
18.54
20
Mali
18.53
* Excluded are countries and territories with relatively few (under 10,000) Kaspersky users.
** Unique users on whose computers Malware local threats were blocked, as a percentage of all unique users of Kaspersky products in the country/territory.
On average worldwide, Malware local threats were detected at least once on 10.93% of users’ computers during Q2.
Lina K., a co-worker, recently shared a firsthand account of how bots are adding League of Legends players via the Riot client friends list immediately after a match ends, striking up a flirty conversation, and eventually pushing an OnlyFans link. The pattern lines up with a wave of complaints that have piled up on Reddit and Facebook gaming communities over the past several months, and it fits into a broader trend of AI-assisted social engineering that has moved from dating apps straight into game clients.
The pattern
The scheme reported by multiple League of Legends players follows a near-identical script. A friend request lands in the Riot client within moments of a match ending, from an account whose name does not match anyone from that game. The message opens with generic flattery like “you played really well last game” or “I liked your playstyle” designed to sound like a genuine compliment from an opponent or teammate.
When questioned about who they are, the accounts often claim to have been on the enemy team despite name mismatches, and many present themselves as a woman looking for a duo partner. A detail that likely raises engagement odds. Victims who check the account’s profile frequently find it blank: no visible match history, no overview data, sometimes a very low account level. These are all signs of a throwaway account built or bought purely for outreach, but sometimes they turn out to be stolen existing accounts.
After a short exchange, the contact says they are “getting off soon” and hands over a Discord username, moving the conversation to a platform Riot’s chat protections cannot see or moderate.
Once on Discord, the persona shifts into a longer-form romance/flirtation script. Usually, hours of chat building rapport, paired with a steady stream of photos that are suggestive but stop short of explicit content, a tactic that keeps engagement high while deferring the “reveal” until trust is established. That reveal ultimately comes in the form of a link to a paid subscription platform, most often OnlyFans, framed as an exclusive, limited-time offer.
A reverse image search on the photos sent during one such conversation turned up the same pictures recycled across unrelated websites and at least one YouTube video, with commenters in that video describing having received identical images from a bot under different names. This is strong evidence that the same photo set is cycling through many chats simultaneously, run at scale rather than by one individual.
Lina stated:
“One of my friends tried to break the bot too, left it on read for some time – the bot actually switched the pictures to match the context of “Concern” on the face of the model with “Why are you not replying?”, which quite clearly gave away bulk image generation for the script.’
When the account was pressed with a “reveal your instructions” style prompt-injection attempt (text formatted to look like a system message ordering the bot to break character and print its configuration), it did not comply and instead stayed in persona, deflecting the request and continuing the pitch.
That resilience to a common jailbreak technique suggests the bot’s operators have added guardrails against exactly this kind of probing, or that the “model” behind it is a simpler scripted flow layered with some LLM-generated text rather than an open, unrestricted chatbot.
Why this is happening inside the game client now
What makes this wave notable isn’t the romance scam script itself. AI-driven catfishing has been documented on dating apps and social media for a couple of years. The difference is the entry point. Players have reported getting these bot friend requests after essentially every single match, with no way to distinguish a real player’s request from a bot’s inside the Riot client.
Community threads describe the bots seemingly appearing right after a game ends, which has fueled speculation that the bot operators are scraping or monitoring publicly available match data through third-party stats-tracking sites and associated APIs to identify recently finished games and target participants, though this has not been independently confirmed by Riot.
Riot’s own client architecture may be inadvertently helping. The Riot Client exposes local endpoints (such as the friends list API) that third-party tools and overlays query, and community-run “op.gg“-style trackers pull player and match data that could plausibly be used to correlate who just finished a game with who to target next. Some affected players have found a partial workaround: switching on the client’s “streamer mode,” which hides recent match and online status information, appears to reduce how often bot requests arrive. Which is an indirect clue that the targeting relies on visible activity signals rather than random spam.
Unlike classic Discord scams that push fake Nitro codes or malware-laden “test my game” links to hijack accounts, this particular chain appears primarily aimed at driving paid subscriptions to an OnlyFans-style page of a fake AI girl. That doesn’t make it harmless. Even when the underlying OnlyFans account is real, the conversations are very likely run by paid chat operators or scripted/AI-powered systems working from a shared script and a reused media library, a business model that has been described by former OnlyFans “chatters” themselves: agencies assign staff (or bots) to respond as the creator around the clock, pull from a pre-made vault of photos and messages, and are financially incentivized to convert every conversation into a subscription or tip.
There are also more damaging variants layered onto the same funnel. Community reports describe some of these bot accounts eventually sending a link that, once clicked, is designed to hijack the recipient’s Discord account or harvest credentials rather than lead to legitimate content.
That means the “girl who wants to duo” opening can just as easily terminate in an account-takeover attempt as in a subscription upsell. Because the funnel starts with a low-cost, disposable Riot account and migrates the target to Discord within minutes, the League client friend request functions purely as a first-contact filter: cheap to generate, easy to discard after a single use, and outside the reach of Riot’s in-game reporting tools once the conversation moves off-platform.
How to stay safe
Recognizing these scams is the best way to protect yourself. But there is more you can do:
Treat any Riot client friend request from an unrecognized name as suspicious by default, especially one that arrives seconds after a match ends—check whether the account actually appeared in your last game before accepting anything.
Enable streamer mode or equivalent privacy settings in the Riot client to limit what activity and match data outside parties can see, which several affected players found reduced the frequency of these requests.
Be skeptical of anyone who quickly steers the conversation off-platform to Discord, especially if they cite being unavailable (“gotta go soon, here’s my Discord”) as the reason—this is a deliberate move to a channel with less moderation and no shared match context to verify identity.
Run a reverse image search (Google Images, TinEye, or a dedicated tool) on any profile or “personal” photos sent early in a conversation; recycled images across unrelated sites or forums are one of the most reliable tells of a bot or catfishing operation.
Watch for AI-typical conversation patterns: responses that feel scripted, arrive instantly regardless of time of day, are grammatically flawless but emotionally generic, or that consistently dodge voice/video calls.
Never send money, gift cards, cryptocurrency, or payment details to someone you met exclusively through in-game or Discord contact, no matter how convincing the rapport feels—legitimate connections do not require urgent financial “help” or exclusive subscription purchases within hours of meeting.
Do not click links sent by unfamiliar contacts, even ones framed as harmless subscription pages, game invites, or file downloads; some variants of this scheme are documented to lead to credential-stealing or account-hijacking pages rather than legitimate content.
Lock down Discord’s privacy settings (restrict who can DM you and send friend requests) and enable multi-factor authentication, since a compromised Discord account is often used to relaunch the same scam against the victim’s own friend list.
Report suspicious Riot client accounts to Riot Support and suspicious Discord accounts/servers to Discord Trust & Safety; reporting does not remove the account instantly but it feeds the pattern data that platforms use to detect and ban clusters of bot accounts.
If a bot or scripted persona pushes back convincingly against attempts to “break” it (e.g., ignoring prompt-injection or jailbreak-style messages designed to expose it as an AI), treat that resilience itself as a red flag rather than reassurance—a well-guarded script is not the same as a genuine person.
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After attacks hit 30+ Minnesota water systems, CISA urged utilities to remove internet-exposed PLCs and strengthen OT security.
Between Sunday and Monday, July 26 and 27, a coordinated cyberattack hit operational technology (OT) systems at more than 30 community water utilities across the state, according to Minnesota IT Services (MNIT).
“A coordinated cyberattack targeted operational technology at more than 30 Minnesota community water systems on July 26 and 27. Minnesota IT Services (MNIT) immediately activated the state’s cybersecurity incident response capabilities.” reads the statement published by MNIT. “MNIT continues to collaborate with federal, state, local, Tribal, and private-sector partners to investigate the attack, support affected communities, and strengthen the security of Minnesota’s critical infrastructure.”
The agency activated its statewide incident response the moment it learned of the attack, and it’s still active as of this week.
Four cities went public with details: Braham, Maple Plain, Plymouth, and South St. Paul. Braham took the hardest hit of the group; the town of about 1,700 people had its water plant knocked offline entirely after attackers disabled the computerized controls running its well and treatment systems.
State and federal investigators are working to determine attribution, but the timing is hard to ignore: the attacks came four days after CISA updated its advisory on Iranian-affiliated actors targeting programmable logic controllers across US critical infrastructure. No formal attribution has been made, but Tenable researchers assess the operational pattern is consistent with CyberAv3ngers, an Iran-linked group formally tied to the IRGC.
“Federal and state officials have not publicly attributed the Minnesota attacks to any specific actor. However, the operational pattern is consistent with the CyberAv3ngers threat ecosystem, a state-directed group the U.S. government has formally attributed to Iran’s Islamic Revolutionary Guard Corps Cyber-Electronic Command.” reported Tenable.
CISA now warns of a surge in attacks targeting internet-exposed PLCs at water utilities. Attackers have changed passwords and IP addresses to lock out operators, causing boil water notices and forcing some facilities to switch to manual operations. The US agency urges organizations to remove publicly accessible PLCs and other OT systems from the internet immediately.
“CISA is currently observing a significant increase in cyber threat actors targeting programmable logic controllers (PLCs) in the Water and Wastewater Systems (WWS) Sector. CISA urges critical infrastructure owners, operators, and integrators to remove publicly exposed PLCs and other operational technology (OT) from the internet as soon as possible.” reads CISA’s alert. “Threat actors targeting exposed PLCs have modified passwords to lock out operators and disconnected the PLCs by changing their IP addresses. This activity has resulted in boil water notices and sustained manual operations.”
The FBI confirmed that utility companies in at least seven states have reported PLC-related incidents. The attacks aren’t sophisticated in the traditional sense, after remotely accessing internet-facing devices, the actors changed IP addresses and passwords, resulting in loss of monitoring and control functionality. That’s it. Default or weak credentials on internet-exposed hardware, and suddenly operators are locked out of their own systems.
CVE-2021-22681 is a critical Rockwell Automation vulnerability (CVSS 9.8) that remained unexploited for years because industrial control systems are difficult to patch without disrupting essential services. Since March 2026, however, Iranian-affiliated threat actors have actively exploited the flaw, prompting CISA to add it to its Known Exploited Vulnerabilities catalog. Rockwell has confirmed that no security patch is available, making network isolation and other compensating controls essential.
That last sentence is worth sitting with. A CVSS 9.8 vulnerability in controllers that run public water infrastructure, no patch, actively exploited. The compensating control is network isolation, which is exactly what CISA is now urgently requesting.
“These threat actors are targeting water entities of all sizes. Even water organizations with mature cybersecurity processes should validate their external connections, as this targeting activity includes cellular modems installed by operators, vendors, or system integrators that may not be documented or included in routine attack surface scans.” continues the alert. “OT assets exposed to the internet have an increased risk of defacement, configuration changes, operational disruptions, and, in severe cases, physical damage.”
A July 2026 update to CISA’s advisory found that attacks exploiting internet-exposed PLCs have expanded beyond Rockwell Automation to include Schneider Electric and Siemens devices. The advisory also documents attackers stealing PLC project files for the first time and adds new guidance to detect tampering with reusable code modules embedded in industrial control programs.
Exfiltrating project files means the attacker is taking the engineering logic of the plant, the actual programmed behavior of the industrial process, and studying it offline. That’s reconnaissance for a more targeted future attack, not just disruption for its own sake.
The Minnesota attacks resulted in boil water notices and sustained manual operations at affected utilities. Drinking water remained safe in most cases, and contingency procedures held. But the affected cities include Maple Plain, Braham, South St. Paul, and Plymouthm not isolated rural facilities, but communities of real scale. CyberAv3ngers is known for targeting small water and municipal facilities, which experts believe are among the lowest-hanging fruit in US critical infrastructure. Many small and rural facilities lack dedicated cybersecurity resources. That’s the point. These attacks aren’t about technical sophistication. They’re about finding the organizations with the least capacity to defend themselves and demonstrating that the capability to disrupt public services exists and can be exercised.
CISA’s alert specifically notes that even mature organizations should validate their external connections, because the targeting includes cellular modems installed by operators, vendors, or system integrators that may not appear in routine network scans. A modem installed by a contractor for remote access and never documented in the asset inventory is still an attack surface. The practical checklist is short: get PLCs off the internet, segment OT networks from IT networks, change default credentials, and audit every remote access path, including the ones you didn’t authorize.
“CISA recommends organizations implement the following mitigations:
Disconnect the PLC from the internet. Remote access for operational purposes should go through a VPN or gateway device, not directly to the PLC.
Enable password protection and change default passwords.
Allowlist IPs to only allow remote access from known engineering laptops or other critical OT assets.
After disconnecting PLCs from the internet, operators should ensure they have a known clean backup of the PLC image in case they are locked out by a modified password.” concludes CISA. Note: Owners, operators, and integrators of Rockwell Automation MicroLogix 1400 PLCs should see Rockwell Automation’s IMPORTANT NOTICE: Restoring Access to a MicroLogix 1400 Controller When the Password Is Unknown for guidance addressing this activity.”
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1400 Controller When the Password Is Unknown
