Ukrainian ransomware crook Artem Stryzhak has been sentenced to 70 months in the slammer by a New York federal court for his role as an affiliate of the Nefilim and Hive ransomware gangs. Prosecutors believe the cybercriminal began working with Nefilim in or around June 2021, while living in Barcelona, Spain. The Nefilim ransomware-as-a-service (RaaS) operation was known for targeting wealthy companies, with its operators encouraging affiliates to pursue businesses capable of paying substantial ransom demands. One of Nefilim's most high-profile attacks was on Australian logistics giant Toll Group in 2020, encrypting its files roughly three months after it suffered a separate Mailto ransomware attack. Court documents [PDF] state that Stryzhak agreed with alleged Nefilim boss Volodymyr Tymoshchuk, who remains at large, to pay the ransomware crew a 20 percent cut of the ransom proceeds he collected. Tymoshchuk told Stryzhak that his preference was for attacks to target companies based in the US, Canada, and Australia that turn over more than $100 million annually. This guidance was soon tweaked to encourage targeting companies in the same regions with more than $200 million in annual revenue. Prosecutors claim that around the time Stryzhak joined forces with Nefilim, he also signed up to the Hive ransomware operation as "one of its earliest affiliates," and used its platform to attack approximately seven victims. Hive's operators claimed they targeted circa 1,500 victims worldwide between June 2021 and January 2023. According to separate court documents [PDF], Hive's victims included a law firm and an Ohio hospital, which paid approximately $1.7 million in Bitcoin after the gang initially demanded $2 million during the COVID-19 pandemic. Before its infrastructure was seized in an international law enforcement operation in January 2023, Hive was known for attacking healthcare facilities during the COVID-19 pandemic, as well as being one of the ransomware groups that battered Costa Rica in 2022. Brett Leatherman, assistant director at the FBI’s cyber branch, described Stryzhak as a “prolific cybercriminal” who played a role in groups that were responsible for more than $100 million in victim damages. “Today’s sentence reflects the seriousness of Stryzhak’s crimes and demonstrates the FBI’s global reach and extensive network of international partners,” he said. “Multiple field offices contributed to this investigation, and our work does not end here. We will continue to leverage every tool at our disposal to track down Stryzhak’s co-conspirators and hold them accountable, including Volodymyr Viktorovych Tymoshchuk.” Stryzhak was arrested by Spanish police in June 2024 before being extradited to the US in April 2025. In announcing Stryzhak's sentencing, the Justice Department took the opportunity to remind the public that rewards totaling up to $11 million are available for qualifying information about alleged Nefilim operator Volodymyr Tymoshchuk and other key ransomware suspects. ®

Cisco has open sourced a behavior detection engine that watches AI agents, to help security teams prevent rogue agents from going off the rails like they did with the Hugging Face hack – or worse. It’s called Project Quarry, and it aims to provide a “shared language” for evaluating agent behavior, along the lines of what Snort, which Cisco also maintains, did for detecting malicious network traffic and what YARA did for rule-based malware identification. Most detection tools rely on specific interactions with an AI model or agent. Did it attempt prompt injection? Or did the agent call an attack tool? “But what is missing is the entire context under which something may occur,” Amy Chang, head of AI threat and security research at Cisco, said in an exclusive interview with The Register. She likened this to credit card fraud detection. Without context, individual transactions such as a small test charge or a single purchase in a location far away from a card-holder's usual location may not raise any flags. “And then you try again,” making another fraudulent purchase, “and that went through, too. So now I’m gonna buy the PS5,” Chang said. “Those are the things that Quarry addresses by taking into consideration the entire agent session,” she explained. “One tool call may seem in-scope until you realize that that next step is taking that information and sending it to an attacker-controlled inbox or server.” Even data theft is a sequence and not a single agentic action. Agentic AI security firm Invariant Labs demonstrated this with a proof-of-concept attack against GitHub's MCP server that hijacked a user's agent via a malicious GitHub Issue, and coerced it into leaking data from private repositories. Simply reading a configuration file, or sending a request to an external endpoint may be legitimate agentic actions. However, combining the two can lead to data exfiltration – and shows “why action relationships matter,” wrote Chang and fellow Cisco researchers Adam Swanda, Ravikumar Balakrishnan, and Konstantin Berlin in a blog post about Quarry shared with The Register ahead of publication “A policy can produce a finding when the trace shows a sensitive file read followed within a defined window by an external send,” they wrote. “The risk comes from the relationship between the two actions, so the finding should preserve evidence from both." Quarry covers single- and multi-turn large language model conversations, agents, tool use, Model Context Protocol (MCP) interactions, and multimodal inputs. In addition to the open source code itself, the project’s GitHub repository includes installation instructions, supported Python versions, plugins for Claude Code, Codex and other MCP-compatible agents, configuration examples, rule-writing guidance, and a rule starter pack. For instance, with the rule pack, “If a base-64 encoded malware is somewhere in the tool call, that would result in a block,” Chang said. The rule format looks similar to a YARA or Snort rule, with a header that details the traffic to examine, content to match, and metadata for tracking the rule. Here’s a Quarry rule that flags an agent that reads a credentials file: While the Cisco Ai researchers have not run Quarry against data describing the OpenAI-Hugging Face incident, they suggest that if the intrusion had been read as a complete, step-by-step record of a single session, there were several points where the AI agents’ steps would have given a Quarry rule something to act on and flag for humans. For example, Quarry would probably have flagged internet access from a sandbox. “The rule can flag specific tool calls that reach an external server asset that wasn’t in the task’s allow list,” Chang said. “Another one would be credentials found and used somewhere else.” According to OpenAI’s technical report about the Hugging Face intrusion, this is exactly what happened on July 10, when an agent validated 14 exposed Hugging Face tokens with write access and shared them. “The rule would flag that there was a credential in the tool result that then called an outside service, which is likely not within the parameters of what you would want to do in this case,” Chang said. “We don't want you to go and search for credentials that may have been leaked or inadvertently exposed and then utilize them to conduct a task.” The Cisco team is quick to say that rules along are not a substitute for chain-of-thought monitors, or other forms of human oversight – but they do help record a pattern that other teams can then “review, test, and apply to their own agents,” they wrote. Herein also lies the benefit of open source, and a collective approach to defending against adversarial use of AI, Chang said. “Do we have all the answers? No,” Chang said. “We all see slices of the problem, and it’s important for us to share what we see.”®

UK domain registrar 123 Reg (no relation – Ed) says it was the victim of an “AI-driven cyberattack” that exposed customer data. Customers began receiving their notification emails this week, informing them that their contact information, "related customer relationship data," company VAT numbers, and "product information from an application programming interface (API)" were compromised. A company spokesperson elaborated, saying this means that names, phone numbers, countries, language and currency preferences, account creation dates, the products on the account, and marketing preferences were affected. 123 Reg described the September 18 intrusion as "the first known AI-driven cyberattack against our company," and told The Register that early signs point toward a China-nexus attacker. "Our investigation identified IP addresses that we assessed to be the core attacker infrastructure, which were hosted in China and Singapore, indicating a strong Chinese nexus," the spokesperson said.  "Our investigation further identified AI cyberattack 'skills' hosted on Chinese infrastructure, including copies of skills open sourced by Anthropic and several other AI exploitation frameworks and scripts." They went on to say that many of the artefacts left behind led 123 Reg to suspect that a Chinese state-sponsored group, known for abusing Claude Code in attacks against at least 30 organizations, could be behind the break-in. There is also a suspicion that the same group that hit a number of South Korea’s financial institutions using open-source Chinese AI tool ARTEX, was behind the attack on 123 Reg too. "The TA's mirror of 'anthropic_skills,' and the account naming conventions found on the Chinese servers are consistent with preparation of this class of AI-augmented operation," the spokesperson told us.  "In addition, on October 7, 2026, CrowdStrike published CSA-261162, describing an unknown, likely Chinese-speaking actor that targeted several South Korean financial organizations starting in late September 2026, which is the same period during which we were attacked. "That actor used ARTEX, an open-source Chinese-developed agentic penetration-testing tool released in July 2026, which was also observed to be used in the attack that targeted us." The GoDaddy-owned registrar reported the attack to law enforcement agencies, brought in outside cybersecurity support, and notified the FTC, as well as the data protection authorities in the UK and EU. The company spokesperson added that it worked with Singapore-based ISPs to shut down the attacker's servers in the region, which helped disrupt the attack, in addition to "other actions by us and industry partners." 123 Reg's email to customers stated the attacker's activity "was limited to reading" customer data, although the spokesperson told us "it's possible they created copies of the information," and that this is what prompted the notification. The registrar urged customers to stay alert to the potential misuse of their data, and to treat communications appearing to come from the company with caution. "If you receive a message or call and aren't sure it's from 123 Reg, go directly to our website and log in," the email said. "We will never contact you to request your password, payment details, or verification codes by email, text, or phone. "We also strongly recommend turning on two-step verification (2SV), which helps keep your account protected even if someone tricks you into sharing your password. You can find instructions for setting up 2SV in your 123 Reg account. "We apologize for any inconvenience this may have caused." ®

An autonomous AI agent discovered four vulnerabilities in the decades-old, widely used EPICS (Experimental Physics and Industrial Control System) open source software toolkit, including a critical flaw that could allow remote attackers to execute code on systems used to control particle accelerators and fusion experiments. The bugs include a critical, 9.8-rated under CVSS v3.1 integer overflow vulnerability (CVE-2026-114595), leading to an attacker-controlled out-of-bounds heap write and potentially remote code execution; an 8.2-rated, high-severity, improper message-length validation flaw (CVE-2026-114596), causing an out-of-bounds memory write and controller-process crash; a 7.5-rated, high-severity insufficient bounds checking bug (CVE-2026-114597) that allows out-of-bounds memory reads and process crashes; and a 7.5-rated, high-severity type confusion flaw (CVE-2026-114598) that can lead to denial of service and could expose adjacent memory contents. All four affect EPICS Base, which is used to operate some of the world's largest scientific research projects and facilities, and organizations should update to version 7.0.11, which includes the fixes. “Successful exploitation of these vulnerabilities could allow an attacker to cause a denial-of-service condition, corrupt memory, disclose sensitive information, or potentially execute arbitrary code,” the US Cybersecurity and Infrastructure Security Agency (CISA) warned in a Tuesday advisory. An AI agent called Cipher independently found all four previously unknown security holes - investigating and testing the unfamiliar EPICS system, and validating the four exploits - in three hours and 49 minutes, Causal Security co-founder Shubham Raj told The Register. “The initial investigation required no human intervention, followed by one instruction authorizing deeper exploitability testing in a secure environment,” Raj said. Earlier this year, Causal Security’s Cipher, which Raj described as “a fully autonomous super hacker that can reason across the technology stack,” found multiple critical attack paths in power-grid systems used across North America and Europe, prompting an October 8 security advisory from CISA. EPICS, originally developed by Los Alamos National Laboratory and Argonne National Laboratory, is used to build and remotely control distributed Supervisory Control and Data Acquisition (SCADA) systems, connecting operators to physical devices. It’s used in around 90 major scientific, university, and industrial projects and facilities globally including Argonne National Laboratory's Advanced Photon Source and ITER's fusion reactor control system. All four of these flaws illustrate how AI agents are really good at finding vulnerabilities in industrial and operational technologies - systems and equipment that used to be able to rely on obscurity to protect them from hackers - and add to defenders' concerns that it's only a matter of time until an autonomous cyberattack shuts down critical services, like power grids or water systems. These are the types of digital intrusions that can cause physical harm. Raj points to CVE-2026-114595, the critical integer-overflow vulnerability, as an example. “It allows attacker-controlled network data to cause an out-of-bounds heap memory write, with potential for remote code execution,” he told us. “EPICS controllers sit between operators and physical equipment, handling measurements, commands, and control functions,” he continued. “Operationally: Imagine a particle accelerator in the middle of an expensive experiment. An attacker could potentially crash a controller, interrupt critical measurements or control functions, and force operators to halt the experiment. That could mean lost experimental work, significant downtime, and expensive recovery.” Plus, if an attacker was able to develop an RCE exploit, this could allow them to “take control of the affected process, manipulate readings, interfere with control functions, or disrupt the equipment connected to it,” Raj said. The prerequisite for exploiting these vulns in a real scientific facility is being able to reach the vulnerable EPICS services on a facility's control network. But this could occur if the networks weren’t sufficiently segmented, or another system had access to the vulnerable EPICS network. “Once an attacker is able to find a network, which is either misconfigured or they are able to reach, it’s pretty easy to carry out the attacks,” Raj said, adding that exploitation wouldn’t require deep OT knowledge, or understanding of how particle accelerators or fusion reactors work. “Someone with conventional exploitation skills could investigate them, and increasingly capable AI systems could help develop exploits without requiring specialized OT expertise.” Manipulating specific physical processes does require additional knowledge, he added. “But an attacker doesn't need to understand the physics of a particle accelerator to disrupt the software controlling it. Crashing critical processes or interrupting monitoring and control can already have serious operational consequences. What's changing is that attackers may no longer need years of specialized expertise just to discover these weaknesses.” ®