News threats

A beginner-level firewall for large language models (LLMs) has been developed as a project by college students. The firewall uses a two-tiered approach combining heuristic methods and a machine learning classifier to detect injection and jailbreak attempts before they reach the LLM. The implementation is based on llama-3.3 and may experience occasional delays in detection time. The project is shared publicly for feedback but does not represent a known vulnerability or active threat.

A 21-year-old individual pleaded guilty to hacking the Stark County Criminal Justice Information System (CJIS) and a multinational corporation in Connecticut. The intrusions occurred in 2023 and 2024, involving unauthorized access to sensitive personal and employee data. The attacker used custom programs and malware, employing proxy servers to conceal identity. He also destroyed digital evidence to obstruct the federal investigation. Sentencing is pending, with potential prison time estimated between 21 to 27 months due to mitigating factors.

Levi Strauss & Co. (Levi's) says that hackers used social engineering on three of its employees to gain access to and steal corporate data stored on their machines. [...]

The North Carolina Ports Authority has confirmed that a cyberattack disrupted IT systems and slowed operations at Port of Wilmington, Port of Morehead City, and Charlotte Inland Port. [...]

Agentic AI armed attackers first, but it also put real building power in defenders’ hands. Here’s what security practitioners built in two days at Black Hat USA 2026, and how the CyberAgents Exchange keeps that work compounding long after the event. Key takeaways Building defensive cybersecurity tooling no longer requires a developer. Agentic tooling drove the cost of finding and exploiting a vulnerability down to 1990s levels; it also removed the engineering barrier that kept defenders from building the automation they’ve always wanted. The unglamorous work won the room: triage, reconciliation, toil. Given two days and a requirement to publish, practitioners at SWARM developed agents for prioritization, cross-tool reconciliation, and the unglamorous toil they recognize from their own environments. All SWARM builds live on the CyberAgents Exchange , source repos attached. Every component built at SWARM is published open source with its source repository attached, so the next team facing the same problem starts from working code instead of a blank editor. Another security team already built the AI agent you need You may not realize it, but somewhere out in the ether, there’s a security team facing the same challenge as you. The only difference is they just solved the problem with agentic AI. The problem is, you have no way to find out the solution even exists. It could be an asset inventory that three systems describe in three different ways; a findings queue nobody has the hours to work; or a “critical” that a platform upgrade quietly neutralized six months ago, still sitting there waiting for someone to prove it. Somebody has already built the thing you keep meaning to build. Now it’s time we help you find it. At Black Hat USA 2026, nearly 100 registrants had the opportunity to come together for 48 hours and solve both halves of that problem: identifying a key operational pain point and building the fix. Problems like those got solved at SWARM, and the fixes are sitting on the CyberAgents Exchange right now, open source, with their source repositories attached. One team built the agent that works out which handful of fixes retires the most risk across thousands of findings. Another correlated two scanners to tell whether a flaw in the code is even reachable in the running application. A third made the case that a finding had already been mitigated, with evidence an auditor would accept. You can download and deploy any of them today. Agentic AI doesn’t just arm attackers Black Hat’s keynote stage spent this year focused on one theme: the plummeting cost of cyber offense in the agentic AI era. The price for an attacker to find and exploit a vulnerability is at lows the industry hasn’t seen since the 1990s, when a working exploit meant weeks of expert reverse engineering. Now all it takes is an afternoon and a subscription. The artisanal exploit isn’t rare anymore. True. But neither is the defender who can build. The same agentic tooling that’s arming attackers puts real building power in everyone’s hands, and that half of the story got almost no airtime. Security automation used to require the work and ongoing maintenance of skilled engineers. Now practitioners who understand the problem can build the fix. Inside the conference room at the Mandalay Bay where Tenable hosted our inaugural SWARM event, the proof of that was on every table. The winning ranking engine ships as a skill that runs on the Python standard library alone — no packages, no install step, no build pipeline. Point it at the bundled demo estate and it answers “what should we fix first?” in seconds. That’s a deliverable a practitioner can produce and a colleague can run, and two days was enough. The attacker-defender asymmetry doesn’t stem from a lack of talent or willingness. Offensive cyber capabilities compound because the tooling circulates: it’s built once, forked, passed on, or sold to the next threat actor to leverage in their attack. Meanwhile, defenders…

UNIX systems (including Linux) are well-known to record a lot of activities in many different locations. But there is one domain where they definitely lack of "modern" logging: shells. Most shells provide an historization of the typed commands through a flat file in the $HOME directory (ex: $HOME/.bash_history). They suffer of multiple problems:

OpenAI is rolling out a more reliable version of ChatGPT GPT-5.6 Sol for Plus and Pro users, while Free users are getting unlimited text chats with GPT-5.6 Luna. [...]

A recent scan identified over 4,000 Rockwell Automation and Allen-Bradley industrial controllers used in U.S. water and wastewater systems exposed directly to the internet. Despite federal warnings, many of these devices remain accessible, including 22 in cities recently targeted by cyberattacks. The exposed devices use the EtherNet/IP protocol, which can allow remote identification and potential configuration changes if improperly secured. Some devices appear vulnerable to a known remote code execution flaw disclosed in 2017 (CVE-2017-16740). The FBI and EPA have confirmed cyberattacks on water utilities in multiple states, with some attacks causing operational disruptions such as pressure loss and flooding. The exposure is attributed to mass scanning and opportunistic exploitation rather than targeted zero-day attacks. Manufacturers and federal agencies have long advised against placing such controllers on the public internet.

The Cybersecurity and Infrastructure Security Agency (CISA) released a strategic framework titled 'OSS Security Principles and Practices' to guide federal agencies in managing open source software (OSS) securely throughout its lifecycle. The framework highlights OSS benefits such as transparency, cost efficiency, and flexibility, while addressing unique risks like decentralized development and supply chain vulnerabilities. It introduces the C4 Framework to assess OSS risk across codebase, community, conduct, and configuration. The guidelines mandate rigorous source code inventories, legal reviews, and encourage contributing security fixes upstream. Special considerations for AI systems require full access to training data and pipelines to ensure security. These principles aim to strengthen supply chain risk management and can be applied beyond federal agencies.

A 26-year-old Canadian man once described as one of the most consequential cybercrime threat actors of 2024 has pleaded guilty to computer fraud and conspiracy to hack and extort more than 165 organizations that used the cloud provider Snowflake . Connor Riley Moucka , of Kitchener, Ontario, also admitted to stealing call and text history records of more than 100 million AT&T customers. A surveillance photo of Connor Riley Moucka, a.k.a. “Judische” and “Waifu,” dated Oct 21, 2024, 9 days before Moucka’s arrest. This image was included in an affidavit filed by an investigator with the Royal Canadian Mounted Police (RCMP). The U.S. Justice Department said between February and October 2024, Moucka and co-conspirators used stolen login credentials to steal cloud-hosted data belonging to at least 165 customers of a U.S.-based software-as-a-service company. The hackers targeted stolen credentials for Snowflake customer accounts that did not enforce multi-factor authentication, and extorted or attempted to extort a host of well-known companies, including TicketMaster, Lending Tree, Advance Auto Parts and Neiman Marcus. Snowflake responded to the data thefts by increasing password complexity requirements and enforcing multi-factor authentication. Moucka adopted new nicknames frequently — sometimes operating multiple identities concurrently — but two of his best-known monikers were “ Judische ” and “ Waifu .” Judische’s admitted role in the Snowflake data thefts was first documented by KrebsOnSecurity in a September 2024 story about the overlap between Western, English-speaking cybercriminals and extremist groups that harass and extort minors into harming themselves or others. That September 2024 story identified Judische as a software engineer from Ontario who has been involved in numerous data breaches and voice phishing attacks against U.S. companies since at least 2020. A little more than a month later, Canadian authorities arrested Moucka on a provisional warrant from the United States. The government says Moucka and others used their unauthorized access to steal billions of sensitive customer records and download terabytes of information, “including individuals’ non-content call and text history records, banking and other financial information, payroll records, Drug Enforcement Administration (DEA) registration numbers, driver’s license numbers, passport numbers, social security numbers and other personally identifiable information. They then extorted victims by threatening to publish data online.” Moucka also threatened and harassed government officials and security researchers who were helping to track him down. The Justice Department said the conspirators made over $2.5 million in ransom payments, and that in at least one instance, Moucka re-extorted a victim with threats of further disclosure of the victim’s stolen data. “Moucka used the stolen data of a government officer and members of a then-former government officer’s immediate family in this re-extortion attempt,” reads a statement from the Justice Department. One of Moucka’s admitted co-conspirators is Cameron “Kiberphant0m” Wagenius , a U.S. Army soldier who pleaded guilty in July 2025 to extorting AT&T and Verizon for their customer account data. Less than a month before Wagenius’s arrest, KrebsOnSecurity published a deep dive into Kiberphant0m’s various Telegram and Discord identities over the years, revealing how the owner of the accounts told others they were in the Army and stationed in South Korea. One of several selfies on the Facebook page of Cameron Wagenius. Kiberphant0m also re-extorted victims. Immediately following Moucka’s arrest, Kiberphant0m posted on hacker forums what he claimed were the AT&T call logs for then President-elect Donald Trump and for then Vice President Kamala Harris, as well schematics allegedly stolen from the U.S. National Security Agency (NSA). Wagenius is set to be sentenced on September 3, 2026. The government says he faces a maxim…

Connor Riley Moucka was extradited to the United States in July 2025 after he was arrested in Canada. The post Snowflake Hacker Pleads Guilty in US Court appeared first on SecurityWeek .

AI did not create a new browser security problem. It exposed one that enterprises have long been able to ignore. Skyhigh Security explains why browsers have become a critical control point for governing data movement, AI interactions, and modern work. [...]

Zenity researchers reported the findings to Anthropic and OpenAI in late 2025 and early 2026, but they remain unpatched. The post Zero-Click AI Browser Hacking: Claude and ChatGPT Atlas Hijacked via Emails, X Posts appeared first on SecurityWeek .

(Video) In this podcast, we share insights from Edna Conway, a recognized leader in cybersecurity and supply chain resilience with over 40 years of experience in the field. The post Podcast: Compliance Won’t Save You: The Future of Cyber Risk with Edna Conway appeared first on SecurityWeek .

[This is a Guest Diary by Daryl Jiminez, an ISC intern as part of the SANS.edu BACS program]

A Canadian man pleaded guilty today to his role in accessing company accounts at cloud storage provider Snowflake and stealing data from at least 165 organizations in a scheme to extort millions of dollars from victims. [...]

The chain involved the exploitation of several vulnerabilities in the Samsung Members and Samsung Account applications. The post How a $50,000 Exploit Chain Turned Bixby Against Samsung Phones appeared first on SecurityWeek .

As organizations adopt AI, they must secure both cloud and AI environments through a unified security control plane as their attack surface expands. Because modern applications and AI workloads are built and run in the cloud, security teams must understand which exposures matter most, prioritize what can truly be exploited, and reduce risk across cloud infrastructure, applications, identities, data, and AI systems in one place. Modern IT estates now span multiple clouds and on-premises systems, with architectures built on containers, Kubernetes, serverless functions, microservices, APIs, and AI-powered workloads. This increases both the volume and the interconnectedness of security signals. The challenge is no longer identifying individual risks, but determining how misconfigurations, identities, and data exposures combine to create real attack paths, and which of these are most critical to fix at the source. KuppingerCole’s Leadership Compass: Cloud Native Application Protection Platforms (CNAPP) reflects this shift. The report describes how CNAPP is evolving from a consolidation of cloud security tools into the security foundation for AI-native enterprises, combining cloud security, AI security posture management, runtime protection, attack path analysis, cloud detection and response, and agentic AI operations into unified platforms. Read the full report Within this evolving market, KuppingerCole names Microsoft a Leader across all four of its Leadership categories: Overall, Product, Innovation, and Market. In the report’s words: “Microsoft earns its Overall Leadership with its Defender for Cloud that is redefining the CNAPP market by extending cloud security beyond infrastructure protection and into a unified security platform for cloud, data, identity, AI, and security operations, supported by one of the industry’s most advanced agentic AI ecosystems.” That recognition reflects where the category is heading: toward platforms that unify cloud and AI security into one operational view of risk. Why CNAPP is being redefined KuppingerCole makes a clear point: CNAPP is no longer about posture or visibility alone. It is becoming the operational foundation for securing AI-powered applications, services, and business processes, across the full software lifecycle from cloud infrastructure to the AI systems running on top of it. Modern environments introduce complexity across: Multicloud and hybrid infrastructure. Rapid development and continuous deployment. Containers, serverless, microservices, and APIs. AI models, agents, pipelines, and machine identities. This complexity exposes the limits of traditional, siloed tools, where cloud posture, workload protection, AI security, and the security operations center (SOC) each live in their own console. Organizations now need platforms that can: Correlate posture, runtime, identity, data, application, and AI signals. Prioritize risk based on exploitability, not severity alone. Integrate security across development, cloud operations, and the SOC. Bring AI systems into the same risk model as the rest of the cloud. Runtime intelligence is now central to this shift. Across the platforms KuppingerCole evaluated, 94% detect active exploitation of the complex attack paths they surface, moving teams from long lists of findings to the exposures threat actors can actually use. What distinguishes leading platforms KuppingerCole evaluates providers on product strength, innovation, and market presence, and, more importantly, on how effectively they help organizations manage real risk across cloud and AI. Several themes define the next generation of platforms: AI security posture management that governs models, pipelines, and AI-specific attack paths. Agentic AI that investigates, validates exposures, and helps remediate, not just detect. Runtime-driven risk prioritization focused on what is exploitable in production. Security graphs and attack path analysis across identity, data, network, workload, an…