Analysis threats

Actor usage of AI is exploding. By analyzing artifacts left behind, Talos has created a detailed analysis of how we are seeing adversaries leverage the technology to include development, force multiplication, and vulnerability research. Based on the evidence Talos gathered, guardrails did not provide much protection, with most actors able to convince the models to comply despite the lack of sophisticated techniques or encoding. The pre-existing skill of the actor has a large impact on what they can accomplish with AI. Talos observed novice users able to create malicious capabilities, albeit with limited capabilities and success. Advanced users were able to build astonishing capabilities, pushing the models to create sophisticated and complex outputs. Artificial intelligence (AI) and associated language models are now ubiquitous and heavily used in both personal and professional contexts to streamline tasks and expand capabilities. With AI being used everywhere and by almost everyone, one of the biggest questions is how malicious actors are taking advantage. Fortunately, actors make mistakes and chatbots leave artifacts. Leveraging cloud-based AI models leaves behind a variety of artifacts, most notably a prompt log. These logs can take on a variety of shapes and sizes, but they are left on endpoints that are running various applications, such as Claude Code, CodeX, Cursor, or Gemini. Over the course of our research, we’ve collected a significant corpus of these files and can start discussing the ways we see bad actors leveraging these technologies. In conducting the research, three categories of activity emerged. One was using AI as a malicious software engineer, leveraging AI to write (in some cases) very sophisticated code with clear malicious intentions. Another was actors leveraging AI to scale criminal operations and campaigns. Finally, there were a lot of actors leveraging it for bug bounty or vulnerability research, rapidly accelerating their capabilities of discovery and disclosure. Each category demonstrates how threat actors are currently leveraging AI. Within each category is a wide disparity in sophistication based on the knowledge level of the actors involved. We tried to include use cases to cover the breadth of what we found. Takeaways and high-level findings With the recent disclosures from Hugging Face and OpenAI , it's clear the era of agentic attackers has effectively arrived. In that incident, the models were operating inside a sanctioned evaluation with safeguards deliberately relaxed — but they autonomously escaped their sandbox, found and chained real vulnerabilities, and compromised production infrastructure to reach their objective. The capabilities exist; the only missing ingredient is malicious intent, and it's a matter of time before threat actors supply it. For defenders, this is a wake-up call: Vulnerabilities will surface faster, exploitation will happen sooner, and the actors behind it won't need rest or downtime. As the case studies below show, the central challenge for guardrails right now is supporting legitimate dual-use work — red teaming and vulnerability research — without empowering malicious actors. One of the immediate takeaways is that guardrails are not functioning as expected. We did not encounter any sophisticated encoding or techniques designed to trick the models — most of the time it was a simple “I'm allowed to do this,” and the model complied. When guardrails did engage, they accomplished little. In one instance, we watched an actor abandon a censored model and pivot to an uncensored version, which completed the task without question. In another, a model pushed back on a distributed denial-of-service (DDoS) operator, but by that point the tooling had already been built. This wasn't specific to a single model or platform; it was across the board. The other big takeaway is that an actor's skill level largely determines how effectively AI can be leveraged and how much impact it u…

For the latest discoveries in cyber research for the week of 27th July, please download our Threat Intelligence Bulletin. TOP ATTACKS AND BREACHES Minnesota IT Services has confirmed coordinated cyberattacks affecting more than 30 community water utilities across the state. The incidents briefly disrupted a treatment plant in Braham and affected industrial control systems. Officials reported that drinking water safety was not affected. While the attack was not officially attributed, federal officials previously posted warning regarding targeting of critical infrastructure by Iranian-affiliated threat actors. Bank of Baroda, a major Indian bank, has disclosed an email account compromise that exposed internal communications and attachments. Reports claim more than 700GB of customer files, loan documents, and audit records were leaked, although the bank has not confirmed the reported volume. Core banking systems were unaffected. Amgen, a US biotechnology company that develops medicines for serious illnesses, has confirmed a breach involving cloud environments operated by third-party providers. Attackers exfiltrated proprietary corporate information and patient health data. The company reported no disruption to manufacturing, financial reporting, products, or its ability to supply medicines. Angola’s largest telecommunications provider, Unitel, has suffered a cyberattack that disrupted voice, mobile data, and internet services for millions of customers. The outage also affected electronic payments shortly before the company’s stock market debut. Network data indicated that internal systems were disabled while external routers remained online. AI THREATS Anthropic has disclosed that Claude-based cybersecurity models gained unauthorized access to systems belonging to three outside organizations during controlled evaluations. The models moved beyond intended test environments and reached sensitive production assets. Anthropic identified the incidents while reviewing testing practices following separate autonomous AI security failures. Researchers have published details of CVE-2026-59726, a critical vulnerability in the Ruflo AI agent platform. An unauthenticated attacker could abuse its exposed Model Context Protocol bridge to execute commands, steal API keys, access conversations, and alter stored AI memory. Ruflo addressed the issue in version 3.16.3. Researchers surfaced a privacy issue in Anthropic’s Claude sharing feature that allowed publicly shared conversations and artifacts to be indexed by search engines. Indexed content reportedly included personal information, resumes, financial records, access codes, API keys, and clinical trial material that users may not have expected to become searchable. VULNERABILITIES AND PATCHES Cisco has addressed CVE-2026-20316, an actively exploited vulnerability in Secure Firewall Management Center. The flaw allows unauthenticated attackers to access a built-in low-privileged account and retrieve sensitive information from affected systems. Cisco released hotfixes after exploitation was identified, and the vulnerability was added to CISA’s catalog. Broadcom has released patches for five vulnerabilities affecting VMware vCenter, ESX, Workstation, and Fusion. Three critical flaws could allow authentication bypass, arbitrary code execution, or escape from a virtual machine to its host. The issues include CVE-2026-59309 and CVE-2026-59310, both carrying CVSS scores of 9.8. JetBrains has released fixes for CVE-2026-63077, a critical authentication bypass affecting all TeamCity On-Premises versions. A remote unauthenticated attacker could execute code with TeamCity server privileges and compromise connected build environments. The flaw is fixed in versions 2025.11.7 and 2026.1.3. TeamCity Cloud was not affected. Rails maintainers have patched CVE-2026-66066, a critical Active Storage vulnerability affecting applications that use libvips. An unauthenticated attacker could read sensitive server files…

Explore how passkey implementation gaps undermine security when relying parties fail to validate the User Verified flag, reducing MFA to a single factor. The post Pass the Passkey: A Novel Attack Surface in Passwordless Authentication appeared first on Unit 42 .

Tenable spent 30 days running frontier AI models against our own code. It didn’t just find bugs — it proved they’re real, with reproducible exploits. That fundamentally changes code security from ranking potential code defects to a much higher signal focused on the findings that matter. Read on to learn how it reshaped our security team's work, what it cost, and why your program is next. Key takeaways: Now code security starts with proof, not suspicions. Frontier AI instantly builds working exploits and proves which flaws are genuinely dangerous in your source code. Now remediations are confirmed issues, not just ranked lists of maybes. The durable asset is the harness, not the model. Frontier AI models get the attention, but the durable asset for security teams is the harness: the orchestration and systems around the model that turn suspected flaws into proven, reproducible exploits engineers can act on. Frontier AI doesn’t replace senior researchers; it makes one as productive as five. The scarce resource is still the expert who writes the threat model and judges what’s real. Buy the compute without funding that person, and you get a very fast way to generate findings no one can use. We’ve been running Claude Mythos Preview against our own code now for over 30 days, and one thing is crystal clear: Code security is fundamentally changing, and we believe there’s no turning back. At Tenable, our security team already had security testing agents that drove our applications, exercised API endpoints, and ran our predefined checks. But until recently, the agents couldn’t handle the harder part of code testing: finding previously unidentified flaws and proving their exploitability. As part of our work testing Anthropic’s Claude Mythos Preview for Project Glasswing , we built an agentic code security harness and powered it with this Anthropic frontier LLM, running it against our code and service repositories with pinned commits to ensure reproducible results. The work of code security is changing, but not in the way hype-driven blogs suggest. And certainly not for free. We’ve found the costs are measured in two currencies: dollars and senior-engineer hours. What follows is an account from the security practitioner’s perspective of Tenable’s internal security team and how we leveraged frontier AI: where the model proved its value, where it fell short, and what you should consider before investing further. From ranking guesses to ranking proof with frontier AI For well over a decade, the scarce resource for security teams was analyst attention. We built a whole discipline around it — reachability heuristics, exploitability guesswork, etc. — all to decide what a human security analyst should look at first in your own code. Now a frontier AI model in a harness collapses that. The ranking doesn’t go away, it gets a proof instead of a guess. When a finding arrives with a working exploit, you’re no longer ranking by how likely it is to matter; you’re ranking by what you’ve already proven does. When an LLM can surface a suspected flaw and drive a working exploit against a running build, the difficult question is no longer “which among the thousands of static findings deserves a human first?” It becomes “which of the code defects are real, and can we prove it?” A bug that shows up with a reproducible proof-of-concept sorts itself. One that can’t be reproduced goes to a validation queue. This does not mean fewer bugs. In fact, it means many more findings, especially early on, because the model surfaces threats and exposures in your source code that traditional tooling never would. Instead, what changes with frontier AI is that practically all of the bugs that reach a human analyst arrive pre-sorted by proof instead of by score. It becomes a short list of things you can already reproduce, plus a holding pen of candidates the harness is still chewing on. The model gets the headlines; the harness does the work This is not to say that the model do…

This detailed 2026 investigative briefing analyzes the surge in manufacturing cyber security breaches, highlighting real-world incidents at Mercedes-Benz and Coca-Cola Fairlife. It provides a technical breakdown of SCADA supply chain attack methods and prescribes a Zero-Trust defense architecture tailored for industrial environments, offering actionable mitigation strategies for defenders.

The article details a significant data breach at SplitVPN exposing 865,336 user emails, hashed passwords, and nearly 58 million connection logs, contradicting the provider's no-logs claim. It provides a verified scope of the leaked data, analyzes the privacy implications, and offers actionable mitigation steps for affected users and organizations.

Sooner or later, every company faces the need to upgrade its infrastructure — whether to accommodate expansion, optimize processes, or keep up with the latest trends in IT. When such a decision is made, company management typically thinks first and foremost about broad changes at the platform level — assuming that applications can simply be reinstalled and everything will work as before. And to a certain extent, that’s actually true. In an era when corporate security could be ensured solely by antivirus software on workstations, that would have worked; however, modern cyberthreats require protection at a fundamentally different level. In this post, we explore why platform migration should be discussed with the security team as well, and why simply “installing a program” isn’t enough to ensure modern-day protection. Security is no longer just a single program In the past, securing endpoints was enough to prevent most attacks. In today’s environment, endpoint protection is just one layer of cybersecurity. A modern extended detection and response (XDR) solution isn’t a single application installed on a computer; it’s a set of components that work in conjunction. They provide protection for workstations and servers, event logging and storing, infrastructure-level threat detection mechanisms, investigation tools, automated response, reporting, and asset management. Each component serves a specific purpose and places different demands on the hardware and platform. For the event storage system , disk speed is the most critical factor. In a large company, the security system generates millions of records per day, and all of them must be written quickly and then retrieved just as quickly when needed. The bottleneck here usually isn’t processor capabilities, but rather how fast the system can read and write data. Threat detection requires computing power. The system compares events in real time and determines what can be a sign of an attack, and what is normal operational activity. Response time is critical for investigation tools . When an analyst investigates an incident and pieces together what happened, they work in real time, and every second of waiting adds to the overall response time to the attack. What does this mean? When a company switches platforms, it’s not enough to simply verify that the company’s existing cybersecurity solutions support the new architecture. The answer “yes, it’s supported” is too vague. It’s essential to clearly understand exactly which parts of the cybersecurity architecture are supported — starting from which version, and what is still under development. What to ask before it’s too late To avoid unexpected complications during implementation and operation, we recommend asking the right questions in advance — during the planning phase. Here are those questions: Which specific components have been tested on the new platform? The question shouldn’t be phrased as “Is the platform supported?”; the compatibility of each part of the system should be verified. Different components of a modern information-security solution operate under different rules, which is why their compatibility is tested separately. A one-word “yes” answer should raise a red flag: a reputable vendor will always provide a detailed response — including a list of components and any caveats (where applicable). Will there be sufficient resources to handle the company’s workload? “It will run” and “it will handle needed data volume” are two fundamentally different statements. The former is verified in a lab on a test bench; the latter depends on how many events specific infrastructure generates per day, and how long the company is required to retain them under regulatory or internal policies. It makes sense to ask the vendor for recommendations on calculating resources based on specific data volumes rather than relying on general minimum resource requirements when planning. Is the security solution up to date? It’s always important to clearl…

Analysis of XCSSET v40 reveals a macOS malware targeting developers via Xcode. Unit 42 used advanced pattern matching and AI to decode its logic. The post The Xcode Assassin Returns: A Deep Dive Into the Latest XCSSET Version appeared first on Unit 42 .

As federal enforcement tightens and states begin stepping in with their own cybersecurity mandates, water and wastewater utilities face a looming wave of hard compliance deadlines, compounded by recent cyber attacks on state water utilities. Key takeaways While the EPA’s national sanitary-survey mandate stalled in court, the agency is aggressively using existing authority, technical guidance, and enforcement alerts to inspect cyber gaps. Community water systems serving 3,301 to 49,999 people, the vast majority of U.S. systems, must certify their Risk and Resilience Assessments (RRAs) by June 30, 2026, under AWIA 2013. New York has already finalized binding cybersecurity regulations for wastewater facilities, setting a regulatory template that other states are expected to follow in 2026 and 2027. Under CIRCIA, utilities will soon be legally required to report significant cyber incidents to CISA within 72 hours and ransom payments within 24 hours. Federal grant programs (SLCGP) and liability protections have been extended through Sept. 30, 2026, but remain tied to unpredictable budget cycles while targeted cyber threats continue to rise. Navigating the new reality of water cyber regulation In 2023, the U.S. EPA made an initial push to fold cybersecurity evaluations into state sanitary surveys. While that effort was stayed in court and subsequently withdrawn, the underlying federal statutory requirements and enforcement drivers remain fully active. Instead of relying on new survey rules, federal and state regulators are actively using existing statutory authority and technical guidance to shift water cybersecurity from voluntary recommendations to enforceable compliance deadlines. The urgency to strengthen cybersecurity for water facilities is underscored by a recent coordinated cyber attack that disrupted water and wastewater utility operations across more than 30 Minnesota communities in late July 2026. Utility cyber regulations and mandates moving forward America’s Water Infrastructure Act (AWIA) 2013 / Safe Drinking Water Act (SDWA) 1433 is still very much in force. Community water systems serving more than 3,300 people are legally required to certify a Risk and Resilience Assessment (RRA) and Emergency Response Plan (ERP) to EPA on a five-year recertification cycle, and that cycle explicitly covers cyber threats, not just physical and natural hazards. Recertification deadlines: Systems serving 100,000-plus people: March 31, 2025 50,000–99,999 tier: Dec. 31, 2025 3,301–49,999 tier, the vast majority of U.S. water systems: June 30, 2026, with ERPs due six months after. The EPA hasn’t stopped pushing on cyber. It’s just doing it through guidance, technical assistance, and enforcement of existing authority rather than new rulemaking. In May 2024, the EPA issued an enforcement alert warning it would step up inspections tied to cybersecurity gaps found in drinking water systems. On Oct. 23, 2025, the EPA released an updated package of cyber tools: Revised Emergency Response Plan guide Cybersecurity Incident Response Plan (CIRP) template Incident-specific checklists Cybersecurity procurement checklist These tools are designed to help utilities fold cybersecurity directly into the RRA/ERP process they’re already required to complete. States are stepping in where EPA stepped back With the EPA’s national sanitary-survey mandate dead, states have started writing their own cybersecurity rules for water systems. New York is the clearest example: In March 2026, the New York State Department of Environmental Conservation finalized amendments to six New York Codes, Rules and Regulations (NYCRR) Parts 616, 650 and 750 , adding binding cybersecurity regulations for wastewater treatment facilities, including mandatory incident reporting and access-control requirements built around EPA’s own cybersecurity guidance, incorporated into the rule by reference. Reporting requirements took effect March 26, 2026. It’s a template other states are watchi…

Welcome to this week’s edition of the Threat Source newsletter. For my fianceé’s 30 th birthday, I took her on a weekend trip to Shenandoah National Park – a favorite of ours since we went to a wedding there several years back. We’ve done several incredible hikes over the years, but one in particular had always loomed over my head: Old Rag, a 9.3 mile circuit hike that’s largely considered the most difficult in Virginia. I've always been warned that at the beginning and end, you hate Old Rag. For the first 2.6 miles, you’re hiking a steep climb on a dirt road, with lots of switchbacks, and plenty of places where you turn a corner and groan, because there’s an even steeper section ahead. This part was pretty torturous, because 1) I felt like my heart was going to explode out of my chest, 2) I couldn’t breathe, and 3) several times, there was a family we passed as they were taking a break, then WE took a break and THEY passed US, and so on and so forth. So awkward. Finally, we reached the fun part: a mile-long rock scramble, where you're squeezing through (and down) narrow rock crevices, cramming your boots to desperately find any leverage to propel yourself upward, and using all your upper body strength to control your descent. This was definitely the most fun part, although my hands and knees were sore by the end. After hiking for hours, you reach the top and realize it was all worth it, because the summit has a a spectacular vie— ... That’s what we get for being excited to hike in overcast weather. Well, at least the way back down is fun— oh wait, four miles downward on a fire trail, crushing your toes in the front of your hiking boots? Yike. It may sound like I’m complaining a lot about this hike, but it was genuinely the most fun one that I’ve done to date. By the time I was freshly showered and drinking an iced coffee in Culpeper, I was gushing about when we’d go back. There’s a really good tie-in to cybersecurity somewhere here. Ah, got it. Everyone has had those uphill hike phases with the endless documentation, patching, and alerts that keep you up at night. You’re waiting for the misery to end and hoping that around the next corner, you’ll see a sign that you’re almost out of the woods. Bruised and out of breath, you finally arrive at the exciting parts: a complex project that finally comes together, the thrill of stopping an attack, or a feeling of pride when someone you're mentoring gets a new certification. Maybe the payoff is something completely unexpected. Those moments definitely don’t erase the exhaustion — you're still sore and bruised, and will be for days — but they do remind you why you started in the first place. The one big thing Talos released our Q2 2026 Incident Response Trends report , which showed a massive spike in authentication abuse and sophisticated phishing tactics. Phishing drove over half of all engagements, with attackers leveraging QR codes and advanced platforms like ARToken to bypass multi-factor authentication (MFA). Additionally, ransomware operators are increasingly weaponizing legitimate remote management tools like MeshAgent and Zoho Assist to establish stealthy, persistent access. Why do I care? Standard email gateways and basic MFA are no longer enough to stop adversaries from bypassing traditional defenses. By abusing legitimate administrative tools and trusted cloud infrastructure, threat actors can easily blend malicious traffic with normal network activity to remain undetected before deploying ransomware. Furthermore, the continued targeting of health care and public administration highlights a deliberate focus on organizations with zero tolerance for downtime. So now what? Organizations must transition from push- and SMS-based MFA to phishing-resistant methods like FIDO2 or hardware security keys. Defenders should also shift to behavior-based monitoring, specifically hunting for unauthorized instances of administrative tools. Finally, configure centralized logging with at leas…

Every organization needs security that protects end to end with the speed and scale of AI. Microsoft’s vision is simple: security should be ambient and autonomous, just like the AI it protects. As organizations scale AI and expand across environments, security teams need protection that covers every surface. This month’s updates help security and IT teams secure their AI environments, use AI to defend at speed and scale, and strengthen the foundations that AI-powered operations depend on. Here’s what’s new: Project Perception brings agentic defense to security operations Project Perception , newly announced, is a coordinated system of specialized agents, cybersecurity-focused models, and enterprise-wide signals that transform how security operates. The agents work as a team: red team agents expose weaknesses, blue team agents investigate cyberthreats, and green agents harden what’s found. These multi-agent autonomous workflows work as a team to operate in continuous loops to execute end-to-end security workflows. Learn more about Project Perception Microsoft Defender secures the full AI attack surface, from inbox to cloud Expanded Microsoft Defender protections are designed to reduce risks associated with day-to-day AI interactions, from email inboxes to cloud agent environments. New prompt injection protection in Microsoft Defender, now in preview, identifies and isolates emails containing malicious AI instructions before delivery, reducing the risk of prompt injection attacks reaching the inbox. Unified Defender posture and runtime protection for cloud agents in Microsoft Agent 365 consolidates security posture assessment and runtime protection for Microsoft Foundry, Microsoft Copilot Studio, and third party-managed agents, helping teams reduce AI-specific risk across the agent estate. Accelerate detection, prioritization, and response with AI embedded in SecOps workflows Security teams can accelerate detection, prioritization, and response to cyberthreats with AI embedded directly into security operations (SecOps) workflows through Microsoft Defender. Threat intelligence enhancements, including Microsoft Defender Threat Intelligence convergence and an enhanced Threat Intelligence Agent , bring more out-of-the-box intelligence and automation into the unified SecOps workflow, so teams can move from summary to action. Strengthen the cloud, code, and identity foundations AI depends on Microsoft Defender is strengthening the foundational protections that AI-era operations depend on across cloud, code, and identity. Cloud Security Posture Management extends coverage to serverless containers , giving teams visibility and continuous posture assessment across containerized workloads running on Azure Container Apps, Azure Container Instances, and Amazon Web Services Elastic Container Service (AWS ECS) on Fargate. New interconnected experiences between Defender and Microsoft Entra empower the security operations center (SOC) to disable compromised identities directly using a role-based access control (RBAC) mode that maintains least privilege. Microsoft Defender Experts services are also expanding : Microsoft Defender Experts Threat Intelligence delivers human-led, curated insight into the cyberthreats most relevant to each organization, and Microsoft Defender Experts MDR extends expert-run detection and response beyond the Microsoft estate into third-party and multicloud signals through Microsoft Sentinel . Microsoft Entra strengthens identity across the AI-powered enterprise Strengthen identity foundations for AI-powered operations New capabilities in Microsoft Entra are designed to strengthen the identity foundations that AI-powered operations depend on. Tenant governance helps organizations discover, manage, and govern tenants across their environment with centralized policies and cross-tenant delegated administration. Microsoft Entra ID is making passkeys the default authentication experience , which helps reduce reliance on SMS…

Your phone rings, you pick up and say hello. On the other end: total silence. No one answers, and the call abruptly disconnects. If you don’t already use spam call blockers, you’ve almost certainly run into this situation before. In most cases, these are scam calls. Today, we explain why these calls happen, what the callers want from you, and how to protect yourself. Most importantly, we’ll look at whether you even need to bother protecting yourself against them in the first place. Who’s calling? It’s not just scammers on the line — robots, legitimate call center operators, and ordinary folks make these calls too. Let’s break down each type of caller — ordered from best-case to worst-case scenario for your security. Actual person The most harmless scenario is that an actual person called you, but their microphone is acting up. Maybe they accidentally muted themselves with their ear, or their smartphone connected to a Bluetooth headset, speaker, or car system that isn’t capturing their voice. Carrier glitches can also mute one side of a call. The caller might have no idea there’s a problem — as far as they know, they are speaking, but no one can hear them. In cases like this, you usually recognize the incoming phone number. If the call comes from an unknown number, there’s still no need to panic — though the list of those who might be calling gets much longer. One legitimate possibility is a call center agent who simply didn’t pick up or connect their headset in time. Call center systems are designed to dial numbers faster than agents can wrap up their calls. The system tried to route the call to a human, but no reps were available. That’s why you sometimes have to wait a few seconds before hearing a single word, or why you might hear ringing tones as if you were the one making the call. Robot or AI Silence on the line is a common sign of robocalls. Robots test whether a phone number is active and, if it is, pass it along to a human — meaning a real sales rep (or scammer) will call you back in the next few days. It’s worth noting that scammers aren’t the only ones making these pinging calls. Legitimate call centers use the exact same tools to reduce the workload on their live agents. An AI agent could also be behind the silent call. To the person answering, there’s no practical difference: the call looks identical to one made by a standard bot. However, AI can do more than just auto-dial numbers — it can analyze your response and use that data to decide whether your number is active and ready to be handed off to a live person for follow-up. Unwanted caller Now we get to the real threat. Perhaps one of the most dangerous and unpleasant sources of silent phone calls is a scammer. A quick, silent call like this can actually be the groundwork for a long, elaborate attack with cover stories about loans, government agencies, other fraudsters, even law enforcement. Debt collectors might also be calling and staying quiet. Your number could end up on their radar if you, your family, or close contacts have outstanding debts. In these cases, a silent call is often used as a tactic for psychological pressure. A similar technique is used in stalking. While silent calls cause no direct harm on their own, they can be leveraged to induce anxiety, create a feeling of being constantly watched, and cause ongoing emotional distress. Why do they call and stay silent? When you pick up, you likely respond out of habit with a quick “Hello?” or “Hi there.” That’s all it takes for the other party to gather a wealth of data. While this information used to be difficult to process, the rise of artificial intelligence has made the task significantly easier. Let’s look at what someone can learn about you from just one spoken word: Region, accent, and location. Scammers are sophisticated and cunning. Their tactics are often tailored by region — targeting residents of specific countries or even regions within them. This is especially relevant in places like In…

Five years after the initial release, the refresh introduces new elements, removes others, and updates terminology. The post US and Allies Update SBOM Guidance appeared first on SecurityWeek .

As organizations move beyond AI experimentation, success will depend on how effectively they combine intelligence and trust. The same systems that amplify knowledge, accelerate decisions, and unlock new outcomes must also protect data, govern AI, and build resilience. In this next phase of transformation, security is not separate from innovation—it is an enabler that helps make responsible innovation possible at a faster pace. That starts with asking better questions—the kind that help organizations turn intelligence into action and trust into a foundation for progress. AI is changing how security decisions are made. Defenders now have access to more signals, insights, and analytical power than ever before. But better security does not start with more information. It starts with asking the right questions: What are we trying to protect? What risks matter most? What conditions need to be true? And what decisions do we need to make with confidence? That clarity matters because security is shaped by more than technology. The challenges organizations face rarely exist in isolation. They emerge across people, processes, technology, data, identities, and governance. Understanding those connections is what allows security teams to use platforms, AI, and automation to make better decisions under real-world conditions. Connect with Microsoft Security at Black Hat USA 2026 Security as a systems challenge Security has never been a single-layer challenge. Vulnerabilities can emerge across code, data, identities, and integrations, while exposure is often created at the intersections between them. Designing for security requires a systems mindset—understanding how these elements work together, where failure can occur, and what safeguards are needed so no single layer carries the burden alone. That is why defense in depth remains essential: layered controls, ongoing monitoring, mitigations, and risk management across the AI lifecycle help organizations reduce exposure while continuing to adapt. Agentic AI in cybersecurity Explore actionable takeaways ↗ This is especially important as AI becomes more embedded in how organizations operate. AI can help teams analyze vast amounts of information, identify patterns, and surface recommendations at a scale that was previously unthinkable. Those AI outputs still require oversight, governance, and human judgment, with clear accountability for how AI-generated insights are validated and used. But insight only creates value when it is grounded in the right context and connected to action. AI-generated insights still require validation, oversight, and resilience planning because AI systems can produce incomplete or inaccurate outputs. Clarity creates better decisions The most important security decisions start with a clear view of the risk, the level of control or visibility required, and the outcome the system is designed to achieve. When we optimize for capability over context, we miss how security decisions are actually made: through signals, expertise, validation, and judgment. This becomes even more important as AI expands what is possible. Better analysis can surface more insights, but better decisions still depend on understanding what matters most and applying the right context. That matters most when conditions are changing quickly, and teams need to act before every answer is certain. Threat intelligence offers a useful example. Defenders operate in environments defined by ambiguity, incomplete information, and rapidly changing conditions. Success rarely comes from a single source or signal. It comes from combining multiple forms of intelligence, applying expertise, validating assumptions, and connecting insights in ways that strengthen assurance. The lesson extends beyond threat intelligence. Different security objectives require different combinations of signals, analysis, and human judgment. Resilient decisions come from bringing those elements together thoughtfully, rather than relying on a…

The US Cybersecurity and Infrastructure Security Agency (CISA) and Australia's Cyber Security Centre (ACSC) have jointly published guidance to help critical infrastructure organizations isolate operational technology (OT) and supporting systems. The guidance aims to enhance cyber resilience by enabling these systems to operate in isolation for extended periods, ensuring continuity of critical services during disruptions or crises. It details steps for identifying vital systems, segmenting networks, establishing physical and logical isolation points, and creating graduated isolation plans. The guidance also highlights operational and security risks introduced by isolation, such as reduced patching and increased removable media risks, advising organizations to manage these carefully.

Research reveals a phenomenon called subliminal learning where AI language models trained on outputs from other models inherit behavioral traits, including misalignment, even when training data appears unrelated to those traits. This transmission occurs through subtle, non-semantic patterns in the data and is specific to models sharing the same base architecture. The findings challenge current AI safety assumptions that layering safety models or filtering training data can prevent unwanted trait propagation. The study highlights risks in distillation and fine-tuning processes and calls for deeper safety evaluations beyond observable model behavior.

Phishing was the primary means of gaining initial access this quarter, appearing in over half of all Cisco Talos Incident Response (Talos IR) engagements – an increase from approximately a third of engagements last quarter. Attackers continued to innovate their delivery methods to evade defenses, deploying QR code-embedded PDFs to bypass traditional email gateways and hosting links on trusted cloud platforms. We also saw a spike in authentication abuse this quarter — observed in 65 percent of engagements compared to 35 percent last quarter — with attackers frequently bypassing or defeating multi-factor authentication (MFA) using adversary-in-the-middle (AitM) proxies, session-token theft, MFA fatigue attacks, and self-enrolled devices, amongst other methods. Ransomware incidents made up over 20 percent of engagements this quarter, similar to just under 20 percent last quarter. Talos IR responded to Sinobi ransomware for the first time, as well as previously seen variants Nitrogen and Warlock. We observed ransomware operators leveraging legitimate remote monitoring and management (RMM) tools, such as trojanized MeshAgent binary and Zoho Assist, for stealthy access, requiring defenders to prioritize behavior-based monitoring and strict control over administrative binaries. In the latest Talos Threat Perspective episode, we explore these trends, and highlight where defenders have the best opportunities to detect attackers: QR phishing campaign leverages trusted infrastructure to target Australian organizations Starting in April, we observed a persistent QR code phishing campaign targeting primarily Australian organizations that leverages compromised Microsoft 365 accounts to harvest credentials and propagate the attack via internal contact lists. The campaign, which remained ongoing as of late June 2026, employs auto-generated, victim-tailored PDF documents containing QR codes that direct to adversary-controlled M365 credential harvesting pages. If credentials are successfully captured, the adversary attempts access to the victim’s Microsoft account and conducts various post-compromise actions including creating email inbox rules for defense evasion, leveraging SharePoint to host malicious documents, and sending additional internal and external phishing emails to continue the compromise chain. We assess with high confidence that the threat actor, who we have dubbed UAT-11764, will almost certainly continue leveraging this QR code phishing operation, using each newly compromised mailbox's contact lists to expand its reach and sustain the campaign's momentum. By weaponizing existing, trusted infrastructure like SharePoint and M365, UAT-11764 can bypass many standard email security gateways. As such, network defenders should implement policies that block or flag emails containing QR codes within PDF attachments, enforce phishing-resistant MFA on M365 accounts, and monitor for suspicious inbox rule creation and anomalous SharePoint file staging as indicators of post-compromise activity. ARToken platform provides toolkit for Microsoft 365 account compromise Talos uncovered a phishing-as-a-service (PhaaS) operator platform, ARToken, in an engagement this quarter that is closely linked to the EvilTokens platform. According to our analysis, the ARToken panel exposes 80+ API endpoints for device code phishing, primary refresh token (PRT) persistence, email access, business email compromise (BEC) operations, and SharePoint exfiltration — all accessible to operators through a React-based dashboard. Our investigation into the platform found phishing lures that impersonate trusted vendors and abuse legitimate Microsoft services, allowing attackers to bypass MFA through the OAuth device authorization flow rather than stealing passwords. ARToken extends beyond a typical phishing kit by providing affiliates with a comprehensive post-compromise toolkit. We observed capabilities including automated token management, persistent access through PRTs,…

We break down how ClickFix works on macOS: why attackers trick users into running commands in Terminal, what data the malware steals, and how to protect your device.

The physics of cybersecurity are changing. Introducing security's new cyber stack: Project Perception. The post Rethinking security for the age of AI appeared first on Microsoft Security Blog .

Microsoft's External Red Team Alliance (EXTRA) is a global AI security initiative designed to advance AI safety research and red teaming. By partnering with universities, researchers, and regional experts, EXTRA helps identify emerging AI risks, improve security testing, and strengthen the resilience of frontier AI systems. The post Enhancing AI security through global AI red teaming appeared first on Microsoft Security Blog .