Threats tagged 'rce'

A critical remote code execution (RCE) vulnerability (CVE-2026-44963) affects Veeam Backup & Replication (VBR) versions up to 12.3.2.4465. This flaw allows any authenticated domain user with low privileges to execute code remotely on domain-joined backup servers. The vulnerability is fixed in version 12.3.2.4854 and does not affect version 13.x due to architectural changes.

SAP released security patches addressing multiple critical vulnerabilities in NetWeaver, Commerce, and Data Hub components. These flaws include an XML Signature Wrapping issue in SAML authentication, a memory corruption bug in the SAP kernel, a Spring Security HTTP header issue, and a directory traversal vulnerability in NetWeaver Application Server Java. The vulnerabilities could lead to sensitive information disclosure, memory corruption, denial-of-service, and disruption of normal system usage. Temporary mitigation for the XML Signature Wrapping flaw includes disabling SAML authentication. SAP has issued official patches for these critical issues.

This diary continues the Internet Storm Center&&#x23&#x3b;x26&#x3b;&#x23&#x3b;39&#x3b;s tracking of the TeamPCP supply chain campaign, first documented in the SANS white paper When the Security Scanner Became the Weapon and most recently in the handler diary Activity Through 2026-05-24. Since that update, the story moved into two new places: the United States government, which formally caught up to the campaign, and the wider population of attackers now wielding the Mini Shai-Hulud framework that TeamPCP open-sourced last month.

Microsoft has created an open-source fork of Windows Terminal called "Intelligent Terminal," and it allows you to use AI directly inside Terminal without interfering with the regular session. [...]

Scope: AWS Content Type: Important (requires attention) Publication Date: 2025/07/23 6:00 PM PDT Updated Date: 2025/07/25 6:00 PM PDT Description: Amazon Q Developer for Visual Studio Code (VS Code) Extension is a development tool that integrates Amazon Q's AI-powered coding assistance directly into the VS Code integrated development environment (IDE). AWS is aware of and has addressed an issue in the Amazon Q Developer for VS Code Extension, which is assigned to CVE-2025-8217. AWS Security has inspected the code and determined the malicious code was distributed with the extension but was unsuccessful in executing due to a syntax error. This prevented the malicious code from making changes to any services or customer environments. We will update this bulletin if we have additional information to share. Affected version: Amazon Q Developer for Visual Studio Code Extension (version 1.84.0)

Bulletin ID: AWS-2025-019 Scope: AWS Content Type: Important (requires attention) Publication Date: 2025/10/07 01:30 PM PDT Description: We are aware of blog posts by Embrace The Red (“The Month of AI Bugs”) describing prompt injection issues in Amazon Q Developer and Kiro. Amazon Q Developer: Remote Code Execution with Prompt Injection” and “Amazon Q Developer for VS Code Vulnerable to Invisible Prompt Injection. These issues require an open chat session and intentional access to a malicious file using commands such as find, grep, or echo, which could be executed without Human-in-the-Loop (HITL) confirmation. In some cases, invisible control characters could obfuscate these commands. On July 17, 2025, we released Language Server v1.22.0, which requires HITL confirmation for these commands Amazon Q Developer: Secrets Leaked via DNS and Prompt Injection. This issue requires a developer to accept a prompt-injected suggestion including commands such as ping or dig, which could exfiltrate metadata via DNS queries without HITL confirmation. On July 29, 2025, we released Language Server v1.24.0, which requires HITL confirmation for these commands. AWS Kiro: Arbitrary Code Execution via Indirect Prompt Injection. This issue requires local system access to inject instructions that lead to arbitrary code execution via Kiro IDE or MCP settings files without HITL confirmation in either Kiro's Autopilot or Supervised mode. On August 1, 2025, we released Kiro version 0.1.42, which requires HITL confirmation for these actions when configured in Supervised mode. Amazon Q Developer and Kiro are built on the principles of agentic development, enabling developers to work more efficiently with the help of AI agents. As customers adopt AI-enhanced development workflows, we recommend they evaluate and implement appropriate security controls and policies based on their specific environments and shared responsibility models (AWS, Amazon Q, Kiro). Amazon Q Developer and Kiro provide safeguards, including Human-in-the-Loop protections and customizable execution policies, to support secure adoption. Affected versions: Amazon Q Developer for find, grep, echo (version <1.22.0) Amazon Q Developer for ping, dig: (versions <1.24.0) AWS Kiro: version 0.1.42

CVE Lite CLI is a free, open-source command line tool that scans your projects in seconds and tells you exactly which included packages contain a vulnerability. The post OWASP Incubator Project Helps Developers Find and Fix Vulnerable Dependencies in Seconds appeared first on SecurityWeek .

On June 2, 2026, the White House signed an Executive Order directing federal agencies to harden their systems with AI-enabled cyber defenses and to stand up a new AI cybersecurity clearinghouse — most of it on a 30-day clock. Here’s what the EO requires and how Tenable can help. Key takeaways: The new AI Security Executive Order will require national security and civilian federal agencies to prioritize cyber defenses to account for new frontier AI model capabilities. Tenable is well positioned to help federal agencies gain visibility across their environments, including AI assets, and to prioritize the vulnerabilities and other exposures that pose the highest risk; Tenable AI-enabled exposure management capabilities can help support vulnerability remediation and automate multi-step remediation workflows. The vulnerability and patching clearinghouse which will be developed under the Executive Order will require strong engagement from private sector partners, including Tenable, to drive actionable insights on AI-associated vulnerabilities and mitigation prioritization. On June 2, 2026, the President signed an Executive Order (EO) titled “ Promoting Advanced Artificial Intelligence Innovation and Security .” The direction is clear and the calls to action are fast-moving. Within 30 days: Federal agencies must begin hardening their information systems with AI-enabled cyber defenses. CISA must issue new directives or guidance for civilian agencies. The Department of the Treasury (Treasury), with the National Security Agency (NSA) and the Cybersecurity and Infrastructure Security Agency (CISA), must stand up a new AI cybersecurity clearinghouse focused on finding and fixing software vulnerabilities. Within 60 days, Treasury, with the Department of War (DoW), NSA and CISA, in consultation with the White House and other agencies, must establish a classified benchmarking process to assess the capabilities of frontier AI models through voluntary collaboration with AI developers. While the Executive Order applies to U.S. federal agencies, the need to prepare for changes in the threat landscape brought about by the advanced cyber capabilities of frontier AI models applies to any organization that needs to manage cyber risk. Here’s a breakdown of what the AI EO requires, the deadlines that matter, and where Tenable fits. What the AI Executive Order requires The EO’s operative provisions sit in Section 2 (“Upgrading American systems for advanced AI”) and Section 3 (“Secure frontier model deployment”). The cybersecurity core is in Section 2. Within 30 days: National security and defense systems. The Committee on National Security Systems must prioritize the cyber defense of National Security Systems (NSS) and the Secretary of War must do the same for DoW information systems (Section 2(a) and 2(b)). Civilian federal systems and critical infrastructure. CISA, in consultation with the Office of Management and Budget (OMB), the Assistant to the President for National Security Affairs, and the National Cyber Director, must release Binding Operational Directives (BODs) “and other guidance as appropriate” to: Expedite and prioritize the cyber defense of civilian federal information systems. Establish or expand federal programs and services that enhance AI-enabled defensive tools. Facilitate access to cybersecurity tools and services, including where appropriate, covered frontier models, for agencies, state and local authorities, and critical infrastructure operators such as rural hospitals, community banks, and local utilities. Worth noting, while the EO directs CISA to release BODs or other guidance for federal civilian agencies, the specific implementation directives are not yet known (Section 2(c)). The AI cybersecurity clearinghouse. The Secretary of the Treasury, with the National Cyber Director, NSA, and CISA, must form an AI cybersecurity clearinghouse, in voluntary collaboration with the AI industry and critical infrastructure operators. The EO tasks the clearinghouse with three concrete functions, per Section 2(d): Coordinate and deconflict scanning for software vulnerabilities Discover and validate those vulnerabilities Coordinate and prioritize the remediation and distribution of vulnerability patches. Grant funding for AI vulnerability detection. OMB, with the National Cyber Director and CISA, must determine whether existing federal grant programs have funding that can be directed toward applicants developing advanced AI vulnerability detection (Section 2(e)). Within 60 days: Cybersecurity workforce. The Office of Personnel Management must expand hiring and placement pathways for cybersecurity specialists through the United States Tech Force (Section 2(f)). Secure frontier model deployment. Treasury, NSA, and CISA, in consultation with NIST and others, must develop a classified benchmarking process to assess the advanced cyber capabilities of AI models. They must also set the threshold for designating a “covered frontier model,” and design a voluntary framework through which developers can give the government up to 30 days of pre-release access to those models. The Executive Order is explicit that it does not create any mandatory licensing, preclearance, or permitting requirement for AI models (Section 3). No fixed deadline: Criminal enforcement. The EO directs the Attorney General to prioritize enforcement against those who use AI to illegally access or damage computer systems (Section 4). For federal cybersecurity leaders, this is less a future-state policy document than a near-term planning trigger. Watch for CISA’s issuance of BODs and other guidance, and for readouts on the clearinghouse, during June and July. How Tenable can help The EO’s center of gravity — finding software vulnerabilities, validating them, prioritizing them, and driving remediation — is the work Tenable's platform is built to do. While the AI Executive Order focuses on vulnerability discovery, validation, prioritization, and remediation, the benefit of the Tenable One Exposure Management Platform is that it addresses vulnerabilities alongside other security weaknesses, including misconfigurations of AI systems and overpermissioned AI agents, to serve as the system of action for mitigating cyber exposure and reducing cyber risk across organizations’ expanding attack surfaces. Below, learn how specific Tenable capabilities map to the EO’s requirements. Continuous vulnerability detection across the attack surface Sections 2(a) through 2(d) turn on the ability to find vulnerabilities across a wide range of systems continuously. Tenable One Vulnerability Management and Tenable Security Center provide network-based and agent-based assessment across IT assets, with credentialed scanning for greater depth. Tenable One Cloud Exposure extends that visibility to cloud workloads and configurations, and Tenable One Attack Surface Management maps internet-facing assets that agencies may not know they have. For agencies operating classified or air-gapped environments — relevant to the National Security Systems named in Section 2(a) — Tenable Enclave Security is built to run vulnerability and configuration assessment inside those boundaries. Risk-based prioritization, not “patch everything” Section 2(d) doesn’t only call for discovering vulnerabilities — it calls for prioritizing them for remediation. That distinction matters because no agency can patch everything at once. Tenable’s Vulnerability Priority Rating (VPR) uses machine learning, trained on the company’s corpus of more than 1.7 trillion security findings accumulated over more than 25 years of continuous scanning, to forecast which vulnerabilities are most likely to be exploited, so defenders can focus on the smaller set that represents real, immediate risk. By leveraging AI-generated features and expert intelligence from Tenable's Research Special Operations team, VPR helps organizations pinpoint the critical 1.6% of vulnerabilities that represent actual business risk . Tenable also ingests CISA’s Known Exploited Vulnerabilities (KEV) catalog — the continuously updated, authoritative list of Common Vulnerabilities and Exposures (CVEs) under active exploitation — directly into prioritization, aligning remediation guidance to the same source CISA uses to track risk across the federal enterprise. AI-enabled defensive tooling Section 2(c) directs CISA to establish or expand programs that enhance AI-enabled defensive tools. As frontier AI models accelerate the rate at which vulnerabilities can be discovered and exploited , the traditional window for manual remediation is rapidly closing. The June 2026 AI Executive Order recognizes this shift, directing federal agencies to counter machine-speed threats with AI-enabled cyber defenses within 30 days. Tenable Hexa AI , the agentic engine of the Tenable One Exposure Management Platform , is designed to help counter machine-speed threats, supercharge productivity, and accelerate risk reduction by automating multi-step remediation workflows. Security teams can leverage pre-built agents directly in the user interface or build custom agents via the Model Context Protocol (MCP), turning exposure intelligence into decisive action at machine speed. At the same time, as agencies build custom models or adopt third-party tools like ChatGPT and Copilot, they fundamentally expand their attack surface. It is now critical to protect enterprise AI, shadow AI, training data, and underlying infrastructure from emerging threats like adversarial attacks, data poisoning, and model theft. Tenable secures this expanding attack surface with Tenable One AI Exposure , which is designed to help agencies see, manage, and control the risks introduced by generative AI. Tenable One AI Exposure allows agencies to discover and inventory AI tools and libraries, and apply AI usage policies across the environment — a growing requirement as agencies adopt AI and need to account for it as part of

By participating in Project Glasswing and working with Claude Mythos Preview, Tenable can help customers better understand how emerging frontier AI models behave, their evolving risks and benefits for cybersecurity, and the kinds of controls organizations will need as AI adoption accelerates. Key takeaways Tenable is also interested in using Mythos Preview to drive new research, strengthen the security of Tenable, and help customers better understand how emerging frontier AI models behave, their evolving risks and benefits, and the kinds of controls organizations will need as they accelerate AI adoption. Tenable previously announced the integration of the Tenable One Exposure Management Platform with the Claude Compliance API to give Tenable customers better AI visibility and governance capabilities, along with Claude-powered workflows in Tenable Hexa AI, the agentic engine of the Tenable One platform. Over the past year, it has become increasingly clear that AI is going to fundamentally reshape cybersecurity. Not eventually. Now. The pace of vulnerability discovery is accelerating. Attack surfaces are expanding faster than ever. Security teams are already overwhelmed trying to determine what actually matters. At the same time, frontier AI models like Claude Mythos Preview are demonstrating that new capabilities in reasoning and agentic workflows are on the horizon and could significantly accelerate cyber offense and challenge cyber defense over the next few years. Tenable joining Project Glasswing is a strategic step forward for defenders, and an extension of our existing partnership with Anthropic . We also believe the industry is entering a period where defender advantage will not come from access to any single model. It will come from understanding what matters most, reducing exposure before attackers strike, and coordinating remediation at the speed modern threats demand. Improving what matters most The industry already has more findings than humans can realistically process. The real challenge is understanding what matters most. Which exposures are actually dangerous? Which combinations create meaningful attack paths? What should be fixed first? What actions will materially reduce risk? Those are exposure management problems. We’re working with frontier AI models to evaluate and benchmark how advanced reasoning capabilities may improve exposure analysis, attack path understanding, prioritization, and remediation decision-making to help our customers and partners improve their own security and risk management initiatives. As part of Project Glasswing, we’re particularly interested in driving new research using Mythos Preview to better understand where it can help reinforce existing security analysis, and strengthen our own defenses by using frontier models to improve the security of Tenable. We also plan to use Mythos alongside other models to help challenge assumptions, and identify relationships and risk patterns faster than traditional approaches alone. We believe frontier models will increasingly become another important source of security insight and telemetry flowing into exposure management platforms. The long-term differentiator for defenders will not be access to a single model. It will be the ability to combine those signals with authoritative context, asset intelligence, attack path analysis, and coordinated remediation across the enterprise. Understanding the AI attack surface Another important reality is that organizations are increasingly responsible for AI systems they did not build themselves. That creates a rapidly expanding attack surface. Our goal is simple: when meaningful advances in AI capabilities arrive, we will be ready to translate them into practical customer value quickly and responsibly. Participating in frontier AI initiatives like Project Glasswing help us better understand emerging model behaviors, evolving risks, and the kinds of controls organizations will need as AI adoption accelerates. That learning directly informs both our products and our own internal security practices. The future of cybersecurity One thing is becoming increasingly clear: frontier AI capabilities will not remain rare for long. Capabilities that seem extraordinary today will eventually become widely available across the industry, including to attackers. In that world, defender advantage will not come from access to any single model. It will come from understanding what matters most, reducing exposure before attackers strike, and coordinating remediation at the speed modern threats demand. That is the work we’re focused on at Tenable. That is our commitment to our partners and customers. And we’re excited to be doing it alongside Anthropic and the broader Project Glasswing community.

Law enforcement and tech companies disrupted infrastructure linked to scammers operating across Southeast Asia. The post Over 1.4 Million Accounts Disrupted in Cybercrime Crackdown appeared first on SecurityWeek .

Visual Studio Code (VS Code) has introduced a two-hour delay before automatically updating most extensions to newly published versions. This delay aims to add a layer of protection against problematic or potentially compromised extension releases. Trusted publishers such as Microsoft, GitHub, and OpenAI are exempt from this delay and their extensions update immediately. Users can still manually update extensions at any time without waiting. This change is intended as a security measure to reduce risk from malicious or unstable extension updates.

This is an announcement of an open-source detection ruleset called OT Sentinel, designed for Operational Technology (OT) and Industrial Control Systems (ICS) protocols such as Modbus, DNP3, IEC 104, MQTT, and OPC-UA. The ruleset includes 29 detection rules for Wazuh and Sigma platforms, mapped to MITRE ATT&CK for ICS. The project is community-driven, lab-validated for Modbus, and intended as an educational and detection engineering resource rather than a production-ready solution. It aims to fill a gap in open-source OT detection capabilities, providing visibility into OT protocol attacks at the SIEM layer. The author requests community feedback and emphasizes testing in non-production environments before deployment. This is not a vulnerability or exploit but a security tool resource.

SYNTEX has open sourced 2,500 novel MITRE ATT&CK technique mutations generated autonomously by their Nemesis AI red team using reinforcement learning. These mutations represent new attack vectors derived from known MITRE techniques, validated against a production defense system (Guardian AI). The dataset is intended for use in threat intelligence and detection rule development. There is no indication that these mutations represent active exploits in the wild or vulnerabilities in specific products. The vectors are provided in standard formats for SIEM integration and are licensed for free use with attribution.

CVE-2026-23479 is a critical use-after-free vulnerability in Redis introduced in version 7.2.0 and publicly disclosed in 2026. It allows an authenticated user to execute arbitrary OS commands via a three-stage exploit chain involving Lua scripting and memory manipulation. The vulnerability survived multiple security reviews and affects many Redis deployments, especially those without password protection. Official patches were released on May 5, 2026, across multiple Redis branches. Mitigations include immediate patching, restricting Redis exposure to the public internet, enforcing TLS, tightening ACLs, and disabling Lua scripting if unused. This vulnerability is part of a broader set of Redis RCE flaws disclosed simultaneously.

Tenable CTO Vlad Korsunsky talks about participating in the World Economic Forum’s Annual Meeting on Cybersecurity and Tenable’s EXPOSURE 2026 conference, where he talked with global leaders about new game-changing AI threats and the groundbreaking benefits of exposure management. Key takeaways The patching cycle is obsolete. Advanced AI models have compressed exploitation timelines into “negative days,” meaning adversaries actively weaponize vulnerabilities before vendor patches are even released. Shift from static CVE severity scores to AI-powered exposure management. Point-in-time vulnerability-risk snapshots fall short. You need AI insights to prioritize remediation based on real-world exploitability of your entire attack surface. Secure the agentic economy. The rapid explosion of autonomous non-human AI identities demands the immediate application of zero trust and least-privilege cryptographic primitives to mitigate severe, systemic internal risks. Don’t focus only on vulnerabilities. While the 2026 Verizon DBIR ranks vulnerability exploitation as the top initial access vector for breaches (about 30%), the majority of breaches (70%) stem from human errors, such as misconfigurations and identity flaws. Tenable Chief Technology Officer Vlad Korsunsky recently participated in the World Economic Forum’s Annual Meeting on Cybersecurity in Geneva, Switzerland, an annual summit that takes the pulse of global cyber risk. Korsunsky was one of 150 senior leaders from global industry and government who gathered to discuss how to strengthen businesses’ cyber defenses. The sobering, collective consensus: The traditional cybersecurity playbook is obsolete, as AI becomes an unprecedented threat multiplier. For Tenable, participating in foundational, high-level dialogues and collaborations such as this one is both a privilege and an immense responsibility. As the cybersecurity operating model gets rewritten in real-time, Tenable feels a duty to help shape cyber defenders’ collective insights and strategies. Tenable has spent years addressing the structural cybersecurity operational gaps that worry C-level executives and government leaders worldwide. Korsunsky also had a chance to sit down with many of the hundreds of cybersecurity executives who gathered recently at Tenable’s EXPOSURE 2026 conference . The EXPOSURE 2026 discussions ranged from the death of reactive patching cycles to the need to counter AI threats with systemic cyber resilience, and signaled an urgent need to shift away from a siloed, fragmented approach to cybersecurity and move toward AI-powered exposure management . Below is an in-depth Q&A with Korsunsky, expanding on his participation in the Geneva and Tenable meetings, the rapid escalation of AI threats, and the way to tame cyber risk today and in the coming years. Q: Vlad, you recently returned from the World Economic Forum’s Annual Meeting on Cybersecurity in Geneva. What was the overarching energy in the room among these 150 global leaders, which included CEOs, CTOs, CISOs and government leaders? Vlad Korsunsky: The energy was highly focused and, frankly, deeply sober. We are witnessing an unprecedented compression of the threat landscape, and everyone in that room, whether they were running a multinational bank, directing a national cyber defense agency, or leading an NGO, realized that conventional cyber defenses cannot keep up with this velocity. A telling example of how high the stakes have jumped occurred just recently in Washington, D.C. The then Federal Reserve Chair Jerome Powell and U.S. Treasury Secretary Scott Bessent convened an emergency, high-level meeting with the CEOs of some of America's largest financial institutions, including Wall Street giants like Goldman Sachs, Citigroup, Wells Fargo, Bank of America, and Morgan Stanley. The entire meeting focused on a single AI model: Anthropic’s Claude Mythos Preview . Anthropic had flagged that while it built Mythos to bolster cyber defense, its raw capabilities were so advanced that, if weaponized or leaked, it could pose a major threat to the structural stability of the global financial system. When the highest echelons of fiscal and state power are holding emergency briefings over the capabilities of a single generative AI model, you know you’re dealing with a fundamentally different cyber threat landscape. Q: When asked, "What are the top cyber concerns for 2027?," meeting participants ranked the capacity of AI to be a threat multiplier as number one. Is this a future problem, or are we living it now? Vlad Korsunsky: The threat of AI in the hands of attackers is absolutely a global concern today. Look at the empirical metrics tracking adversary speed over the last decade and a half. For years, Mandiant tracked a linear trend that actually looked like a win for defenders. Time-to-exploit, which is the window between a vulnerability being disclosed and an active exploit hitting the wild, shrank steadily from 63 days in 2018 down to 32 days by 2022. Concurrently, average attacker dwell time — the time an attacker remains undiscovered after breaching a network – plummeted from more than 400 days in 2011 down to just 14 days in 2025. In short, defenders were actively closing the gap. Then came 2023, and the trend broke violently. Time-to-exploit collapsed from 32 days to just five. By 2024, it went negative: minus one day. According to Mandiant’s latest “M-Trends 2026 Report ,” published last month, the average time-to-exploit sits at minus seven days . Think about that structural asymmetry. Attackers are successfully weaponizing and exploiting vulnerabilities a full week before a vendor compiles and ships a patch. Meanwhile, the median timeline for an enterprise to deploy a patch across their environment is roughly 43 to 55 days, according to this year’s Verizon Data Breach Investigations Report (DBIR) . If adversaries are operating in negative time and defenders are operating across months, the traditional patching cycle is effectively a dead strategy. Q: What is driving this terrifying acceleration? How are attackers moving so quickly? Vlad Korsunsky: It is driven entirely by advanced frontier LLMs doing in minutes what used to require weeks of highly specialized human labor. Back in February, Anthropic’s Opus 4.6 model uncovered more than 500 zero-day vulnerabilities in widely utilized open-source software, flaws that had remained undiscovered despite decades of manual peer review by brilliant human engineers. Less than two months later, Anthropic’s Mythos model found thousands more vulnerabilities across foundational operating systems, web browsers, and core cryptographic libraries. More importantly, Mythos went further after spotting them; it boasted an 83% autonomous success rate in chaining disparate, low-severity logic flaws into devastating, end-to-end critical exploits. Essentially, we have reached a watershed moment reminiscent of when Google DeepMind’s AlphaGo defeated human Go champions . Experts believed a computer was decades away from mastering the Go game because the game features more potential board configurations than there are atoms in the observable universe. Brute force was impossible. Yet, AlphaGo won by leveraging deep neural networks to synthesize a form of machine intuition, discovering creative moves no human had conceived in 2,500 years of play. Today, frontier AI models are applying that exact evolutionary leap to cybersecurity. The most powerful LLMs can now execute 32-step complex reasoning chains to autonomously map and compromise simulated corporate networks. The asymmetry is stark. This massive capability curve means the absolute volume of known exposures is poised for a massive step-change, and GenAI has poured pure gasoline on the fire. Q: With zero-days dropping in droves thanks to AI-aided discoveries, should enterprises focus all their engineering resources on hunting down these vulnerabilities? What did you hear from CISOs and other high-level cybersecurity leaders about this issue at Tenable’s EXPOSURE 2026? Vlad Korsunsky: This is where we have to look at the whole board and avoid panic. While the influx of AI-driven zero-day disclosures is a massive upstream pressure on software vendors, data from this year’s Verizon DBIR shows that breaches directly leveraging software exploits account for about 30% of incidents. It's a significant percentage, yes, but what about the other 70%? Cybersecurity leaders I talked to at EXPOSURE 2026 realize that the overwhelming majority of enterprise breaches do not begin with an ultra-sophisticated, state-sponsored zero-day exploit. They start with incredibly simple, unforced human errors: unsecured shadow IT cloud assets running outside corporate governance; misconfigured databases left wide open to the public internet; over-privileged corporate identities; a lack of multi-factor authentication (MFA); and highly targeted, AI-driven spear phishing. This is a critical insight for guiding your cyber strategy today. These misconfigurations and unsecured cloud credentials are the dry fuel sitting inside an enterprise network. When an AI hacking agent comes looking, that fuel ignites faster than any traditional cybersecurity team can react. So organizations must be diligent about proactively maintaining stringent security hygiene. Q: If paddling faster inside the old patching model won't save us, how do defenders change the rules of the game? Vlad Korsunsky: We have to look at this the way wildland firefighters have looked at massive forest fires for over a century. When a wildfire is roaring toward a town faster than a human can run, firefighters don’t just stand at the edge of the flames reaching for a bigger water hose. They get ahead of the blaze and light a controlled burn. They intentionally clear out the brush, trees, and fuel ahead of time. When the main fire line reaches that cleared zone, it starves and dies because there is nothing left to consume. Enterprise security must adopt this exact philosophy. We have to stop reacting to the fire and start aggressively clearing the fuel before the adversary arrives. This requires a wholesale shift from reactive vulnerability patching to continuous exposure management . The traditional Common Vulnerability Scoring System (CVSS) is effectively dead as a primary prioritization tool . A static CVSS score tells you the theoretical severity of a single CVE in a vacuum; it tells you absolutely nothing about real-world exploitability within the specific context of your unique enterprise environment. At EXPOSURE 2026, we heard from our customers how continuous, AI-driven exposure management is helping them counter today’s evolving AI threats successfully. With exposure management, you use advanced analytics to gain unified, real-time visibility across your entire modern attack surface, encompassing data centers, cloud infrastructure, OT/IoT environments, corporate identities, and newly deployed AI pipelines. We must use AI on the defense side to continuously map true attack paths ; for example, pinpointing exactly where a minor misconfiguration chains into a critical business asset. Q: You mentioned using AI on the defense side. How does Tenable view the balance between human security analysts and autonomous AI defenders? Vlad Korsunsky: Security is fundamentally a team sport, and AI vendors like OpenAI and Anthropic are not our adversaries. AI is the single most potent tool ever introduced into the defender’s toolkit; we simply need to wield it with machine-speed orchestration. Because our adversaries are deploying fully autonomous hacking agents today — tools that are already topping commercial bug bounty leaderboards — the only fair fight is to meet machine speed with machine speed. This means building and deploying agentic AI workflows on the side of the defense to power autonomous exposure management. However, this must always be balanced with strict human-in-the-loop oversight. In Geneva, we spent a great deal of time discussing the systemic risks of unchecked automation. If an autonomous system applies a sweeping remediation script without understanding the broader business context, it can inadvertently trigger a massive operational outage: a self-inflicted systemic failure. Defenders must maintain deep visibility into the “behind-the-scenes” logic of their automation. We need human control to govern business context, while leveraging machine speed to continuously ingest, prioritize, and neutralize exposures before an attacker can strike. Q: Another major pillar of the WEF discussion centered on AI safety and non-human identities. What are the hidden risks enterprises are overlooking as they rush to adopt AI? Vlad Korsunsky: We are transitioning rapidly into what we call the “Agentic Economy.” Historically, enterprise security focused on securing human users and a relatively manageable set of non-human service accounts. As organizations embed AI agents into core business workflows — from code generation to customer operations to financial automation — we are seeing an exponential growth of non-human, agentic identities and agentic workflows. These autonomous agents are fundamentally different. Instead of operating just “on behalf” of a human in a tightly bound session, they execute complex tasks independently. The alarming reality discussed in Geneva and in our EXPOSURE 2026 conference is that our current security frameworks lack effective, native guardrails for these agents. LLMs routinely bypass system prompts or ignore markdown safety files. They can even actively manipulate or hack neighboring AI agents to achieve their algorithmic goals. We’ve seen anecdotal instances of an enterprise AI agent autonomously writing a script to bypass an internal access restriction, and when flagged, its underlying logic essentially argued that the script committed the violation, not the agent itself. Because AI agents behave essentially like trusted corporate insiders that have been let loose across internal data silos, we must immediately apply foundational cryptographic primitives to agentic identities. We need strict zero-trust architectures, rigorous least-privilege access controls, and absolute defense-in-depth tailored specifically for non-human identities before they morph into the next great vector of unmanageable global risk. Q: Any final thoughts for organizations trying to navigate this massive technological shift? Vlad Korsunsky: Attackers are increasingly rocketing laterally across enterprise networks after the initial breach, often in minutes and even seconds, whereas before it could take them days or weeks. The adversary’s inherent advantages will always be timing, velocity, and the luxury of only needing to find a single weak link in your exposure landscape. But as defenders, we possess the ultimate home-field advantage: We can see the whole board, and we have the power to fundamentally alter the terrain. By abandoning obsolete point-in-time checkmarks, embracing continuous, AI-driven exposure management, and proactively clearing out our operational fuel at machine speed through foundational cyber hygiene, we can break the adversary’s curve and effectively secure our environments.

European and international law enforcement agencies have dismantled nine organized crime groups and arrested 29 suspects in a major crackdown on illegal streaming operations. [...]

Dashlane experienced a brute-force attack targeting its two-factor authentication (2FA) system, where attackers attempted to rapidly guess numeric 2FA codes to register their own devices on user accounts. This allowed attackers to download encrypted vaults from fewer than 20 personal plan users. Dashlane's security systems detected the attack quickly and automatically locked affected accounts to limit impact. The encrypted vaults remain protected by the users' master passwords, which were not compromised. There is no evidence of any impact on Dashlane's internal systems. Affected users have been notified and accounts restored.

Multiple Dashlane users have been locked out of their accounts following brute-force attacks that attempted logins from distant locations and unknown devices. [...]

Hackers exploited a vulnerability in Meta's AI support assistant bot used for Instagram account recovery to hijack high-profile accounts, including those of the Obama White House and the U.S. Space Force Chief Master Sergeant. The attackers tricked the AI bot into linking a new email address to targeted accounts, enabling password resets and account takeovers. The exploit relied on using a VPN with an IP address near the victim's usual location and succeeded only on accounts without multi-factor authentication (MFA). Meta responded by deploying an emergency patch and securing impacted accounts.

The Centre for Cybersecurity Belgium (CCB), the country's national authority for cybersecurity, warned on Friday that threat actors are now exploiting a recently patched critical Windows Netlogon vulnerability in attacks. [...]