CJIS v6.1 requires agencies to maintain strong authentication, account security, and audit controls while demonstrating ongoing compliance. Specops outlines five practical priorities covering MFA, account management, passwords, logging, and audit readiness.
A Nigerian national was sentenced to eight years in prison for his involvement in a series of spearphishing attacks targeting US tax preparation businesses since 2019. 40-year-old Chukwuemeka Victor Amachukwu (also known as Chukwuemeka Victor Eletuo and So Kwan Leung) has pleaded guilty to conspiracy to commit computer intrusions and wire fraud after being extradited from France to the United States in August 2025. "Chukwuemeka Amachukwu believed he was operating safely offshore when he targeted his victims, but he has now been held to account and now faces a serious sentence for his crimes," said US Attorney Jamie McDonald in a Monday press release. "Amachukwu took part in sophisticated schemes to hack into US businesses, steal and use stolen identity information of victims, and commit fraud. These crimes imposed significant harm on the victims and the public, and so it is only appropriate that the crimes also come with a significant sentence for the defendant."
Fintech company Revolut is working to resolve a massive outage that disrupted most of its services worldwide earlier today. Since the incident began, thousands of users on the Downdetector outage tracking platform have reported issues with the Revolut app, mobile banking services, and transferring funds between accounts. In a statement today, the company said the outage has affected its services since Tuesday morning and added that customers' data and funds are safe. "We are currently experiencing a service disruption affecting multiple services. We can confirm that all our customers' money and data are safe," Revolut said. "We've been working to fix the issue since it was identified this morning and apologise to anyone affected and for any inconvenience caused." On its official status page, the company says the outage affects 28 services, including sign-ins, card payments, transfers, currency exchange, stock trading, and live support chat, which are now flagged as partially unavailable.
Microsoft urges organizations to secure AI Agents as insider threats, using dynamic permissions, continuous risk monitoring and automated containment. Microsoft published a detailed blog post explaining how organizations should secure AI agents. Microsoft sees them as a growing insider threat, not just a possible risk in the future. AI agents are not dangerous by nature, but they can access critical systems and may fail, be manipulated, or be compromised. “The most trustworthy agentic system will not be the one with the model we trust most. It will be the one designed that enables us to trust the model least.” said Satya Nadella This is not just a theory. It is a principle that should guide how organizations design and secure AI systems. The post makes a distinction worth holding onto. An agent that starts a task with the right permissions and behaves correctly can still become dangerous if its context changes mid-run. A prompt injection in an external document, a piece of untrusted data that shifts the agent’s reasoning, a task that evolves in a direction nobody anticipated, none of these require the agent to be compromised in the traditional sense. The model produces variable outputs, the context changes, and the agent’s behavior drifts. At machine speed, the window between that drift starting and it causing damage is very short. Microsoft’s proposed answer is continuous containment rather than upfront trust. You define what the agent is allowed to do before it acts, you monitor what it actually does while it runs, and you adjust its permissions in real time as its behavior or the risk calculation changes. An expense approval agent should start with access scoped exactly to reviewing and approving expenses, nothing broader, and those permissions should shrink or disappear the moment the agent tries something outside that task. The post introduces Dynamic Permissions to apply the principle of least privilege to AI agents. An agent should not automatically get the same access rights as the employee who deployed it. It starts with no permissions and receives only the access needed for its approved task. These permissions remain active only while the task is running. “The employee retains the employee’s access.” Microsoft states. “The agent receives its own identity, permissions and its own authority scoped to its current task and for the duration of the task only.” Alongside that, Dynamic Agent Risk is a continuously updated score that combines signals from identity, endpoints, network, cloud, runtime, and the agent’s own behavior to assess whether what the agent is currently doing still matches what it was authorized to do. The response when risk rises is graduated rather than binary: preserve reads while blocking writes, narrow accessible resources, require human approval for high-impact steps, or stop execution entirely if the risk warrants it. “Dynamic Agent Risk combines signals from identity, data, endpoints, cloud, network, runtime, and the agent’s own activity. It considers how securely the agent is configured, what resources it can reach, the potential impact if something goes wrong, and whether its actions are drifting from the user’s or organization’s intent.” Microsoft states. “The result is not a one-time score assigned at onboarding. It is a continuously updated understanding of the agent’s current risk and whether its current authority still matches that risk. “ Organizations frequently have AI agents running locally or introduced through third-party tools that were never formally registered in any central system. Microsoft says it’s expanding discovery to 60 types of local agents, including Claude Code, OpenAI Codex, and GitHub Copilot. Getting those into a unified registry with accountable identities is the prerequisite for applying any of the governance controls described in the rest of the post. You can’t set least-privilege permissions for an agent you don’t know exists. You can’t detect behavioral drift from an agent that doesn’t have a tracked identity. The agent registration problem is logistically harder than it sounds, especially for organizations where individual employees can spin up agents without IT involvement, which is most organizations right now. Microsoft recognizes that organizations cannot manually review every risk alert when they run hundreds of thousands of AI agents. Its solution is Guardian Agents, AI agents focused on security. They follow playbooks created by human operators, investigate changes in risk, apply or recommend security measures, and use what they learn to improve security policies. Humans set the goals and approve important decisions, while the agents handle continuous monitoring and response. However, this approach raises another concern. Guardian Agents are also AI agents, so they can fail or be manipulated, just like the agents they are supposed to control. Microsoft says security controls must operate outside the AI model and must not be changed by it. But this raises an important question: how can organizations ensure these controls remain reliable when the system enforcing them is also an AI agent? This is a challenge that real-world deployments will need to address in the coming years. “Organizations are adopting agents to serve customers better, solve problems faster, and give people more time for the work that matters most. The goal is not to make every model perfectly predictable before it can be useful.” Microsoft concludes. “The goal is to build systems that remain secure even when the model is not.” Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, AI Agents)
Introduction Imagine you’ve ordered a small paper unicorn from an online marketplace. You clicked “Buy”, received a cheerful notification, and expect a courier to bring the box tomorrow. If the unicorn is delayed by a day, it will be annoying but not catastrophic: an apology, a discount promo code — and the incident is forgotten. Now let’s multiply one late unicorn by several hundred thousand orders. Packages start heading to the wrong cities. The website shows an item is in stock, even though the required bin is empty. Conveyors stop, boxes get stuck between floors, the cargo piles up with no freight manifest. Trucks line up at the gates, and every minute of downtime turns into blown schedules, support tickets, fines, and lost sales. It is at exactly this scale that a cyberincident in a warehouse becomes a problem for the entire business. A modern warehouse is no longer just a big building with shelving. It is a tightly interconnected hybrid system: web applications, radio channels, and an automated factory. Physical processes here depend on data, and errors in data have very physical consequences. Examples include an outage that affected warehouse management systems at the grocery giant Morrisons, and the 2025 Form 10-K annual report of United Natural Foods, Inc. (UNFI), which confirmed unauthorized activity on information technology systems that impacted order fulfillment. More recently, reports emerged that a cyberattack disrupted eight CEVA Logistics warehouses across Europe and exposed customer delivery data. This paper follows a single order through a warehouse to show where the operation is vulnerable, the stages it traverses, the systems that drive it, and the points where an attacker can reach them. We then set out the threat model: what is at risk, who is in a position to take it, and how each risk lands on the business. From there, we look at how an attacker gets in, and what reaching the warehouse management system costs in practical terms: orders unshipped, inventory records nobody can trust, and an operation that stops. We close with recommendations on where the controls that matter actually sit. Tracing the unicorn A modern warehouse is a sequence of stages involving many machines and people, all working together to keep the business process stable so that, in the end, your order gets delivered. This process consists of eight main stages, shown in the figure below. Stages of order fulfillment So let’s assume we’ve ordered our paper unicorn and are waiting for it at home. Let’s follow our order through all the main stages, from its arrival at the warehouse to the final stop on its journey. Unloading First, the unicorn arrives in the unloading zone, packed in a big truck. The driver is assigned a gate, for example, via a tablet with kiosk mode enabled, or an outdoor display board, indicating where the truck should park and where the cargo will be unloaded. Even at this very first step, a digital command (the gate number on the screen) is already triggering a physical action. Therefore, incorrectly assigned gates can create a queue, delay unloading, or send goods into the wrong workflow. Receiving At this stage, employees identify the cargo. They scan a barcode using a portable data terminal (PDT) and the central system receives a message indicating that this object arrives at the warehouse. From this moment, the unicorn exists in two forms at once: as a real box and as a record in the information system. If these two versions diverge, the error is inherited by all subsequent processes. Putaway Next, the goods are moved into internal storage. Two new devices come into play here. First, a thermal printer, connected to the internal network over Wi-Fi, creates an internal label for each item. Then an employee, forklift, or automated system moves the goods to the assigned bin, often with the help of lifts controlled by PLCs. Both of these devices can be valuable attack entry points: one can let an adversary pivot into the internal network, while the other can give them control over an electric motor. Storage Then the unicorn goes into storage. Many distribution centers use multi-level mezzanine structures: several floors of metal shelving inside a huge space. They allow efficient use of the building’s height, but at the same time complicate control over the technical infrastructure. Wi-Fi access points, cameras, switches, cables, and sensors may be mounted high overhead or buried deep inside the rows. A forgotten Ethernet cable or misconfigured networked device (access point or switch) left behind in a dark corner can become a convenient initial access point into critical infrastructure. Picking When the customer places an order, picking begins if the goods were already stored in the warehouse or as soon as they are unloaded. A PDT, workstation, light indicator, or voice terminal directs the employee to the required bin where they pick the goods and move them to the next stage. These devices are themselves potential attack entry points: compromising a workstation or PDT could allow an attacker to manipulate picking information, which could misdirect employees to the wrong bin. Here, both the speed and integrity of the information are critical, and any manipulation or disruption can lead to wrong orders, delays, or problems in subsequent stages. Sorting At the sorting stage, the warehouse starts to look more like a factory. Boxes move through conveyor belts and pass through different scanners, diverters, and chutes. The sorting plans are usually stored and managed by dedicated servers, while PLCs are responsible for controlling the machinery and executing these plans. For example, when the warehouse management system (WMS) decides that our unicorn should take route A, the control system needs to activate the right diverter at the right moment, sometimes within a fraction of a second. Packing During packing, an employee or a robotic arm places the goods into the final box, prints the shipping label, and sometimes measures the dimensions and weight of the package. Safety mechanisms usually prevent robotic arms from leaving the controlled zone and harming nearby operators, but their compromise might inflict physical damage on the packages being processed. Shipment Finally, at the shipping stage, the parcel heads to the gates. Automated guided vehicles (AGVs) and autonomous mobile robots (AMRs) move containers and pallets across the warehouse, while the dock management system coordinates the truck that will carry the unicorn onward to a store, a sorting center, or straight to the customer. These robots are themselves a potential target for attackers. Attacks can be conducted against AGVs and AMRs to interfere with their operation, for example by affecting their navigation or preventing them from reaching their intended destination. All eight stages are coordinated by the WMS. It looks like a large web application, but in its role it’s closer to the operating system of the entire warehouse: it knows which goods exist, where they’re located, who or what should move them, and where they go next, linking employees, inventory levels, storage addresses, tasks, and orders. It also exchanges data externally: with ERP systems, transport platforms, marketplaces, dark stores, and external carriers. Surrounding the WMS is an even larger digital ecosystem: identity services, databases, APIs, printers, carrier systems, technicians’ laptops, video surveillance, access control, fire and gas alarms, power supply, and a building management system (BMS). That is why a single “warehouse network” doesn’t really exist. As we’ve seen, there are many overlapping technologies — IT infrastructure, OT systems, radio, cloud services, building security, and automation — layered on top of one another. A lone vulnerability scanner will never tell you whether a warehouse is secure. Hunting the unicorn Securing an environment such as a warehouse requires a comprehensive security assessment covering all of its interconnected systems. This involves identifying vulnerabilities across each system and understanding how weaknesses can be combined into attack paths that a real attacker could exploit. But a vulnerability only matters in proportion to what it exposes and who is able to reach it, so before looking at the weaknesses themselves, we need to understand what an attacker in this environment is actually after, because in a warehouse, the blast radius extends well beyond data. Everything we just traced — the systems, the devices, and the people operating them — exists to keep goods moving, and attacks in various parts along that chain can affect the business differently. The chart below shows what is at risk in the warehouse and where those risks land for the business. The segment on the left groups them under the three core security properties: integrity, availability, and confidentiality. The segment on the right maps each property to the business outcomes a failure can cause. Warehouse risks The first area at risk is integrity. Inventory counts, locations, orders, and shipment data must stay in sync with the physical world. Corrupting a record silently desynchronizes the operation, and because the eight stages form a dependency chain, one falsified entry early on is inherited downstream, surfacing later as stockouts and mis-shipments. In its deliberate forms, this lets an attacker redirect goods, release stock, and perform other actions on behalf of the platform’s vendors under cover of legitimate records. Integrity is also a safety concern: when people or machines act on information that no longer reflects the physical environment, a data failure can become a physical incident. This is why integrity is the only property linked to all five outcomes, including harm to people. The second is availability, the warehouse’s ability to keep goods moving. Halting a conveyor, a sorter, label printing, or the WMS stops orders from shipping, and in a business built on speed, every hour of downtime means delayed deliveries and broken promises. Ransomware can bring the whole warehouse to a standstill. The impact shows up as operational disruption, lost revenue, and reputational damage. The third is confidentiality. Customer data, business records, and system credentials are valuable targets. Their exposure leads to legal liability and reputational damage, and stolen credentials often open the door to further attacks. Where the WMS connects to financial or ERP processes, the risk extends to theft of funds. Knowing what is at risk tells us what an attacker stands to gain; the next question is who is in a position to take it. Threat actors differ in the access they already hold. For example, an attacker may be authenticated and privileged, have limited physical or remote access, or have no legitimate access to the environment at all. Based on their relationship with the warehouse and their level of access, threat actors can generally be divided into two categories: External. An attacker with no legitimate relationship with the warehouse or the organization, operating without authorized access. External attackers can be divided into two categories based on their physical proximity to the environment: Remote. An attacker operating from outside the site’s physical area, reaching the environment through whatever the organization exposes or makes reachable over the internet, including web services, remote access infrastructure, and third-party connections used by suppliers, carriers, and integrators. Proximate. An attacker with no legitimate access who has nevertheless moved within physical range of the site’s locally reachable technologies. They may, for example, be in a parking lot, a neighboring unit, or a delivery bay. Their proximity may allow them to interact with wireless, radio, Bluetooth, or other short-range interfaces without possessing an account, badge, employment relationship, or other authorized access. Internal. An individual with legitimate access to the warehouse, its systems, or its information, who intentionally or unintentionally creates a security risk. This includes employees, administrators, operators, contractors, and temporary staff. Combining these threat actors and their access levels with the risks identified earlier, the vulnerabilities present in each system, the resulting attack surfaces, and the potential attack paths between them provides a threat model for the warehouse environment. This allows an organization to understand how different systems and people could be targeted, how individual weaknesses could be combined, and where security controls are most needed. Cornering the unicorn Knowing what is at risk and who might come after it still leaves the most practical question open: how they would actually get in, and how far they could go once they did. The diagram below sets out the warehouse’s attack surface: every point where an attacker can get in, organized by the access that reaching each point requires. Warehouse attack surface On the left are the attacker categories discussed above, distinguished by where they stand and what access they already hold. Each reaches the environment through a different set of entry points, and the impact of a successful attack can land on several systems, from the WMS to OT systems such as robots, sorters, and physical access control system (PACS). The WMS is highlighted because it is the most significant of these: it coordinates the OT systems, so compromising it can affect the entire operation rather than a single process. Next, we will cover the initial access vectors, the points a threat actor can use to reach the warehouse environment. Following that, we turn to the impact on the logistics processes themselves, focusing on the WMS, since its compromise affects every logistics operation that depends on it. Initial attack vectors Internet-facing services Remote access through internet-facing services, third-party connections, and corporate networks gives an external attacker a foothold on the warehouse network infrastructure. It is a well-covered problem and not specific to this environment, so we note it here as an entry point but will not examine it further. Wi-Fi, Bluetooth, and other radio channels Wi-Fi connects handhelds, tablets, printers, cameras, and workstations. Bluetooth serves scanners, headsets, and positioning beacons. Zigbee and similar low-power protocols run lighting, sensors, and building automation, while LoRaWAN carries telemetry over long distances. Cellular provides a backup channel for kiosks and contractor equipment, and proprietary protocols control industrial panels and specialized machinery. Radio passes through windows, gates, roofing, and thin external panels, so a network built for receiving and processing goods may be reachable from the parking lot and, with a directional antenna, from considerably farther away. That reach matters in two ways. It gives an external attacker a place to start, as proximity alone is enough to reach the Wi-Fi and the low-power protocols, and from there to gain an initial foothold in the warehouse networks. However, radio does not only lead into the network. It also connects directly to the field devices and carries the live control traffic of warehouse operations, which makes availability a first-order concern. If hundreds of handhelds lose their connection at once, picking stops. If an AGV loses its control channel, the safe reaction may be to halt in place, and a stopped machine can block an entire route. Physical network The scale of the warehouse itself is part of the attack surface. A fulfillment warehouse can run up to tens of thousands of square meters, with racking climbing several stories and walkways threading through it. Structured cabling runs along that racking, cameras and access points are mounted on that, and wall jacks sit behind pallets that have not moved in months. Almost none of it is in anyone’s line of sight. That gives a person in the warehouse something a normal office does not: unsupervised access to live network infrastructure. Unplugging a ceiling camera leaves an active port. An unused jack behind a shelf leaves another. Neither requires tools, credentials, or any interaction with a system that logs anything. And since the camera or access point sits on the same segment as the rest of the site, the compromised port, not being isolated, opens a path to the network core. Barcode scanners Barcode scanners are everywhere in a warehouse. They are the main tool workers use to tell the system what is moving and where, supporting receiving, picking, packing, and inventory management. A typical setup has handheld scanners communicating with a base station, which is in turn connected to a workstation or another business system. This makes the scanner an entry point into the core network in two ways. First, through the barcode itself. Since the scanner acts as a keyboard to the connected host, a maliciously crafted barcode or QR code can inject keystrokes when scanned, potentially giving the attacker an initial foothold on the host without directly accessing the network. Second, through the scanner’s wireless link. During a customer engagement, with the provided test stand of such a device, we discovered that an attacker within range could inject keystrokes into the connected host and potentially achieve remote code execution without user interaction. This attack pattern was observed across multiple vendors, including, for example, Honeywell devices affected by CVE-2026-4272. In both cases, the result is the same: a foothold on a host inside the warehouse network. The scanner is simply the entry point; the significance of that foothold comes from the host’s trusted position within the operational environment and its connectivity to core systems. Portable data terminals Portable data terminals (PDTs) are essentially ordinary Android devices with an embedded barcode scanner, carried by workers to scan items; each scan is passed to a dedicated application that forwards it to a remote server over an API. To keep workers on task, the devices usually run in kiosk mode, locking the user to that single application and preventing interaction with the rest of the Android system. That lockdown is exactly what an attacker wants to break, and breaking it is what turns the terminal into an initial access vector: escaping the kiosk can expose the Wi-Fi password of the network the terminal is connected to, or allow malicious software to be installed that gives the attacker remote access to the network over the internet. Printers Warehouses contain different types of printers. Alongside the usual IT printers used for documents and paperwork, there are specialized thermal printers, small devices that use heated elements on the printhead to create labels, barcodes, and tags. As we mentioned earlier, these are mainly used to print the labels, usually containing barcodes, that are attached to goods during the putaway stage. Here we focus on mobile thermal printers: small, battery-powered devices that workers can carry or wear. They typically connect to the internal network over Wi-Fi to receive print commands, while also supporting Bluetooth for connecting to nearby devices. This combination makes them a potential entry point into the internal network. Some models, such as the Zebra ZQ630, support multiple interfaces and can run applications directly on the device. During a security assessment, we discovered that apps can be uploaded and executed over Bluetooth. By exploiting a pairing misconfiguration, an attacker within Bluetooth range could bypass pairing, upload malicious software, and gain an initial foothold through the printer. Impact on logistics processes (attacks on WMS) With a foothold in the network, an attacker can pivot to the logistics processes themselves: from the WMS through the warehouse infrastructure to the PLCs and the machinery they drive. As we saw earlier, all OT systems and devices are interconnected and the WMS sits at the head of that chain: it is the system of record every other process reads from and writes to, so compromising it reaches all of them at once. That, and its being specific to this environment, is why it is the focus here. Warehouse management systems (WMS) are the software platforms that optimize warehouse processes from the entry of goods to their exit. They provide real-time visibility into inventory and orchestrate end-to-end fulfillment by integrating with many warehouse subsystems and pieces of automation equipment, such as conveyors, PLCs, robotics, scanners, and voice systems. A typical WMS includes modules for receiving, inventory control, order management, labor management, shipping, and reporting. Major vendors include SAP EWM, Oracle Warehouse Management, Manhattan Active, Blue Yonder, Infor, Körber/HighJump, Microsoft, and TECSYS. To picture how central this is, think back to our unicorn. From the moment it was scanned at receiving, it stopped being only a physical box and became a record inside the WMS, a record the system then used to decide where it should be stored, when it should be picked, how it should be sorted, and where it should ship. Every device employed along the way — the PDT at receiving, the printer at putaway, the workstation at picking, the conveyor at sorting — was really just talking to the WMS. It is the thread that ties all eight stages together, which is exactly what makes it such a valuable target. Because modern WMS platforms are usually web-based and heavily interconnected, they inherit common web and API vulnerabilities alongside flaws specific to the WMS itself. A recent example is CVE-2026-70774 in Oracle Warehouse Management, part of Oracle E-Business Suite. Oracle rated it High and described it as an easily exploitable authorization bypass flaw in which a low-privileged attacker with network access can compromise the application, affecting integrity and availability by allowing unauthorized creation, deletion, or modification of critical data. A flaw like this may look like a typical web application issue, but its consequences in a warehouse are more serious, because the WMS is the system of record. If an attacker can modify its data, they can alter stock levels, bin locations, receiving records, picking tasks, or shipment information, silently corrupting the digital twin of the warehouse. And since the eight stages form a dependency chain, that corruption doesn’t stay contained: a falsified record at receiving is inherited by putaway, picking, and everything downstream. The physical box and its record diverge, and every later process trusts the record. The most direct version of this attack comes from an authorization bypass flaw like the Oracle vulnerability above. Here the threat actor can be an external attacker who has reached the application over the network, or an insider such as a low-privileged operator or storekeeper who already holds a legitimate account. The danger grows when such a flaw is chained with others. An external attacker who combines remote code execution with SQL injection could generate shipment orders to arbitrary addresses together with the documents needed for goods to physically leave the warehouse, fabricate waybills, acceptance or transfer records, and registers, while also exposing customer data such as names and delivery addresses. In effect, the goods are sent out with legitimate-looking paperwork. This is why ordinary web vulnerabilities carry considerable weight in a WMS. For an external attacker or an insider probing beyond their assigned role, broken access control could open a path into another warehouse zone, allow manipulation of other workers’ tasks, permit unauthorized exception operations, or expose administrative APIs. A server-side request forgery flaw could force the WMS server to reach resources an external attacker cannot touch directly, and if the network is flat or only formally segmented, that server may in turn reach internal management panels, cloud service interfaces, or systems sitting close to the operational network, turning a single web bug into a bridge between IT and OT. Attacks on a WMS don’t always target the application directly, though. As we saw while tracing the unicorn, the warehouse is full of connected devices that already hold trusted access. A handheld terminal carries authenticated WMS API access as a matter of course, and anyone who gains control of that terminal inherits it (by escaping the kiosk, for example). Depending on the device’s permissions, that might mean confirming picks that never occurred, falsifying receiving operations, adjusting stock counts, or marking orders complete — something warehouse employees themselves could use to avoid their assigned duties. Where the WMS is connected to control and automation systems, access to the WMS can extend into physical operations, including conveyors, sorting systems, lifts, doors, and pumps. PLCs translate WMS instructions and sensor inputs into physical actions. Compromising a system that controls them therefore creates an opportunity to manipulate those actions. The impact can be as simple as a sorting diverter sending boxes down the wrong route, a conveyor repeatedly entering an error state and creating a backlog, or a falsified sensor value causing a line to be treated as clear when it is full. However the WMS is compromised, the business consequence is the same: inventory corruption, unauthorized shipments, and operational disruption, each reaching the customer in the end as a late or missing delivery, the wrong item in the box, or a personal address exposed to a stranger. Securing the unicorn We followed our unicorn through web applications and databases, radio channels and PDTs, printers, conveyors, robots, and the loading zone. Because warehouse environments combine IT, OT, wireless, physical, and human components, security controls should be implemented as a single, coordinated security architecture rather than as isolated measures. Network segmentation should be a foundational control, with clear separation between corporate IT, warehouse OT, operational devices, management networks, and externally connected systems. Segmentation should also extend across facilities and customer environments so that each site and customer integration is isolated from the others, limiting the potential impact of a compromise. A zero-trust approach should reinforce this architecture by requiring explicit authentication and authorization for connections between systems, regardless of their network location, and by applying least-privilege access wherever possible. Regular penetration testing of the corporate IT environment, including domain services, identity infrastructure, and endpoints, should be incorporated into the warehouse security program. Physical and network access controls should be implemented together. Access to warehouse facilities, network rooms, communication cabinets, and operational areas should be restricted according to business need, with appropriate authentication, monitoring, and access logging. Network infrastructure should be hardened through controls such as switch port security, MAC-based access restrictions where appropriate, and IEEE 802.1X with EAP-TLS for strong device and user authentication. Network equipment should also be securely configured and regularly reviewed to ensure that unused interfaces, insecure management protocols, default credentials, and unnecessary services are disabled. Web applications and their supporting infrastructure should be governed through a secure software development lifecycle (SSDLC), including security requirements, secure coding practices, code and dependency review, and application security assessment before deployment and throughout the application’s lifecycle. Third-party applications and components should be continuously monitored and updated, with a defined vulnerability and patch management process. This should explicitly include warehouse management systems (WMS), warehouse portals, APIs, and other applications that provide operational or customer-facing functionality. Wireless technologies should be subject to dedicated security assessment and engineering. Radio-frequency surveys should be conducted to establish expected coverage, identify unauthorized or unexpected signals, validate the availability and protection of operational communications, and determine whether wireless deployments create unintended access paths into warehouse networks. Wireless security should be assessed not only from a connectivity perspective but also in terms of authentication, encryption, device provisioning, protocol exposure, interference resilience, and the potential impact of unauthorized devices. Warehouse operational devices should be incorporated into the organization’s endpoint security and vulnerability management processes. Devices should receive security updates and firmware patches on a defined schedule, with accelerated remediation for critical vulnerabilities. Security assessments should be performed periodically to identify weaknesses in device configuration, applications, exposed services, and authentication mechanisms. Personnel security should form an additional layer of the warehouse security architecture. In most industrial and ICS environments, getting inside means clearing background checks, holding relevant qualifications, or proving prior experience; the hiring process itself acts as a filter. A warehouse is different. Roles in sorting, packing, and courier work are hired quickly and in volume, and they typically require no prior expertise, certification, or specialized background at all. An ordinary person can walk in off the street, be hired within days, and immediately hold legitimate physical access to the facility. Therefore, a more restrictive and risk-based approach to hiring should be considered, particularly for roles that provide access to sensitive areas, operational systems, network infrastructure, or customer assets. Ultimately, all of these measures serve the same objective: protecting the continuity and reliability of the warehouse as a whole. This matters because real warehouses handle food, medicines, machine parts, and the millions of ordinary things people and companies depend on every day. Protecting their journey means seeing the warehouse as it has actually become: a single digital system with doors, motors, shelving, and radio signals, and with entirely real consequences when it fails. And if the security program works, the customer never knows any of this happened. The unicorn simply arrives at the scheduled time. If your warehouse operations rely on interconnected systems like these, we can help identify the gaps before an adversary does. Reach out to discuss a security assessment.
Ransomware operators including Spikey Scorpius (aka Qilin) and Tarnished Scorpius (aka Inc) are exploiting PAN-OS vulnerability CVE-2026-0257. The post Threat Brief: Active Exploitation of PAN-OS CVE-2026-0257 (Updated October 19) appeared first on Unit 42.
Some downloads of the Rank Math PRO WordPress plugin from the vendor’s official website carried malware that planted hidden backdoors in a supply-chain attack last week. According to the vendor, a limited number of users who downloaded version 3.0.123 of the plugin between October 15 at 20:02 UTC and October 16 at 07:12 UTC received compromised versions that could compromise their websites upon activation. “The affected plugin files contained malware that could compromise your website if the plugin was activated,” Rank Math warned. “We immediately removed the affected files and released a clean version, Rank Math PRO v3.0.124.” Users who installed and activated the trojanized version during this 11-hour window should treat their websites as compromised and follow the clean-up procedures in the advisory from the vendor.
Cybercriminals are selling forged identity documents, deepfake videos, and live verification services to help buyers bypass Know Your Client (KYC) checks. Flare examines how these underground services operate and the techniques used to create and maintain fraudulent verified accounts.
F5 has released out-of-band security patches to address multiple NGINX web server flaws, including three critical-severity vulnerabilities that can let attackers execute code on vulnerable systems. The three critical vulnerabilities were found in the ngx_http_v3_module (CVE-2026-15176 and CVE-2026-97205) and the NGINX map directive (CVE-2026-93479). Remote attackers without privileges can exploit them to launch denial-of-service (DoS) attacks or gain code execution on NGINX systems with non-default configurations. Successful exploitation causes a heap-based buffer overflow or use-after-free in the NGINX worker process, leading to crashes or a restart. However, attackers may also be able to "execute code on systems with Address Space Layout Randomization (ASLR) disabled or when the attacker can bypass ASLR."
Meta wants the right to scrape your website for AI training. If you have a business account, that includes you. At the end of the month, Meta plans to change its commercial terms in a way that matters to every company advertising or selling through its platforms. The new language takes effect on October 30, 2026. It lets Meta collect content from websites associated with business customers and use it to train AI models or otherwise improve its products, according to The Register. Meta defines “business customer” broadly. It includes anyone who uses ads or marketing messages, sells or lists products, develops apps, uses a product catalog, manages a Page, runs a Group for business purposes, or uses tools such as Ads Manager or Meta Business Suite. At least one million businesses already use Meta’s AI agents in WhatsApp and Messenger. Nieman Lab also points out that almost every news publisher has at least one Meta business account. The contract clearly explains which tools Meta can use. By accepting the terms, you allow Meta, or anyone working on its behalf, to use automated tools such as web scrapers, bots, spiders and crawlers to access and index your websites, pages and URLs. These tools can also revisit your sites regularly to collect updates. “You authorise us (or any entity acting on our behalf) to use automated software (such as web scrapers, bots, robots, spiders, crawlers and user agents) and create test credentials to access, index, cache, analyse, collect, retrieve or crawl the domains, web pages or URLs (and any content available through them) that are associated with your products or services, or that are made available through your or users’ use of Meta Company Products and services, and to periodically pull updates from such domains, web pages or URLs.” states Meta’s commercial terms. “Meta may use any content from such domains, web pages or URLs to provide, develop, improve, research, train and maintain the integrity of, the Meta Company Products, services and features provided under these Commercial Terms and any other applicable supplemental terms.” Then comes the use clause. The company may use any content from those domains to provide, develop, improve, research, train and maintain the integrity of its products, services and features. The contract lists scrapers, bots, robots, spiders, crawlers and user agents, which is a lot of ways to say visitor you didn’t invite. The News/Media Alliance says there’s no way out. Business accounts have no option to opt out of the terms, and the only alternative is to stop using Meta’s products. ““Meta’s new commercial terms of use are outrageous and probably illegal. The company’s decision to withhold access to its audience unless businesses allow Meta to scrape content from their websites is an appalling, bad-faith policy, and a clear abuse of the company’s market power. It cannot be allowed to be implemented on October 30.” states Media Alliance. “The text is so far reaching that any business with intellectual property online and a Meta business account could have their copyrighted material taken from them.” Danielle Coffey, President and CEO of the News/Media Alliance also pushed the point beyond news sites. Her questions were whether Taylor Swift’s Meta business account would give Meta access to copyrighted media on her website, and whether Shutterstock’s would let Meta scrape its images. The Alliance’s argument is that any business with intellectual property online and a Meta account could be affected, not just publishers. There is also a problem with robots.txt. News reports say the social network giant plans to let businesses control how its crawlers access their websites through robots.txt files, but the contract makes no such promise. The law does not always require companies to follow these instructions, so businesses must rely on Meta to respect their preferences. The company didn’t respond to The Register’s request for comment. If you run a Meta business account, someone should read the terms before October 30 and check what your own robots.txt actually says. Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, AI)
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