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Fortinet, Ivanti, and SAP Issue Urgent Patches for Authentication and Code Execution Flaws - December 10, 2025

Fortinet, Ivanti, and SAP have moved to address critical security flaws in their products that, if successfully exploited, could result in an authentication bypass and code execution. The Fortinet vulnerabilities affect FortiOS, FortiWeb, FortiProxy, and FortiSwitchManager and relate to a case of improper verification of a cryptographic signature. They are tracked as CVE-2025-59718 and

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Adobe Patches Nearly 140 Vulnerabilities - December 09, 2025

The Experience Manager security update resolves 117 vulnerabilities, including 116 identified as cross-site scripting (XSS) bugs.

The post Adobe Patches Nearly 140 Vulnerabilities appeared first on SecurityWeek.

Microsoft Patches 57 Vulnerabilities, Three Zero-Days - December 09, 2025

Microsoft has addressed a Windows vulnerability exploited as zero-day that allows attackers to obtain System privileges.

The post Microsoft Patches 57 Vulnerabilities, Three Zero-Days appeared first on SecurityWeek.

Microsoft Names New Operating CISOs in Strategic Move to Strengthen Cyberdefense - December 09, 2025

Promotions across Microsoft’s security organization reinforce the company’s shift toward AI-driven defense and tighter operational oversight under Global CISO Igor Tsyganskiy.

The post Microsoft Names New Operating CISOs in Strategic Move to Strengthen Cyberdefense appeared first on SecurityWeek.

Prime Security Raises $20 Million to Build Agentic Security Architect - December 09, 2025

The AI-powered platform autonomously conducts security design reviews and proactively identifies design flaws across development work.

The post Prime Security Raises $20 Million to Build Agentic Security Architect appeared first on SecurityWeek.

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Further Hardening Android GPUs - December 09, 2025

Posted by Liz Prucka, Hamzeh Zawawy, Rishika Hooda, Android Security and Privacy Team

Last year, Google's Android Red Team partnered with Arm to conduct an in-depth security analysis of the Mali GPU, a component used in billions of Android devices worldwide. This collaboration was a significant step in proactively identifying and fixing vulnerabilities in the GPU software and firmware stack.

While finding and fixing individual bugs is crucial, and progress continues on eliminating them entirely, making them unreachable by restricting attack surface is another effective and often faster way to improve security. This post details our efforts in partnership with Arm to further harden the GPU by reducing the driver's attack surface.

The Growing Threat: Why GPU Security Matters

The Graphics Processing Unit (GPU) has become a critical and attractive target for attackers due to its complexity and privileged access to the system. The scale of this threat is significant: since 2021, the majority of Android kernel driver-based exploits have targeted the GPU. These exploits primarily target the interface between the User-Mode Driver (UMD) and the highly privileged Kernel-Mode Driver (KMD), where flaws can be exploited by malicious input to trigger memory corruption.

Partnership with Arm

Our goal is to raise the bar on GPU security, ensuring the Mali GPU driver and firmware remain highly resilient against potential threats. We partnered with Arm to conduct an analysis of the Mali driver, used on approximately 45% of Android devices. This collaboration was crucial for understanding the driver’s attack surface and identifying areas that posed a security risk, but were not necessary for production use.

The Right Tool for the Job: Hardening with SELinux

One of the key findings of our investigation was the opportunity to restrict access to certain GPU IOCTLs. IOCTLs act as the GPU kernel driver’s user input and output, as well as the attack surface. This approach builds on earlier kernel hardening efforts, such as those described in the 2016 post Protecting Android with More Linux Security. Mali ioctls can be broadly categorized as:

• Unprivileged: Necessary for normal operation.
• Instrumentation: Used by developers for profiling and debugging.
• Restricted: Should not be used by applications in production. This includes IOCTLs which are intended only for GPU development, as well as IOCTLs which have been deprecated and are no longer used by a device’s current User-Mode Driver (UMD) version.

Our goal is to block access to deprecated and debug IOCTLs in production. Instrumentation IOCTLs are intended for use by profiling tools to monitor system GPU performance and are not intended to be directly used by applications in production. As such, access is restricted to shell or applications marked as debuggable. Production IOCTLs remain accessible to regular applications.

A Staged Rollout

The approach is iterative and is a staged rollout for devices using the Mali GPU. This way, we were able to carefully monitor real-world usage and collect data to validate the policy, minimizing the risk of breaking legitimate applications before moving to broader adoption:

1. Opt-In Policy: We started with an "opt-in" policy. We created a new SELinux attribute, gpu_harden, that disallowed instrumentation ioctls. We then selectively applied this attribute to certain system apps to test the impact. We used the allowxperm rule to audit, but not deny, access to the intended resource, and monitored the denial logs to ensure no breakage.
2. Opt-Out Policy: Once we were confident that our approach was sound, we moved to an "opt-out" policy. We created a gpu_debug domain that would allow access to instrumentation ioctls. All applications were hardened by default, but developers could opt-out by:
• Running on a rooted device.
• Setting the android:debuggable="true" attribute in their app's manifest.
• Requesting a permanent exception in the SELinux policy for their application.

This approach allowed us to roll out the new security policy broadly while minimizing the impact on developers.

Step by Step instructions on how to add your Sepolicy

To help our partners and the broader ecosystem adopt similar hardening measures, this section provides a practical, step-by-step guide for implementing a robust SELinux policy to filter GPU ioctls. This example is based on the policy we implemented for the Mali GPU on Android devices.

The core principle is to create a flexible, platform-level macro that allows each device to define its own specific lists of GPU ioctl commands to be restricted. This approach separates the general policy logic from the device-specific implementation.

Official documentation detailing the added macro and GPU security policy is available at:

SELinux Hardening Macro: GPU Syscall Filtering

Android Security Change: Android 16 Behavior Changes

Step 1: Utilize the Platform-Level Hardening Macro

The first step is to use a generic macro that we built in the platform's system/sepolicy that can be used by any device. This macro establishes the framework for filtering different categories of ioctls.

In the file/sepolicy/public/te_macros, a new macro is created. This macro allows device-specific policies to supply their own lists of ioctls to be filtered. The macro is designed to:

• Allow all applications (appdomain) access to a defined list of unprivileged ioctls.
• Restrict access to sensitive "instrumentation" ioctls, only permitting them for debugging tools like shell or runas_app when the application is debuggable.
• Block access to privileged ioctls based on the application's target SDK version, maintaining compatibility for older applications.

Step 2: Define Device-Specific IOCTL Lists

With the platform macro in place, you can now create a device-specific implementation. This involves defining the exact ioctl commands used by your particular GPU driver.

1. Create an ioctl_macros file in your device's sepolicy directory (e.g., device/your_company/your_device/sepolicy/ioctl_macros).
2. Define the ioctl lists inside this file, categorizing them as needed. Based on our analysis, we recommend at least mali_production_ioctls, mali_instrumentation_ioctls, and mali_debug_ioctls. These lists will contain the hexadecimal ioctl numbers specific to your driver.

   For example, you can define your IOCTL lists as follows:
   

   define(`unpriv_gpu_ioctls', `0x0000, 0x0001, 0x0002')
   define(`restricted_ioctls', `0x1110, 0x1111, 0x1112')
   define(`instrumentation_gpu_ioctls', `0x2220, 0x2221, 0x2222')

Arm has provided official categorization of their IOCTLs in Documentation/ioctl-categories.rst of their r54p2 release. This list will continue to be maintained in future driver releases.

Step 3: Apply the Policy to the GPU Device

Now, you apply the policy to the GPU device node using the macro you created.

1. Create a gpu.te file in your device's sepolicy directory.
2. Call the platform macro from within this file, passing in the device label and the ioctl lists you just defined.

Step 4: Test, Refine, and Enforce

As with any SELinux policy development, the process should be iterative. This iterative process is consistent with best practices for SELinux policy development outlined in the Android Open Source Project documentation.

Conclusion

Attack surface reduction is an effective approach to security hardening, rendering vulnerabilities unreachable. This technique is particularly effective because it provides users strong protection against existing but also not-yet-discovered vulnerabilities, and vulnerabilities that might be introduced in the future. This effort spans across Android and Android OEMs, and required close collaboration with Arm. The Android security team is committed to collaborating with ecosystem partners to drive broader adoption of this approach to help harden the GPU.

Acknowledgments

Thank you to Jeffrey Vander Stoep for his valuable suggestions and extensive feedback on this post.

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Four Threat Clusters Using CastleLoader as GrayBravo Expands Its Malware Service Infrastructure - December 09, 2025

Four distinct threat activity clusters have been observed leveraging a malware loader known as CastleLoader, strengthening the previous assessment that the tool is offered to other threat actors under a malware-as-a-service (MaaS) model. The threat actor behind CastleLoader has been assigned the name GrayBravo by Recorded Future’s Insikt Group, which was previously tracking it as TAG-150.

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Identity Security Firm Saviynt Raises $700 Million at $3 Billion Valuation - December 09, 2025

The funding round was led by KKR, with participation from Sixth Street Growth, TenEleven, and Carrick Capital Partners.

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Storm-0249 Escalates Ransomware Attacks with ClickFix, Fileless PowerShell, and DLL Sideloading - December 09, 2025

The threat actor known as Storm-0249 is likely shifting from its role as an initial access broker to adopt a combination of more advanced tactics like domain spoofing, DLL side-loading, and fileless PowerShell execution to facilitate ransomware attacks. “These methods allow them to bypass defenses, infiltrate networks, maintain persistence, and operate undetected, raising serious concerns for

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Proofpoint Completes $1.8 Billion Acquisition of Hornetsecurity - December 09, 2025

Proofpoint said Hornetsecurity brings in nearly $200 million in annual recurring revenue, with a 20% year-over-year growth rate.

The post Proofpoint Completes $1.8 Billion Acquisition of Hornetsecurity  appeared first on SecurityWeek.

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AI vs. Human Drivers - December 09, 2025

Two competing arguments are making the rounds. The first is by a neurosurgeon in the New York Times. In an op-ed that honestly sounds like it was paid for by Waymo, the author calls driverless cars a “public health breakthrough”:

In medical research, there’s a practice of ending a study early when the results are too striking to ignore. We stop when there is unexpected harm. We also stop for overwhelming benefit, when a treatment is working so well that it would be unethical to continue giving anyone a placebo. When an intervention works this clearly, you change what you do...

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How to Streamline Zero Trust Using the Shared Signals Framework - December 09, 2025

Zero Trust helps organizations shrink their attack surface and respond to threats faster, but many still struggle to implement it because their security tools don’t share signals reliably. 88% of organizations admit they’ve suffered significant challenges in trying to implement such approaches, according to Accenture. When products can’t communicate, real-time access decisions break down. The

Google Adds Layered Defenses to Chrome to Block Indirect Prompt Injection Threats - December 09, 2025

Google on Monday announced a set of new security features in Chrome, following the company’s addition of agentic artificial intelligence (AI) capabilities to the web browser. To that end, the tech giant said it has implemented layered defenses to make it harder for bad actors to exploit indirect prompt injections that arise as a result of exposure to untrusted web content and inflict harm. Chief

STAC6565 Targets Canada in 80% of Attacks as Gold Blade Deploys QWCrypt Ransomware - December 09, 2025

Canadian organizations have emerged as the focus of a targeted cyber campaign orchestrated by a threat activity cluster known as STAC6565. Cybersecurity company Sophos said it investigated almost 40 intrusions linked to the threat actor between February 2024 and August 2025. The campaign is assessed with high confidence to share overlaps with a hacking group known as Gold Blade, which is also

Researchers Find Malicious VS Code, Go, npm, and Rust Packages Stealing Developer Data - December 09, 2025

Cybersecurity researchers have discovered two new extensions on Microsoft Visual Studio Code (VS Code) Marketplace that are designed to infect developer machines with stealer malware. The VS Code extensions masquerade as a premium dark theme and an artificial intelligence (AI)-powered coding assistant, but, in actuality, harbor covert functionality to download additional payloads, take

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Architecting Security for Agentic Capabilities in Chrome - December 08, 2025

Posted by Nathan Parker, Chrome security team

Chrome has been advancing the web’s security for well over 15 years, and we’re committed to meeting new challenges and opportunities with AI. Billions of people trust Chrome to keep them safe by default, and this is a responsibility we take seriously. Following the recent launch of Gemini in Chrome and the preview of agentic capabilities, we want to share our approach and some new innovations to improve the safety of agentic browsing.

The primary new threat facing all agentic browsers is indirect prompt injection. It can appear in malicious sites, third-party content in iframes, or from user-generated content like user reviews, and can cause the agent to take unwanted actions such as initiating financial transactions or exfiltrating sensitive data. Given this open challenge, we are investing in a layered defense that includes both deterministic and probabilistic defenses to make it difficult and costly for attackers to cause harm.

Designing safe agentic browsing for Chrome has involved deep collaboration of security experts across Google. We built on Gemini's existing protections and agent security principles and have implemented several new layers for Chrome.

We’re introducing a user alignment critic where the agent’s actions are vetted by a separate model that is isolated from untrusted content. We’re also extending Chrome’s origin-isolation capabilities to constrain what origins the agent can interact with, to just those that are relevant to the task. Our layered defense also includes user confirmations for critical steps, real-time detection of threats, and red-teaming and response. We’ll step through these layers below.

Checking agent outputs with User Alignment Critic

The main planning model for Gemini uses page content shared in Chrome to decide what action to take next. Exposure to untrusted web content means it is inherently vulnerable to indirect prompt injection. We use techniques like spotlighting that direct the model to strongly prefer following user and system instructions over what’s on the page, and we’ve upstreamed known attacks to train the Gemini model to avoid falling for them.

To further bolster model alignment beyond spotlighting, we’re introducing the User Alignment Critic — a separate model built with Gemini that acts as a high-trust system component. This architecture is inspired partially by the dual-LLM pattern as well as CaMeL research from Google DeepMind.

A flow chart that depicts the User Alignment Critic: a trusted component that vets each action before it reaches the browser.

The User Alignment Critic runs after the planning is complete to double-check each proposed action. Its primary focus is task alignment: determining whether the proposed action serves the user’s stated goal. If the action is misaligned, the Alignment Critic will veto it. This component is architected to see only metadata about the proposed action and not any unfiltered untrustworthy web content, thus ensuring it cannot be poisoned directly from the web. It has less context, but it also has a simpler job — just approve or reject an action.

This is a powerful, extra layer of defense against both goal-hijacking and data exfiltration within the action step. When an action is rejected, the Critic provides feedback to the planning model to re-formulate its plan, and the planner can return control to the user if there are repeated failures.

Enforcing stronger security boundaries with Origin Sets

Site Isolation and the same-origin policy are fundamental boundaries in Chrome’s security model and we’re carrying forward these concepts into the agentic world. By their nature, agents must operate across websites (e.g. collecting ingredients on one site and filling a shopping cart on another). But if an unrestricted agent is compromised and can interact with arbitrary sites, it can create what is effectively a Site Isolation bypass. That can have a severe impact when the agent operates on a local browser like Chrome, with logged-in sites vulnerable to data exfiltration. To address this, we’re extending those principles with Agent Origin Sets. Our design architecturally limits the agent to only access data from origins that are related to the task at hand, or data that the user has chosen to share with the agent. This prevents a compromised agent from acting arbitrarily on unrelated origins.

For each task on the web, a trustworthy gating function decides which origins proposed by the planner are relevant to the task. The design is to separate these into two sets, tracked for each session:

• Read-only origins are those from which Gemini is permitted to consume content. If an iframe’s origin isn’t on the list, the model will not see that content.
• Read-writable origins are those on which the agent is allowed to actuate (e.g., click, type) in addition to reading from.

This delineation enforces that only data from a limited set of origins is available to the agent, and this data can only be passed on to the writable origins. This bounds the threat vector of cross-origin data leaks. This also gives the browser the ability to enforce some of that separation, such as by not even sending to the model data that is outside the readable set. This reduces the model’s exposure to unnecessary cross-site data. Like the Alignment Critic, the gating functions that calculate these origin sets are not exposed to untrusted web content. The planner can also use context from pages the user explicitly shared in that session, but it cannot add new origins without the gating function’s approval. Outside of web origins, the planning model may ingest other non-web content such as from tool calls, so we also delineate those into read-vs-write calls and similarly check that those calls are appropriate for the task.

Iframes from origins that aren’t related to the user’s task are not shown to the model.

Page navigations can happen in several ways: If the planner decides to navigate to a new origin that isn’t yet in the readable set, that origin is checked for relevancy by a variant of the User Alignment critic before Chrome adds it and starts the navigation. And since model-generated URLs could exfiltrate private information, we have a deterministic check to restrict them to known, public URLs. If a page in Chrome navigates on its own to a new origin, it’ll get vetted by the same critic.

Getting the balance right on the first iteration is hard without seeing how users’ tasks interact with these guardrails. We’ve initially implemented a simpler version of origin gating that just tracks the read-writeable set. We will tune the gating functions and other aspects of this system to reduce unnecessary friction while improving security. We think this architecture will provide a powerful security primitive that can be audited and reasoned about within the client, as it provides guardrails against cross-origin sensitive data exfiltration and unwanted actions.

Transparency and control for sensitive actions

We designed the agentic capabilities in Chrome to give the user both transparency and control when they need it most. As the agent works in a tab, it details each step in a work log, allowing the user to observe the agent's actions as they happen. The user can pause to take over or stop a task at any time.

This transparency is paired with several layers of deterministic and model-based checks to trigger user confirmations before the agent takes an impactful action. These serve as guardrails against both model mistakes and adversarial input by putting the user in the loop at key moments.

First, the agent will require a user confirmation before it navigates to certain sensitive sites, such as those dealing with banking transactions or personal medical information. This is based on a deterministic check against a list of sensitive sites. Second, it’ll confirm before allowing Chrome to sign-in to a site via Google Password Manager – the model does not have direct access to stored passwords. Lastly, before any sensitive web actions like completing a purchase or payment, sending messages, or other consequential actions, the agent will try to pause and either get permission from the user before proceeding or ask the user to complete the next step. Like our other safety classifiers, we’re constantly working to improve the accuracy to catch edge cases and grey areas.

Illustrative example of when the agent gets to a payment page, it stops and asks the user to complete the final step.

Detecting “social engineering” of agents

In addition to the structural defenses of alignment checks, origin gating, and confirmations, we have several processes to detect and respond to threats. While the agent is active, it checks every page it sees for indirect prompt injection. This is in addition to Chrome’s real-time scanning with Safe Browsing and on-device AI that detect more traditional scams. This prompt-injection classifier runs in parallel to the planning model’s inference, and will prevent actions from being taken based on content that the classifier determined has intentionally targeted the model to do something unaligned with the user’s goal. While it cannot flag everything that might influence the model with malicious intent, it is a valuable layer in our defense-in-depth.

Continuous auditing, monitoring, response

To validate the security of this set of layered defenses, we’ve built automated red-teaming systems to generate malicious sandboxed sites that try to derail the agent in Chrome. We start with a set of diverse attacks crafted by security researchers, and expand on them using LLMs following a technique we adapted for browser agents. Our continuous testing prioritizes defenses against broad-reach vectors such as user-generated content on social media sites and content delivered via ads. We also prioritize attacks that could lead to lasting harm, such as financial transactions or the leaking of sensitive credentials. The attack success rate across these give immediate feedback to any engineering changes we make, so we can prevent regressions and target improvements. Chrome’s auto-update capabilities allow us to get fixes out to users very quickly, so we can stay ahead of attackers.

Collaborating across the community

We have a long-standing commitment to working with the broader security research community to advance security together, and this includes agentic safety. We’ve updated our Vulnerability Rewards Program (VRP) guidelines to clarify how external researchers can focus on agentic capabilities in Chrome. We want to hear about any serious vulnerabilities in this system, and will pay up to $20,000 for those that demonstrate breaches in the security boundaries. The full details are available in VRP rules.

Looking forward

The upcoming introduction of agentic capabilities in Chrome brings new demands for browser security, and we've approached this challenge with the same rigor that has defined Chrome's security model from its inception. By extending some core principles like origin-isolation and layered defenses, and introducing a trusted-model architecture, we're building a secure foundation for Gemini’s agentic experiences in Chrome. This is an evolving space, and while we're proud of the initial protections we've implemented, we recognize that security for web agents is still an emerging domain. We remain committed to continuous innovation and collaboration with the security community to ensure Chrome users can explore this new era of the web safely.

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Experts Confirm JS#SMUGGLER Uses Compromised Sites to Deploy NetSupport RAT - December 08, 2025

Cybersecurity researchers are calling attention to a new campaign dubbed JS#SMUGGLER that has been observed leveraging compromised websites as a distribution vector for a remote access trojan named NetSupport RAT. The attack chain, analyzed by Securonix, involves three main moving parts: An obfuscated JavaScript loader injected into a website, an HTML Application (HTA) that runs encrypted

⚡ Weekly Recap: USB Malware, React2Shell, WhatsApp Worms, AI IDE Bugs & More - December 08, 2025

It’s been a week of chaos in code and calm in headlines. A bug that broke the internet’s favorite framework, hackers chasing AI tools, fake apps stealing cash, and record-breaking cyberattacks — all within days. If you blink, you’ll miss how fast the threat map is changing. New flaws are being found, published, and exploited in hours instead of weeks. AI-powered tools meant to help developers

Schneier on Security

Security news and analysis by Bruce Schneier

Substitution Cipher Based on The Voynich Manuscript - December 08, 2025

Here’s a fun paper: “The Naibbe cipher: a substitution cipher that encrypts Latin and Italian as Voynich Manuscript-like ciphertext“:

Abstract: In this article, I investigate the hypothesis that the Voynich Manuscript (MS 408, Yale University Beinecke Library) is compatible with being a ciphertext by attempting to develop a historically plausible cipher that can replicate the manuscript’s unusual properties. The resulting cipher­a verbose homophonic substitution cipher I call the Naibbe cipher­can be done entirely by hand with 15th-century materials, and when it encrypts a wide range of Latin and Italian plaintexts, the resulting ciphertexts remain fully decipherable and also reliably reproduce many key statistical properties of the Voynich Manuscript at once. My results suggest that the so-called “ciphertext hypothesis” for the Voynich Manuscript remains viable, while also placing constraints on plausible substitution cipher structures...

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Researchers Uncover 30+ Flaws in AI Coding Tools Enabling Data Theft and RCE Attacks - December 06, 2025

Over 30 security vulnerabilities have been disclosed in various artificial intelligence (AI)-powered Integrated Development Environments (IDEs) that combine prompt injection primitives with legitimate features to achieve data exfiltration and remote code execution. The security shortcomings have been collectively named IDEsaster by security researcher Ari Marzouk (MaccariTA). They affect popular

Critical React2Shell Flaw Added to CISA KEV After Confirmed Active Exploitation - December 06, 2025

The U.S. Cybersecurity and Infrastructure Security Agency (CISA) on Friday formally added a critical security flaw impacting React Server Components (RSC) to its Known Exploited Vulnerabilities (KEV) catalog following reports of active exploitation in the wild. The vulnerability, CVE-2025-55182 (CVSS score: 10.0), relates to a case of remote code execution that could be triggered by an

Schneier on Security

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Friday Squid Blogging: Vampire Squid Genome - December 05, 2025

The vampire squid (Vampyroteuthis infernalis) has the largest cephalopod genome ever sequenced: more than 11 billion base pairs. That’s more than twice as large as the biggest squid genomes.

It’s technically not a squid: “The vampire squid is a fascinating twig tenaciously hanging onto the cephalopod family tree. It’s neither a squid nor an octopus (nor a vampire), but rather the last, lone remnant of an ancient lineage whose other members have long since vanished.”

As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered...

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Zero-Click Agentic Browser Attack Can Delete Entire Google Drive Using Crafted Emails - December 05, 2025

A new agentic browser attack targeting Perplexity’s Comet browser that’s capable of turning a seemingly innocuous email into a destructive action that wipes a user’s entire Google Drive contents, findings from Straiker STAR Labs show. The zero-click Google Drive Wiper technique hinges on connecting the browser to services like Gmail and Google Drive to automate routine tasks by granting them

Critical XXE Bug CVE-2025-66516 (CVSS 10.0) Hits Apache Tika, Requires Urgent Patch - December 05, 2025

A critical security flaw has been disclosed in Apache Tika that could result in an XML external entity (XXE) injection attack. The vulnerability, tracked as CVE-2025-66516, is rated 10.0 on the CVSS scoring scale, indicating maximum severity. “Critical XXE in Apache Tika tika-core (1.13-3.2.1), tika-pdf-module (2.0.0-3.2.1) and tika-parsers (1.13-1.28.5) modules on all platforms allows an

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In Other News: X Fined €120 Million, Array Flaw Exploited, New Iranian Backdoor - December 05, 2025

Other noteworthy stories that might have slipped under the radar: Akamai patches HTTP smuggling vulnerability, Claude Skills used to execute ransomware, PickleScan flaws.

The post In Other News: X Fined €120 Million, Array Flaw Exploited, New Iranian Backdoor appeared first on SecurityWeek.

Cloudflare Outage Caused by React2Shell Mitigations - December 05, 2025

The critical React vulnerability has been exploited in the wild by Chinese and other threat actors.

The post Cloudflare Outage Caused by React2Shell Mitigations appeared first on SecurityWeek.

Imper.ai Emerges From Stealth Mode With $28 Million in Funding - December 05, 2025

The cybersecurity startup detects impersonation risk in real-time, across video, phone, and chat communication.

The post Imper.ai Emerges From Stealth Mode With $28 Million in Funding appeared first on SecurityWeek.

US Organizations Warned of Chinese Malware Used for Long-Term Persistence - December 05, 2025

Warp Panda has been using the BrickStorm, Junction, and GuestConduit malware in attacks against US organizations.

The post US Organizations Warned of Chinese Malware Used for Long-Term Persistence appeared first on SecurityWeek.

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Intellexa Leaks Reveal Zero-Days and Ads-Based Vector for Predator Spyware Delivery - December 05, 2025

A human rights lawyer from Pakistan’s Balochistan province received a suspicious link on WhatsApp from an unknown number, marking the first time a civil society member in the country was targeted by Intellexa’s Predator spyware, Amnesty International said in a report. The link, the non-profit organization said, is a “Predator attack attempt based on the technical behaviour of the infection

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Lumia Security Raises $18 Million for AI Security and Governance - December 05, 2025

The startup will invest in expanding its engineering and research teams, deepening product integrations, and scaling go-to-market efforts.

The post Lumia Security Raises $18 Million for AI Security and Governance appeared first on SecurityWeek.

Aisuru Botnet Powers Record DDoS Attack Peaking at 29 Tbps - December 05, 2025

Cloudflare recently mitigated a new record-breaking Aisuru attack that peaked at 14.1 Bpps.

The post Aisuru Botnet Powers Record DDoS Attack Peaking at 29 Tbps appeared first on SecurityWeek.

Helmet Security Emerges From Stealth Mode With $9 Million in Funding - December 05, 2025

Helmet Security has built an end-to-end platform that secures the infrastructure for agentic AI communication.

The post Helmet Security Emerges From Stealth Mode With $9 Million in Funding appeared first on SecurityWeek.

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JPCERT Confirms Active Command Injection Attacks on Array AG Gateways - December 05, 2025

A command injection vulnerability in Array Networks AG Series secure access gateways has been exploited in the wild since August 2025, according to an alert issued by JPCERT/CC this week. The vulnerability, which does not have a CVE identifier, was addressed by the company on May 11, 2025. It’s rooted in Array’s DesktopDirect, a remote desktop access solution that allows users to securely access