Threats tagged 'cloud'

Microsoft fixed critical vulnerabilities across Azure, Entra, and SharePoint, while Apple patched a high-severity authentication bypass. The post Microsoft, Apple Release Fresh Security Updates appeared first on SecurityWeek .

Bulletin ID: 2026-077-AWS Scope: AWS Content Type: Important (requires attention) Publication Date: 08/06/2026 11:00 AM PDT Description: Strands Agents is an open-source SDK for building AI agents. The strands-agents-tools package provides pre-built tools for use with the SDK, including the mongodb_memory, elasticsearch_memory, and mem0_memory tools for storing and retrieving agent memories. We identified CVE-2026-19111, an insecure direct object reference (IDOR) issue in the mongodb_memory, elasticsearch_memory, and mem0_memory tools. Each tool uses a namespace field as the sole tenant-isolation key, and that namespace was exposed as a parameter the large language model (LLM) could control through the tool schema. A crafted prompt could cause a tool to emit a call with a forged namespace, allowing a remote authenticated user to read, modify, or delete memories belonging to other tenants, or to inject false memories into another tenant's namespace. The standalone mongodb_memory and elasticsearch_memory functions additionally exposed connection parameters, which could allow the memory layer to be redirected to an actor-specified cluster. Impacted versions: < 0.8.3 Please refer to the article below for the most up-to-date and complete information related to this AWS Security Bulletin.

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

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

When you learn that a compromised package executed on one of your build hosts, muscle memory takes over: revoke the npm token, rotate the GitHub PAT, cycle the cloud keys. That reflex has been correct in almost every supply-chain incident I have worked. In the keyv/cacheable compromise that has been unfolding since yesterday, it is the one thing you should not do first — because revoking the stolen token is exactly what arms the payload.

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

In this article Attack chain overview Mitigation and protection guidance Indicators of compromise (IOC) Microsoft Defender XDR detections Advanced hunting queries Learn more Microsoft Threat Intelligence identified a large-scale npm supply chain attack affecting more than 400 packages across multiple unrelated publishers, including packages associated with major enterprise software ecosystems such as keyv, flat-cache, cache-manager, and others. The malicious releases contain a Mini Shai-Hulud variant, a self-propagating credential-stealing worm delivered through a large, heavily obfuscated Bun-based JavaScript payload. The malware typically executes automatically through an npm preinstall lifecycle hook before package installation completes. Once executed, the malware searches developer workstations and continuous integration and continuous delivery (CI/CD) environments for npm, GitHub, cloud, and infrastructure credentials. It uses recovered identities to authenticate to npm, GitHub, Amazon Web Services (AWS), Kubernetes, and HashiCorp Vault, enabling it to enumerate packages, repositories, workflow secrets, cloud parameters, and secret-store values. Collected data is encrypted and transmitted through an attacker-controlled HTTPS endpoint, with GitHub repositories serving as a fallback exfiltration channel. The payload’s most significant capability is automated propagation. After obtaining an npm publishing token, it enumerates packages available to the compromised identity, downloads their latest tarballs, inserts the malware and setup loader, adds a preinstall hook, increments the patch version, and republishes the modified packages. The malware can also use stolen GitHub credentials to inject Claude and Visual Studio Code configuration files into repositories, establishing persistence and creating an additional developer-to-developer infection path. In this blog, we’re sharing our analysis of this supply chain attack, along with protection, detection, amd hunting guidance. Organizations that installed an affected package with lifecycle scripts enabled should treat the associated developer workstation or build runner as potentially compromised. Investigations should prioritize credentials accessible to the affected identity, unauthorized npm releases, unexpected repository or workflow modifications, suspicious cloud and secret-store access, and artifacts produced by affected build systems. Organizations should revoke and rotate exposed credentials from a known-clean environment and rebuild affected systems and downstream artifacts from trusted sources. Attack chain overview The campaign appeared as a rapid sequence of unauthorized patch releases across more than 400 npm packages maintained by otherwise unrelated publishers. Many malicious versions had no corresponding source-code commit, pull request, tag, or legitimate release, indicating that the attackers modified and published package tarballs directly rather than compromising each public source repository. Affected releases typically added a preinstall lifecycle script that launched a malicious file, setup.mjs, contained within the package, which launched the large, obfuscated Bun JavaScript bundle included in the package. Because npm runs preinstall scripts before installation completes, the payload could execute on developer workstations and build runners before application tests or conventional security checks began. After execution, the malware performs the following actions: Determines whether it is running on a developer workstation or in a CI/CD environment. On workstations, it detaches itself to continue after installation; on CI/CD systems, it remains in the active job to access workflow secrets, runner credentials, and OpenID Connect (OIDC) publishing permissions. Both paths could support further package or repository propagation when suitable credentials are found. Collects credentials from local files, environment variables, command-line tools, and GitHub A…

Bulletin ID: 2026-074-AWS Scope: AWS Content Type: Important (requires attention) Publication Date: 08/04/2026 12:30 PM PDT Description: Kiro is an agentic IDE and command-line interface users install on their desktop. We identified CVE-2026-18656 and CVE-2026-18657, an issue where an uncontrolled search path element on Windows might allow an actor to execute arbitrary code via a maliciously crafted project directory containing a planted executable that is resolved before the system PATH when a local user opens the directory. Impacted versions: - Kiro IDE for Windows between versions 1.0.0 through 1.0.212 - Kiro CLI for Windows prior to v2.10.0 Please refer to the article below for the most up-to-date and complete information related to this AWS Security Bulletin.

The calculus of cybersecurity has changed. AI is reshaping how organizations build, deploy, operate, and defend digital systems. AI-powered development tools, agents, and autonomous workflows are accelerating innovation but they are also introducing new attack surfaces, new trust boundaries, and new security challenges. Microsoft has long helped organizations secure their digital estates using Zero Trust principles . That leadership was recently recognized by KuppingerCole analysts, which named Microsoft as the Overall Leader in its Zero Trust Platform Leadership Compass , ranking Microsoft highest for both product and innovation leadership. Learn more about Zero Trust for AI As organizations accelerate AI adoption, secure software development becomes more important than ever. That’s why we are expanding the Zero Trust for AI strategy with two major additions: a new AI-focused Zero Trust Assessment experience and a new DevSecOps pillar in the Zero Trust Workshop . Together, they help organizations get ready for AI by assessing exposure, risks, prioritizing remediation, and securing AI-enabled development from source code to deployment. Zero Trust Assessment tool updates: New set of assessment checks for AI, Security Operations (SecOps), and Infrastructure. Zero Trust Workshop updates: New dedicated pillar focused on Developer Security (DevSecOps) and additional guidance for AI Memory. New guidance: New practical guidance for security practitioners and a new e-book titled Zero Trust for AI, rebuilding security controls for autonomous and agentic systems . This builds directly on the Zero Trust for AI strategy announced at RSA Conference 2026 and moves the conversation from architecture to implementation. If that announcement was about establishing Zero Trust for AI, this one is about operationalizing it: giving security, engineering, and platform teams the specific controls they need to act. To learn more about our work in applying Zero Trust for AI and agents watch this Microsoft Mechanics video: New AI pillar in Zero Trust Assessment tool The Zero Trust Assessment provides an automated view of security posture by evaluating tenant configuration and activity signals across the environment and translating those findings into prioritized recommendations. As organizations adopt AI agents, Copilots, developer tools, and autonomous workflows, the Assessment helps security and platform teams establish a baseline, measure progress, and identify gaps across both traditional and AI-powered environments. It now includes expanded coverage with new pillars for AI, Security Operations, and Infrastructure (in addition to existing Identity, Devices, Network, and Data pillars), with Zero Trust for AI-focused checks that help organizations evaluate the controls required for secure AI adoption. Additionally, enhanced reporting delivers both practitioner-level guidance and executive-ready summaries that communicate risk, progress, and next steps. Results map directly into the Zero Trust Workshop’s First, Then, Next framework, transforming assessment findings into a prioritized roadmap for remediation and implementation. Together, the Assessment and Workshop help organizations move from understanding risk to executing a structured plan for continuous improvement across their Zero Trust and AI security journey. Explore the Zero Trust Assessment updates What’s New in the Zero Trust Workshop AI is fundamentally changing software development. Developers increasingly rely on AI assistants to generate code, recommend packages, create infrastructure configurations, and automate testing. While these capabilities accelerate delivery, they also amplify the consequences of governance gaps, excessive permissions, insecure dependencies, and compromised supply chains. That is why Microsoft is introducing a new DevSecOps pillar (with 15 control groups and 91 tasks that help teams apply Zero Trust from source code to cloud deployment) in the Zero Trust Workshop.…

The news coverage surrounding the breach of the AI platform Hugging Face by OpenAI’s autonomous agents reads like a scene straight out of a Terminator movie (apparently, a prequel). Yet for enterprise security teams — even those that don’t develop or deploy artificial intelligence — the detailed incident report published by Hugging Face provides a critical operational roadmap. The incident needs to be evaluated on the basis of a single, fundamental question: “Which organizational security flaws, missing controls, configurations, or technologies allowed this attack to succeed?” What happened? During cyber-capability testing of OpenAI’s advanced AI models against the ExploitGym benchmark, an agent found a way to break out of its confinement, reached the internet, and breached the infrastructure of several companies — one of them being Hugging Face. The model reasoned that it could find solutions to the benchmark challenges on these external systems. Dozens of articles have since covered these incidents in detail , so no need to go over that here. What truly matters is what transpired within Hugging Face’s systems between July 9 and 13 while the AI agent operated unchecked inside. The Hugging Face incident report includes an interactive attack timeline, so we’ll just list the key stages. A malicious configuration in a dataset uploaded by the agent allowed it to exfiltrate credentials for a worker pod , and execute code within it. The agent then exploited cloud environment metadata and escaped the privileged pod to obtain root-level access on the host. It retrieved a substantial number of secrets from storage and used a stolen VPN key and shared cluster administrator credentials to pivot deeper into the internal network and source code repository before the Hugging Face security team blocked its access. How significant is the fact that this was next-generation AI? Regardless of the specific area of ​​activity of a company, tomorrow it may become a target of human attackers, fully autonomous systems, or AI agents manually controlled by human hackers. Many AI practitioners have rushed to dismiss this incident based on assumptions that OpenAI will never allow its tech to get into serious hacking. However, security researchers have argued for months that even currently available open-source models can be used to launch both offensive research and real-world attacks. Human oversight, while still a requirement, can be minimal. Even mid-tier models can easily iterate through a dozen vulnerabilities, inventory a compromised infrastructure, and quickly figure out how to expand their reach across a network. Defenders must analyze incidents like this in detail, map the key findings to their own environments, and adapt security controls to counter both stealthy human actors and rapid, noisy AI agents. Three distinguishing features of AI-powered attacks The techniques detailed in the Hugging Face report are not novel — the agent didn’t invent anything new. However, three factors regarding the attack’s speed and scale fundamentally shift the economics for both attackers and defenders: Trial and error becomes significantly cheaper. Where a human hacker might test five attack vectors, an agent can iterate through five hundred. Scenarios that security teams previously dismissed as “theoretically possible, but impractical and unlikely” and placed them on the backlog can now become active threats. Attack execution and incident response windows shrink. High-speed attacks are not unheard of, while some ransomware operators achieve compromise within hours even without AI. However, this accelerated pace will likely become the new baseline in cybersecurity, as demonstrated by the agent obtaining admin privileges at Hugging Face within 13 hours. Numerous alerts and log entries generated by the agent’s trial-and-error attempts can both help and hinder attackers as well as defenders. This noise can serve both as an indicator for threat detection, and as cam…

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

Bulletin ID: 2026-072-AWS Scope: AWS Content Type: Important (requires attention) Publication Date: 08/03/2026 13:30 PM PDT Description: Strands Agents is an open-source SDK for building AI agents. The strands-agents-tools package provides pre-built tools for use with the SDK, including the shell tool for executing operating system commands on the agent's host. We identified CVE-2026-18733. The shell tool includes a human consent gate that prompts the operator to approve commands before they run. The tool also exposed a non_interactive parameter in the input schema that the large language model (LLM) could control. A crafted prompt, for example one delivered through untrusted content the agent reads (indirect prompt injection), could set non_interactive to true, which bypasses the consent gate and allows arbitrary operating system commands to execute on the agent's host without operator approval. Impacted versions: < 0.8.0 Please refer to the article below for the most up-to-date and complete information related to this AWS Security Bulletin.

Bulletin ID: 2026-071-AWS Scope: AWS Content Type: Important (requires attention) Publication Date: 08/03/2026 12:30 PM PDT Description: AWS Command Line Interface (AWS CLI) is a unified tool to manage AWS services from the command line. We identified CVE-2026-18654, an issue where the EMR SSH helper commands (aws emr ssh, aws emr socks, aws emr put, aws emr get) disabled SSH host key verification, which might allow man-in-the-middle actors to intercept SSH sessions and file transfers via network positioning between the client and the EMR cluster endpoint. Impacted versions: - AWS CLI v1 <= 1.45.27 - AWS CLI v2 <= 2.35.2 Please refer to the article below for the most up-to-date and complete information related to this AWS Security Bulletin.

Bulletin ID: 2026-070-AWS Scope: AWS Content Type: Important (requires attention) Publication Date: 08/03/2026 12:00 PM PDT Description: AWS Amazon MQ MCP Server (awslabs.amazon-mq-mcp-server) is a Model Context Protocol server that enables AI assistants to interact with Amazon MQ message brokers. We identified CVE-2026-18655, an improper restriction of intended endpoints in the RabbitMQ broker connection tools of the Amazon MQ MCP Server (awslabs.amazon-mq-mcp-server) before 2.0.24 that may allow a remote unauthenticated actor to obtain Amazon MQ for RabbitMQ broker credentials or OAuth access tokens sent to a crafted endpoint controlled through a broker hostname introduced in the MCP client context. Impacted versions: <= 2.0.23 Please refer to the article below for the most up-to-date and complete information related to this AWS Security Bulletin.

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

Pharmaceutical company Amgen says it suffered a data breach after threat actors stole corporate data and patient information stored in multiple cloud systems operated by third-party service providers. [...]

Bulletin ID: 2026-085-AWS Scope: AWS Content Type: Important (requires attention) Publication Date: 08/20/2026 13:30 PM PDT Description: Improper input validation in the Time Series Visual Builder (TSVB) plugin in OpenSearch Dashboards before 3.8 allows a remote authenticated user with standard data access permissions to execute arbitrary code on the server by sending a crafted JSON payload to the metrics visualization API endpoint. To mitigate this issue, users should upgrade to OpenSearch Dashboards 3.8 or later. Impacted products and versions: - OpenSearch-Dashboards (open-source, self-managed): >=3.0.0, =3.0.0, <3.8.0 Please refer to the article below for the most up-to-date and complete information related to this AWS Security Bulletin.

Overview Two vulnerabilities in the REST API were found in Golf Compete foreUP. The first exposes the merchant, Finix, API credentials directly in customer record responses, allowing any user to obtain and use the payment processor account. The second is a missing object-level authorization check, which lets a user retrieve any other customer's full profile, payment token, and transaction history by changing the golfer_id in the request path. Description Golf Compete foreUP provides cloud-based golf course management software to over 2,000 golf courses. They offer tools that allow the management of customers, inventory, tee times, food & beverages, marketing, billing, etc. The vulnerabilities identified are listed below. CVE-2026-15657 A vulnerability in the foreUP customer REST API exposes merchant credentials. Each customer record response includes the facility’s merchant API credentials in cleartext, exposing the following details: finix_username finix_password finix_merchant_id Merchant credentials are identical across for customers at the same facility and are actively used by the backend to register new payment instruments. Any authenticated customer can obtain the facility’s merchant credentials when querying own record. Combined with the second vulnerability described below, an attacker can retrieve merchant credentials from any customer record at the facility. CVE-2026-15658 A missing object-level authorization also known as BOLA (Broken Object Level Authorization) and IDOR (Insecure Direct Object References) in the REST API endpoint returns the record identified by golfer_id without verifying ownership. A caller can substitute any golfer_id while using their own valid JSON Web Token (JWT) and receive another customer's full profile, including the following details: Name, email, phone numbers, date of birth, address Free‑text household relationship notes Finix payment‑instrument tokens Dwolla bank funding‑source tokens Billing and transaction history Impact With a single valid low‑privilege foreUP customer account, someone can perform the following actions: 1. Retrieve any customer’s full profile and contact data 2. Access stored card tokens and Dwolla ACH funding-source tokens 3. Enumerate and view full billing and transaction history for any customer 4. Obtain live Finix merchant API credentials for the facility Also, because the web API is shared by all tenants, all facilities using foreUP are affected, meaning that a customer from facility A could query merchant information from facility B. Solution On 07/26/2026, foreUP confirmed that all vulnerabilities in this report have been remediated. Users should remain aware of increased phishing and identity theft risks and monitor their accounts for suspicious activity. Acknowledgements Thank you to Eric Mead for reporting this vulnerability. This document was written by Bob Kemerer. Vendor Information One or more vendors are listed for this advisory. Please reference the full report for more information. References https://owasp.org/API-Security/editions/2023/en/0xa1-broken-object-level-authorization/ https://owasp.org/www-project-web-security-testing-guide/latest/4-Web_Application_Security_Testing/12-API_Testing/02-API_Broken_Object_Level_Authorization https://portswigger.net/web-security/access-control/idor https://owasp.org/www-project-web-security-testing-guide/latest/4-Web_Application_Security_Testing/05-Authorization_Testing/04-Testing_for_Insecure_Direct_Object_References Other Information CVE IDs: CVE-2026-15657 CVE-2026-15658 Date Public: 2026-07-30 Date First Published: 2026-07-30 Date Last Updated: 2026-07-30 15:12 UTC Document Revision: 1 About vulnerability notes Contact us about this vulnerability Provide a vendor statement

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

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