Analyzing data with ChatGPT

Summary: ChatGPT can analyze data files (like CSV or Excel spreadsheets) by letting you upload them and ask questions in plain language, helping you explore raw data and find insights without building formulas or dashboards manually. The tool is most useful early in analysis, when you're discovering patterns and anomalies, and it can generate visualizations and summaries to share with others. To get reliable results, you should frame your decision clearly, provide context about your data, ask for structured approaches rather than just answers, and verify key numbers before acting on the findings.


ChatGPT for finance teams

Summary: ChatGPT can help finance teams reduce overhead by organizing messy data, drafting reports, and standardizing recurring tasks like variance analysis and forecasting. Rather than replacing financial judgment, it speeds up formatting, rewriting, and workflow setup by structuring problems, improving clarity in communication, and creating consistent templates that teams can reuse across cycles.

Solution: N/A -- no mitigation discussed in source.


Working with files in ChatGPT

Summary: ChatGPT allows you to upload various file types (CSV, XLSX, PDF, DOCX, images, and more) directly into conversations to analyze, edit, and generate content without switching applications. You can ask the AI to summarize reports, visualize data, rewrite documents, or extract information, and some versions support apps that let ChatGPT access third-party tools for additional context.


Writing with ChatGPT

Summary: This document explains how to use ChatGPT for workplace writing tasks like drafting emails, reports, and announcements. ChatGPT works best when you give it clear goals, raw material (like notes or bullet points), specific constraints (such as word limits or tone), and iterate with targeted feedback rather than asking for completely new drafts each time.


ChatGPT for customer success teams

Summary: This is a marketing document from OpenAI describing how ChatGPT can help customer success teams (people who manage client relationships and ensure clients get value from software) reduce administrative work by organizing scattered customer information into structured outputs like plans, summaries, and follow-up messages. The document outlines use cases such as onboarding, account health monitoring, meeting preparation, and renewals, emphasizing that ChatGPT works best when teams use it both for research (understanding account situations) and content creation (communicating plans clearly).


Using projects in ChatGPT

Summary: ChatGPT Projects are dedicated spaces that let you organize chats, files, instructions, and background information for ongoing work in one place, so you don't have to repeat context or search through old conversations. Projects are most useful for work that continues over time, like research, writing with multiple drafts, or shared collaboration, while quick single tasks may not need a project. On some plans, you can invite other people to collaborate and use project-only memory to keep one area of work separate from others.


Creating images with ChatGPT

Summary: ChatGPT can generate original images from text descriptions, allowing users to quickly create and iterate on visual concepts. To get good results, write clear prompts (1-3 sentences) that specify the image's purpose, main subject, setting, and visual style, using direct language like 'soft natural light from the left' rather than vague phrases. The best way to improve images is through small, targeted revisions focusing on one element at a time, with clear spatial language and specific instructions for text or layout details.


Research with ChatGPT

Summary: ChatGPT offers two web search features for research: search retrieves current facts and recent information quickly, while deep research (agentic research, meaning the AI actively plans and executes multi-step exploration) conducts thorough analysis of complex questions by searching, evaluating sources, and synthesizing findings across multiple web sources. Both features provide citations to original sources and help users explore topics more efficiently than traditional browsing.


Applications of AI at OpenAI

Summary: OpenAI offers AI capabilities through two main channels: direct consumer products like ChatGPT (a conversational tool for writing, learning, and problem-solving) and Codex (a code-focused assistant), plus APIs (interfaces that let developers integrate AI into their own applications). OpenAI's goal is to make these powerful AI tools useful, safe, and accessible to individuals, teams, and organizations.


ChatGPT for operations teams

Summary: This is a guide from OpenAI about using ChatGPT to help operations teams organize and streamline their work. ChatGPT acts like an automated assistant that takes messy information from many sources (notes, messages, trackers) and turns it into clear summaries, decision lists, and standardized documents, so teams spend less time gathering information and more time executing tasks.


ChatGPT for research

Summary: This is a guide from OpenAI on using ChatGPT as a research tool to help answer questions and make decisions faster. ChatGPT can gather information from multiple sources, organize findings with citations, and produce structured reports like briefs or comparison tables. The tool offers two approaches: a quick 'Search' mode for fast answers, and a 'Deep research' mode for complex questions that need multiple investigation steps.


Responsible and safe use of AI

Summary: Large language models (LLMs, AI systems trained on vast amounts of text to predict and generate human-like language) like ChatGPT can help with tasks like drafting and summarizing, but they may produce incorrect information or outdated answers since they rely on patterns in their training data rather than real-time information. To use these tools safely, you should verify important facts with trusted sources, check for bias in outputs, seek advice from qualified professionals for legal or medical decisions, and be transparent about your AI use in work or school settings.

Solution: The source mentions several practices to mitigate risks: enable search or deep research features 'so ChatGPT can pull information from current sources' for up-to-date answers, always double-check critical facts with trusted sources, review outputs carefully for bias, use the thumbs-down button to flag errors, and seek expert review from qualified professionals for legal, medical, or financial matters. Additionally, keep conversation links or logs for transparency about how ChatGPT contributed to your work, and obtain consent before recording or sharing others' data.


ChatGPT for managers

Summary: This content is a reference guide showing how ChatGPT can assist managers across ten different job areas, from strategy planning to crisis management. For each area (like hiring, performance reviews, or decision-making), it lists example scenarios and the types of documents or frameworks ChatGPT can help produce. This is a tool overview, not a discussion of AI risks or technical issues.


ChatGPT for marketing teams

Summary: This document describes how marketing teams can use ChatGPT, an AI language model, to speed up their work across campaigns, content creation, and performance analysis. ChatGPT helps teams move from initial ideas through drafting and launch by organizing scattered inputs into clear messaging, generating content variations, and summarizing performance data. The tool is most effective when treated as a thinking partner for iterative refinement rather than a one-time solution, with human judgment applied for final decisions.


ChatGPT for sales teams

Summary: This document outlines how ChatGPT can assist sales teams by generating helpful outputs for various stages of the sales process, from initial prospecting and research through deal closure. It covers practical applications like creating account briefs, discovery guides, meeting agendas, email sequences, proposals, and objection-handling talk tracks across eight common sales scenarios.


Prompting fundamentals

Summary: Prompt engineering is the process of designing and refining your input to help ChatGPT give better answers. The document explains that clear prompts work best when you specify what you need, provide relevant context, describe the desired output format, and break complex tasks into smaller steps. There is no single perfect way to write a prompt, so experimentation and iteration help you discover how to use AI most effectively.


AI fundamentals

Summary: AI is software that recognizes patterns and learns from data to produce useful outputs, with large language models (LLMs, systems trained on large amounts of text to generate and transform language) being a common type you interact with through tools like ChatGPT. Models go through two training stages: pre-training, where they learn general patterns from massive text datasets, and post-training, where they're refined to follow instructions reliably, communicate clearly, and handle sensitive topics carefully through safety checks. Different models are optimized for different tradeoffs, such as reasoning models designed for complex problem-solving versus non-reasoning models built for fast, straightforward tasks.


Using custom GPTs

Summary: Custom GPTs are tailored versions of ChatGPT built for specific, repeatable tasks, where you define how the GPT behaves through instructions and can add knowledge (uploaded documents) and tools like web search or data analysis. They work best when you find yourself reusing the same prompts or instructions across multiple tasks, reducing repetition and keeping context consistent. You create a custom GPT by opening the GPT builder in ChatGPT, naming it, writing clear instructions for how it should behave, and optionally uploading files or enabling features like image generation or code analysis.


Personalizing ChatGPT

Summary: OpenAI has released features that let you customize how ChatGPT behaves by using custom instructions (settings that tell ChatGPT about your role and preferred communication style) and memory (which stores information you want ChatGPT to remember across conversations). These personalization tools help ChatGPT work more like a reliable teammate by building context over time, so you don't have to repeat the same information every time you chat.


Our response to the Axios developer tool compromise

Summary: OpenAI discovered that Axios, a third-party developer library (a pre-written code package used to build software), was compromised in a software supply chain attack (where attackers infiltrate widely-used tools to affect many companies at once) on March 31, 2026, and their macOS app-signing process briefly used a malicious version. OpenAI found no evidence that user data or systems were compromised, but is revoking and updating their security certificates (digital credentials that verify software is authentic) and requiring all macOS users to update their OpenAI apps to prevent the risk of fake apps appearing legitimate. As of May 8, 2026, older versions of ChatGPT Desktop (before 1.2026.051), Codex App (before 26.406.40811), Codex CLI (before 0.119.0), and Atlas (before 1.2026.84.2) will no longer receive updates and may stop working.

Solution: Update to the latest versions of OpenAI's macOS apps through in-app update or official links. OpenAI also addressed the root cause by fixing the GitHub Actions workflow misconfiguration: the workflow previously used a floating tag instead of a specific commit hash and lacked a configured minimumReleaseAge for new packages; these have been corrected. OpenAI rotated the macOS code signing certificate, published new builds of all affected macOS products with the new certificate, and worked with Apple to prevent software notarization using the previous certificate.

OpenAI
ChatGPT Desktop
Codex
Atlas
Axios


ChatGPT has a new $100 per month Pro subscription

Summary: OpenAI has launched a new $100 per month ChatGPT Pro subscription tier that provides 5x more access to Codex (a tool that helps write code) compared to the $20 Plus plan, designed for intensive coding work. This new tier directly competes with Anthropic's Claude Max subscription at the same price point as OpenAI tries to attract users from rival AI services.

OpenAI
ChatGPT
ChatGPT Pro
Anthropic
Claude
Claude Code


Florida launches investigation into OpenAI

Summary: Florida's Attorney General has launched an investigation into OpenAI, citing concerns that the company's data and technology could be accessed by hostile foreign governments like China, and that ChatGPT has been connected to criminal activities including child exploitation and self-harm. The investigation also examines whether ChatGPT was used in connection with a shooting at Florida State University.


CVE-2026-40150: PraisonAIAgents is a multi-agent teams system. Prior to 1.5.128, the web_crawl() function in praisonaiagents/tools/web_c

Summary: PraisonAIAgents is a system that coordinates multiple AI agents working together as teams. Before version 1.5.128, the web_crawl() function didn't check URLs before fetching them, allowing attackers or malicious content to trick agents into accessing sensitive internal systems, cloud configuration data, or local files through specially crafted URLs like file:// paths.

Solution: Update PraisonAIAgents to version 1.5.128 or later, where this vulnerability is fixed.


CVE-2026-40117: PraisonAIAgents is a multi-agent teams system. Prior to 1.5.128, read_skill_file() in skill_tools.py allows reading arbi

Summary: PraisonAIAgents (a system that coordinates multiple AI agents working together) versions before 1.5.128 contain a vulnerability in the read_skill_file() function that allows reading any file from a computer's filesystem without restrictions. An attacker using prompt injection (tricking an AI by hiding instructions in its input) could exploit this to steal sensitive files, because unlike other file-reading functions in the same system, read_skill_file() lacks both boundary protections and approval requirements.


CVE-2026-40116: PraisonAI is a multi-agent teams system. Prior to 4.5.128, the /media-stream WebSocket endpoint in PraisonAI's call modu

Summary: PraisonAI versions before 4.5.128 have a security flaw in their /media-stream WebSocket endpoint (a connection protocol for real-time communication) that allows anyone to connect without proving who they are or validating they're authorized. When attackers connect, the server automatically opens a session to OpenAI's API using its own credentials, and since there are no limits on how many connections or messages are allowed, an attacker can drain the server's resources and use up the victim's OpenAI API credits.

Solution: Update PraisonAI to version 4.5.128 or later, which fixes this vulnerability.


CVE-2026-40113: PraisonAI is a multi-agent teams system. Prior to 4.5.128, deploy.py constructs a single comma-delimited string for the

Summary: PraisonAI, a system for managing multiple AI agents working together, had a vulnerability in versions before 4.5.128 where the deploy.py file didn't check if certain configuration values (openai_model, openai_key, and openai_base) contained commas before putting them into a command. Since commas are used as separators in the gcloud deployment command, an attacker could sneak extra commas into these values to inject arbitrary environment variables (settings that control how the deployed service behaves) into the cloud service.

Solution: Upgrade PraisonAI to version 4.5.128 or later, which fixes this vulnerability.


CVE-2026-40112: PraisonAI is a multi-agent teams system. Prior to 4.5.128, the Flask API endpoint in src/praisonai/api.py renders agent

Summary: PraisonAI, a system that uses multiple AI agents to work together as teams, has a vulnerability in versions before 4.5.128 where it displays agent output as HTML without properly cleaning it first. An attacker can inject malicious JavaScript code (code that runs in a web browser) through poisoned data or tricked prompts, and this code will execute when someone views the output.

Solution: Update PraisonAI to version 4.5.128 or later, which includes a fix for this vulnerability.


CVE-2026-40111: PraisonAIAgents is a multi-agent teams system. Prior to 1.5.128, he memory hooks executor in praisonaiagents passes a us

Summary: PraisonAIAgents (a system for running multiple AI agents as teams) has a critical vulnerability in versions before 1.5.128 where user-controlled commands are passed directly to subprocess.run() with shell=True (a function that executes system commands), allowing attackers to inject shell metacharacters (special characters like pipes and semicolons that the shell interprets as instructions) and run arbitrary code. An attacker who gains file-write access through prompt injection (tricking an AI by hiding malicious instructions in its input) can modify the .praisonai/hooks.json configuration file to execute malicious code automatically every time the agent runs.


GHSA-cm8v-2vh9-cxf3: OpenClaw: GIT_DIR and related git plumbing env vars missing from exec env denylist (GHSA-m866-6qv5-p2fg variant)

Summary: OpenClaw, a local AI assistant tool, had a security flaw where Git environment variables (special settings that control how Git works) were not being removed before running system commands, potentially allowing attackers to redirect Git operations to malicious locations. This vulnerability affected OpenClaw versions up to 2026.3.30.

Solution: Update OpenClaw to version 2026.4.8 or later, which patches the vulnerability by properly removing Git plumbing environment variables before executing host commands.


CVE-2026-40087: LangChain is a framework for building agents and LLM-powered applications. Prior to 0.3.84 and 1.2.28, LangChain's f-str

Summary: LangChain, a framework for building AI agents and applications powered by large language models, had a vulnerability in how it validated f-string templates (a Python feature for inserting variables into text strings). Before versions 0.3.84 and 1.2.28, certain template classes could accept and execute dangerous expressions that should have been blocked, including attribute access and nested replacement fields hidden in format specifiers, which could allow attackers to access unintended data or run unwanted code.

Solution: Update LangChain to version 0.3.84 or 1.2.28 or later, where the f-string validation has been fixed.


OpenAI looks to take on Anthropic with $100 per month ChatGPT Pro subscriptions

Summary: OpenAI announced a new $100 per month Pro subscription tier for ChatGPT that offers five times more usage of Codex (an AI-powered coding assistant that automates tasks and bug fixes for developers) compared to its $20 per month Plus plan. This move is designed to compete with Anthropic's Claude Code, which offers similar high-usage tiers at comparable price points, as coding assistants have become increasingly popular tools for software development.

OpenAI
ChatGPT
Codex
Anthropic
Claude Code


The agentic SOC—Rethinking SecOps for the next decade

Summary: The agentic SOC is a new operating model where security operations centers use AI agents (software programs that can act autonomously) and automated defenses to respond to threats faster and more independently, rather than waiting for human analysts to handle every alert. Instead of reacting to individual incidents, this approach anticipates cyberattacker movements and automatically takes defensive actions, freeing human analysts to focus on strategic decisions and deeper investigation.


CVE-2026-39981: AGiXT is a dynamic AI Agent Automation Platform. Prior to 1.9.2, the safe_join() function in the essential_abilities ext

Summary: AGiXT, a platform for automating AI agents, has a vulnerability in its safe_join() function (a tool meant to safely combine file paths) that fails to check whether file paths stay within the agent's allowed workspace. Before version 1.9.2, an authenticated attacker could use directory traversal sequences (special path tricks like '../' to navigate outside intended folders) to read, write, or delete files on the server.

Solution: Update AGiXT to version 1.9.2, where this vulnerability is fixed.


Google’s Gemini AI can answer your questions with 3D models and simulations

Summary: Google has upgraded Gemini, its AI chatbot, to generate interactive 3D models and simulations in response to user questions. Users can rotate these models, adjust sliders to change parameters, and input different values to see real-time changes in the simulation.


GHSA-3vvq-q2qc-7rmp: OpenClaw B-M3: ClawHub package downloads are not enforced with integrity verification

Summary: OpenClaw, a user-controlled local assistant, had a vulnerability where ClawHub package downloads didn't verify the integrity of downloaded files (a security check ensuring files haven't been tampered with). This meant malicious or corrupted plugin archives could be installed without detection. The vulnerability affected OpenClaw versions 2026.4.1 and earlier.

Solution: Update to OpenClaw npm package version 2026.4.8 or later. The fix is also available in the main branch at commit d7c3210cd6f5fdfdc1beff4c9541673e814354d5.


GHSA-67mf-f936-ppxf: OpenClaw `node.pair.approve` placed in `operator.write` scope instead of `operator.pairing` allows unprivileged pairing approval

Summary: OpenClaw (a local AI assistant software) had a security bug where the `node.pair.approve` function checked for `operator.write` permissions instead of the more restrictive `operator.pairing` scope, allowing users without proper authorization to approve device pairing on executive-capable nodes. This vulnerability only affects OpenClaw in its single-user trust model and does not impact multi-tenant services.

Solution: Update OpenClaw to version 2026.4.8 or later. The fix is available in the npm package and has been verified in commit d7c3210cd6f5fdfdc1beff4c9541673e814354d5 on the main branch.


GHSA-5h3f-885m-v22w: OpenClaw: Existing WS sessions survive shared gateway token rotation

Summary: OpenClaw, a local AI assistant, had a security flaw where WebSocket sessions (persistent connections that allow real-time communication between a client and server) using a shared gateway token remained active even after the token was rotated (changed to a new one). This meant that even after administrators changed the authentication token, old sessions could continue operating without re-authenticating.


GHSA-cmfr-9m2r-xwhq: OpenClaw `node.invoke(browser.proxy)` bypasses `browser.request` persistent profile-mutation guard

Summary: OpenClaw, a user-controlled local assistant, had a security flaw where `node.invoke(browser.proxy)` could bypass the `browser.request` guard and modify persistent browser profiles (stored settings that shouldn't be changed without permission). The vulnerability affected versions up to v2026.04.01.

Solution: Update to patched version `2026.4.8` or later. The fix is available in npm and was verified in commit `d7c3210cd6f5fdfdc1beff4c9541673e814354d5`.


GHSA-whf9-3hcx-gq54: OpenClaw `device.token.rotate` mints tokens for unapproved roles, bypassing device role-upgrade pairing

Summary: OpenClaw's `device.token.rotate` function had a security flaw where it could create tokens with roles (sets of permissions) that hadn't been properly approved through the required pairing process, potentially letting users gain unauthorized access levels. This vulnerability only affects OpenClaw, which is a local assistant software that runs on a user's own device.

Solution: Update OpenClaw to version 2026.4.8 or later. The fix is available in the patched npm version and was merged into the main codebase at commit d7c3210cd6f5fdfdc1beff4c9541673e814354d5.


OpenAI shelves Stargate UK in blow to Britain’s AI ambitions

Summary: OpenAI has delayed its Stargate UK project, which was a planned major investment in Britain's AI infrastructure as part of a larger UK-US deal announced last September. The company cited high energy costs and regulatory concerns as reasons for the delay, disappointing the British government which had positioned AI development as central to its economic growth strategy.


OpenAI pauses UK data centre deal over energy costs and regulation

Summary: OpenAI has paused its UK data centre project called Stargate UK, which would have built a large computing facility in Northumberland to support AI development, citing concerns about high energy costs and regulatory uncertainty. The company stated it will only move forward when conditions improve, though critics note that energy prices and UK AI regulation have not recently changed significantly. This pause is a setback for the UK government's goal to position the country as an AI leader and boost economic growth through tech investment.


GHSA-7437-7hg8-frrw: OpenClaw: HGRCPATH, CARGO_BUILD_RUSTC_WRAPPER, RUSTC_WRAPPER, and MAKEFLAGS missing from exec env denylist — RCE via build tool env injection (GHSA-cm8v-2vh9-cxf3 class)

Summary: OpenClaw, a local AI assistant tool, had a security vulnerability where certain environment variables (HGRCPATH, CARGO_BUILD_RUSTC_WRAPPER, RUSTC_WRAPPER, and MAKEFLAGS) were not blocked from being passed to system commands, allowing attackers to achieve RCE (remote code execution, where an attacker can run commands on a system they don't own) through malicious build tool settings. This vulnerability affected versions before 2026.4.8.

Solution: Update OpenClaw to version 2026.4.8 or later. The fix was released in npm version 2026.4.8 and is available on the main branch at commit d7c3210cd6f5fdfdc1beff4c9541673e814354d5.


The AI industry’s race for profits is now existential

Summary: Major AI companies like OpenAI and Anthropic face a "monetization cliff" where they must become profitable soon or risk collapse, since they've received hundreds of billions in investment but haven't generated enough revenue to justify those costs. AI agents (software programs that can perform tasks autonomously) consume far more computing power than expected, forcing these companies to make difficult choices like killing unprofitable products and restricting free access to conserve resources for their upcoming initial public offerings (IPOs, when companies sell shares to the public for the first time).

OpenAI Anthropic Claude ChatGPT Sora Codex OpenClaw


Apple Intelligence AI Guardrails Bypassed in New Attack

Summary: Researchers at RSAC found a way to bypass Apple Intelligence's guardrails (safety measures that prevent the AI from doing harmful tasks) using two techniques: the Neural Exect method and Unicode manipulation (using special characters to confuse the system). This means attackers could potentially trick Apple's AI into ignoring its safety restrictions.


Meta's long-awaited AI model is finally here. But can it make money?

Summary: Meta has released Muse Spark, its first new AI model after spending billions on hiring and infrastructure, but faces pressure to prove it can generate revenue from AI like competitors OpenAI and Google have done. The company is shifting from open-source models (like its previous Llama family) to a proprietary approach, planning to charge developers for API (application programming interface, a way for software to request data or services from other software) access after an initial preview period. Analysts believe Meta's real advantage lies not in competing with other AI labs for developers, but in using the model to improve its core business: advertising to the 3 billion monthly users of Facebook, Instagram, and WhatsApp.

Meta
Meta Platforms Inc.
Muse Spark
Llama
OpenAI
Anthropic
Google
Gemini


Iran says U.S. breached ceasefire, Anthropic's court loss, rate cut odds and more in Morning Squawk

Summary: This newsletter covers multiple topics including geopolitical tensions, AI regulation, and market movements, with a focus on Iran's ceasefire allegations against the U.S., Anthropic's court loss regarding Pentagon blacklisting over AI safeguard disagreements, and Federal Reserve expectations for interest rate cuts in 2026.


Google API Keys in Android Apps Expose Gemini Endpoints to Unauthorized Access

Summary: Researchers found that Google API keys (credentials that allow apps to access Google services) embedded in Android applications can be extracted from decompiled code (the readable version of compiled software), potentially allowing unauthorized access to Gemini endpoints (the AI service interfaces). This means attackers could use stolen keys to access Google's Gemini AI service without permission.


March 2026 Cyber Threat Landscape Shows No Relief as Ransomware Rebounds and GenAI Risks Intensify

Summary: In March 2026, organizations faced an average of nearly 2,000 cyber-attacks per week, showing a slight 4-5% decrease but remaining at historically high levels. The threat landscape continues to be driven by automation, expanded attack surfaces from cloud adoption, and risks related to GenAI (generative AI, where systems create new content from training data) usage.


OpenAI halts UK stargate project amid regulatory and energy price concerns

Summary: OpenAI has paused its Stargate project in the U.K., which was planned to deploy up to 8,000 graphics processing units (GPUs, the specialized hardware used to train and run AI models) for AI infrastructure. The company cited two main reasons: the U.K.'s high industrial energy costs and concerns about the country's regulatory environment, particularly new rules being developed around how AI models can use copyrighted work.


The Hidden Security Risks of Shadow AI in Enterprises

Summary: Shadow AI refers to AI tools that employees use without approval from their organization's IT and security teams, operating outside security oversight and creating hidden risks. Unlike shadow IT (unapproved software), shadow AI is particularly dangerous because it processes and stores sensitive data beyond security teams' visibility, leading to potential data leaks, expanded attack surfaces (new entry points for hackers), and bypassed security controls. The problem is spreading because AI tools are easy to use, instantly helpful, and many organizations lack clear policies on their use.


Master C and C++ with our new Testing Handbook chapter

Summary: Trail of Bits released a new Testing Handbook chapter focused on security code review for C and C++, covering common bug classes like memory safety issues, integer errors, and type confusion across Linux, Windows, and seccomp (secure computing mode, a Linux feature that restricts system calls) environments. They are also developing a Claude skill that uses an LLM (large language model) to automatically find bugs by running checklist-based prompts against codebases. The handbook emphasizes manual code review techniques and includes platform-specific vulnerabilities like DLL planting on Windows and sandbox bypasses in Linux seccomp filters.


Google makes it easy to deepfake yourself

Summary: YouTube Shorts is launching a new AI feature that lets creators make digital clones of themselves, called avatars, that look and sound like them and can be used in videos. The feature adds to YouTube's struggle with managing AI-generated content, including deepfakes (synthetic videos where someone's face or voice is digitally recreated to look authentic), AI slop (low-quality AI-generated content), and impersonation scams.


Gemini gets notebooks to help you organize projects

Summary: Google is adding a feature called "notebooks" to Gemini (its AI chatbot) that lets users organize files, past conversations, and custom instructions about specific topics in one place. Gemini can then use this organized information as context (background information the AI considers) when answering questions, similar to ChatGPT's Projects feature from 2024.


CyberAgent moves faster with ChatGPT Enterprise and Codex

Summary: CyberAgent, a Japanese internet company, adopted ChatGPT Enterprise and Codex to make AI a foundational technology across their organization rather than just an isolated initiative. The company faced challenges around security concerns and uncertainty about what data could safely be shared with AI tools, which slowed adoption and created inconsistent usage across departments.

Solution: CyberAgent addressed these challenges by adopting ChatGPT Enterprise, which provides enterprise-grade security features, access controls, account management, and visibility into usage that allow employees to confidently use AI. The company also established internal guidelines for handling confidential information to ensure safe and secure use, and provided ongoing training support to build a culture of responsible AI adoption.


Anthropic loses appeals court bid to temporarily block Pentagon blacklisting

Summary: A federal appeals court in Washington, D.C. denied Anthropic's request to temporarily block the Department of Defense's blacklisting of the company as a supply chain risk (a designation claiming the company's technology threatens U.S. national security). The ruling means Anthropic is excluded from DOD contracts, though a separate court earlier granted Anthropic an injunction allowing it to continue working with other government agencies while the lawsuit challenging the blacklisting continues.


OpenAI will allocate IPO shares to retail investors as it preps for debut, CFO says

Summary: OpenAI's CFO announced that the company plans to reserve shares for individual investors when it goes public through an initial public offering (IPO, the first time a private company sells shares to the public). The company saw strong demand from regular retail investors during its recent funding round and wants to ensure broad public participation in ownership, following models used by other companies like Tesla and Block.

OpenAI
ChatGPT
Tesla
SpaceX
Square/Block
JP Morgan
Morgan Stanley
Goldman Sachs


Anthropic keeps latest AI tool out of public’s hands for fear of enabling widespread hacking

Summary: Anthropic has developed an AI model called Claude Mythos that is unusually good at finding software vulnerabilities (security weaknesses in code), and it discovered thousands of these flaws in commonly-used applications that don't yet have fixes available. The company decided not to release Mythos widely to the public because they worry it could enable widespread hacking, and instead partnered with cybersecurity specialists to improve defenses before wider distribution.


Cracks in the Bedrock: Agent God Mode

Summary: Amazon Bedrock AgentCore's starter toolkit automatically creates overly broad IAM roles (identity and access management policies that control what actions software can perform) that grant a single AI agent excessive permissions across an entire AWS account, enabling an attack called Agent God Mode. If compromised, an attacker could exploit these permissions to access other agents' memories, steal container images, and extract sensitive data. AWS updated its documentation to warn that the default roles are only for development and testing, not production use.

Solution: AWS documentation was updated to include a security warning, stating that the default roles are "designed for development and testing purposes" and are not recommended for production deployment.

Amazon Bedrock
Amazon Bedrock AgentCore
AWS


GHSA-2763-cj5r-c79m: PraisonAI Vulnerable to OS Command Injection

Summary: PraisonAI has a critical vulnerability where the `execute_command` function and workflow shell execution pass user-controlled input directly to `subprocess.run()` with `shell=True`, allowing attackers to inject arbitrary shell commands through YAML workflow files, agent configurations, and LLM-generated tool calls by exploiting shell metacharacters like semicolons and pipes.

Solution: N/A -- no mitigation discussed in source.


GHSA-926x-3r5x-gfhw: LangChain has incomplete f-string validation in prompt templates

Summary: LangChain had incomplete validation of f-string templates (a Python feature for inserting variables into text) in some prompt template classes. Attackers who could control the template structure could use attribute access (like `object.field`) or indexing (like `array[0]`) to expose internal data from Python objects being formatted. This issue only affected applications that allow untrusted users to write templates, not those using hardcoded templates or only letting users provide variable values.

Solution: LangChain now applies consistent f-string safety validation across all prompt template classes. The fix rejects templates containing attribute access or indexing syntax (such as `.` or `[]`) and rejects nested replacement fields inside format specifiers (templates with `{` or `}` in the format specification part). This blocks malicious patterns while preserving normal f-string formatting features.


CVE-2026-5803: A security flaw has been discovered in bigsk1 openai-realtime-ui up to 188ccde27fdf3d8fab8da81f3893468f53b2797c. The aff

Summary: A security vulnerability (CVE-2026-5803) was found in bigsk1 openai-realtime-ui that allows attackers to perform SSRF (server-side request forgery, where an attacker tricks a server into making unwanted requests to other systems) through the API Proxy Endpoint in server.js by manipulating a query argument, and this flaw can be exploited remotely. The product uses continuous delivery with rolling releases, so specific affected versions are not documented.

Solution: Install the patch named 54f8f50f43af97c334a881af7b021e84b5b8310f to address this issue.


GHSA-4ggg-h7ph-26qr: n8n-mcp has authenticated SSRF via instance-URL header in multi-tenant HTTP mode

Summary: n8n-mcp versions 2.47.3 and earlier have an authenticated SSRF vulnerability (server-side request forgery, where an attacker tricks a server into making requests to unintended locations) in multi-tenant HTTP mode. An attacker with a valid authentication token can make the server fetch arbitrary URLs and read the responses, potentially exposing cloud credentials (like AWS IMDS), internal network services, and other sensitive data the server can access.

Solution: Upgrade to n8n-mcp 2.47.4 or later (no configuration changes required). If you cannot upgrade immediately, the source explicitly mentions three workarounds: (1) use egress filtering to block outbound traffic from the n8n-mcp container to private IP ranges (RFC1918: 10.0.0.0/8, 172.16.0.0/12, 192.168.0.0/16) and link-local 169.254.0.0/16; (2) disable multi-tenant headers by unsetting ENABLE_MULTI_TENANT and not accepting x-n8n-url / x-n8n-key headers at the reverse proxy if per-request instance switching is not needed; (3) restrict AUTH_TOKEN distribution to fully trusted operators only until you can upgrade.


CVE-2026-34724: Zammad is a web based open source helpdesk/customer support system. Prior to 7.0.1, a server-side template injection vul

Summary: Zammad, a web-based customer support system, had a server-side template injection vulnerability (a flaw where attackers can inject malicious code into templates that the server processes) in versions before 7.0.1 that could lead to RCE (remote code execution, where an attacker can run commands on a system they don't own). The vulnerability only affects systems where an attacker has administrative access to control the type_enrichment_data configuration setting.

Solution: This vulnerability is fixed in version 7.0.1. Users should upgrade to Zammad 7.0.1 or later.


GHSA-hfvc-g4fc-pqhx: opentelemetry-go: BSD kenv command not using absolute path enables PATH hijacking

Summary: OpenTelemetry's Go SDK has a PATH hijacking vulnerability (PATH hijacking is when an attacker puts a malicious program in a directory that the system searches for commands, so their fake program runs instead of the real one) on BSD and Solaris systems because the `kenv` command is called by its name alone instead of its full path. An attacker with local access can place a malicious `kenv` binary in the system's PATH, which will execute with the application's permissions when OpenTelemetry initializes.

Solution: Use the absolute path `/bin/kenv` instead of the bare command name. Change line 42 in `sdk/resource/host_id.go` from `r.execCommand("kenv", "-q", "smbios.system.uuid")` to `r.execCommand("/bin/kenv", "-q", "smbios.system.uuid")`.


GHSA-w8rr-5gcm-pp58: opentelemetry-go: OTLP HTTP exporters read unbounded HTTP response bodies

Summary: OpenTelemetry Go's OTLP HTTP exporters (tools that send trace, metric, and log data over HTTP) read entire HTTP response bodies into memory without limiting their size, which allows an attacker controlling the collector endpoint to crash the application by sending extremely large responses. This vulnerability affects three exporter components: otlptrace, otlpmetric, and otlplog.

Solution: Fixed in PR #8108 (https://github.com/open-telemetry/opentelemetry-go/pull/8108).

go.opentelemetry.io/otel/exporters/otlp/otlplog/otlploghttp@< 0.19.0 (fixed: 0.19.0)

go.opentelemetry.io/otel/exporters/otlp/otlpmetric/otlpmetrichttp@< 1.43.0 (fixed: 1.43.0)

go.opentelemetry.io/otel/exporters/otlp/otlptrace/otlptracehttp@< 1.43.0 (fixed: 1.43.0)


GHSA-qf73-2hrx-xprp: PraisonAI has sandbox escape via exception frame traversal in `execute_code` (subprocess mode)

Summary: PraisonAI's `execute_code()` function has a critical sandbox escape vulnerability in its subprocess mode. The subprocess uses a blocklist of only 11 forbidden attributes, missing four key attributes (`__traceback__`, `tb_frame`, `f_back`, `f_builtins`) that attackers can chain together through exception handling to access the real Python builtins and execute arbitrary code, completely bypassing the sandbox.

praisonaiagents@<= 1.5.114 (fixed: 1.5.115)


ReSLC: Defending backdoor attacks on intelligent vulnerability detection via redundant semantic LLM compression

Summary: This research paper describes a method called ReSLC that protects AI systems used to find software bugs from backdoor attacks, where attackers secretly embed malicious instructions into the AI's training process. The approach uses redundant semantic LLM compression (a technique that removes unnecessary information from large language models while keeping their core abilities) to make these hidden attacks harder to carry out. The work was published in July 2026 in the Journal of Information Security and Applications.


Deep learning-based sequential detection of attacks on low-Latency network services

Summary: This research paper presents a hybrid deep learning method using autoencoders (neural networks that learn to compress and reconstruct data) and transformers (AI models that process sequences of information) to detect a new type of attack called unresponsive ECN attacks on low-latency network services (systems designed to minimize delay in data transmission). The proposed method achieves over 90% accuracy in detecting these attacks while keeping false alarms below 0.01%, outperforming existing detection approaches by more than 10%.


How botnet-driven DDoS attacks evolved in 2H 2025

Summary: In the second half of 2025, DDoS attacks (distributed denial-of-service, where attackers flood a target with traffic to shut it down) became more powerful and easier to launch due to three major changes: IoT botnets (networks of hacked internet-connected devices like routers) reached attack capacities of 30 terabits per second, AI and dark-web LLMs (large language models, AI systems trained on text data) made sophisticated attacks accessible to less-skilled attackers through simple conversational prompts, and DDoS-for-hire services became more widely available. Critical infrastructure like DNS servers (systems that translate website names into IP addresses) and government and finance sectors faced sustained pressure from groups coordinating attacks across multiple countries.


Meta debuts new AI model, attempting to catch Google, OpenAI after spending billions

Summary: Meta has released Muse Spark, a new AI model designed to be small and efficient while still capable of reasoning through complex questions in science, math, and health. The model represents Meta's attempt to compete in the AI market dominated by OpenAI, Google, and Anthropic, and will be integrated into Meta's apps like Facebook, Instagram, and WhatsApp, with plans to offer API (application programming interface, a way for developers to access software features) access to external developers.


Meta is reentering the AI race with a new model called Muse Spark

Summary: Meta has launched a new AI model called Muse Spark, designed specifically to work with Meta's products like WhatsApp, Instagram, Facebook, and Messenger. The model is now available in the Meta AI app and website in the US, with plans to expand to other countries and Meta's smart glasses in the coming weeks.


Anthropic gives our cyber stocks and other big tech names an AI stamp of approval

Summary: This article appears to be a webpage footer or navigation section from CNBC rather than substantive content about AI security or technology. It does not contain specific information about an AI or LLM-related issue, vulnerability, or technical problem.


GHSA-5mwj-v5jw-5c97: LobeHub: Unauthenticated authentication bypass on `webapi` routes via forgeable `X-lobe-chat-auth` header

Summary: LobeHub's webapi routes use a client-controlled header called `X-lobe-chat-auth` for authentication, but it's only XOR-obfuscated (a simple reversible encoding) with a hardcoded key that's visible in the code. An attacker can forge this header to bypass authentication and access protected routes like chat, model listing, and image generation without logging in, potentially using the server's API credentials or impersonating other users.

Solution: Update to LobeHub version 2.1.48 or later, which patches this vulnerability. According to the advisory, the fix involves: stopping use of `X-lobe-chat-auth` as an authentication token, removing the simple apiKey truthiness check as an auth decision, and requiring a real server-validated session, OIDC token (a standard authentication protocol), or validated API key for all protected webapi routes. If client payloads are still needed, they should be signed server-side with an HMAC (a cryptographic signature) or replaced with a normal session-bound backend lookup.


GHSA-w8wv-vfpc-hw2w: NiceGUI: Upload filename sanitization bypass via backslashes allows path traversal on Windows

Summary: NiceGUI has a security flaw where file upload names aren't properly cleaned on Windows. An attacker can use backslashes in filenames to bypass the sanitization check, which only recognizes forward slashes as path separators. This allows them to write files outside the intended upload folder, potentially overwriting important files or running malicious code. Linux and macOS are not affected because they treat backslashes as regular characters in filenames.


The next phase of enterprise AI

Summary: OpenAI reports that enterprise AI adoption has reached a critical phase, with enterprise revenue now exceeding 40% of their business and AI systems handling real work across major companies like Goldman Sachs and Uber. The company is positioning itself as the core infrastructure for enterprise AI by offering Frontier, a unified operating layer that allows AI agents to work across a company's systems, data sources, and tools while maintaining proper permissions and controls, rather than operating as isolated point solutions (individual AI tools that don't connect to each other).

OpenAI
Codex
GPT-5.4
Amazon Web Services (AWS)
McKinsey & Company
Boston Consulting Group (BCG)
Accenture
Capgemini
Databricks
Snowflake
Goldman Sachs
Phillips
State Farm
Cursor
DoorDash
Thermo Fisher
LY Corporation
Oracle
Uber


The vibes are off at OpenAI

Summary: OpenAI, despite recently raising $122 billion in funding and achieving brand recognition similar to "Kleenex," is facing questions about its stability due to recent executive departures, canceled projects, and other organizational changes. The company's position as the leader in consumer-facing AI tools like ChatGPT may be at risk as it navigates these internal challenges and prepares for a potential IPO.


Hackers exploit a critical Flowise flaw affecting thousands of AI workflows

Summary: Flowise, a low-code platform for building custom AI workflows, has a critical vulnerability (CVE-2025-59528, CVSS 10.0) where attackers can inject malicious JavaScript code through improperly validated configurations in the Custom MCP node (a plugin that lets AI agents connect to external tools). Hackers have already begun exploiting this flaw against thousands of exposed Flowise instances since April 6, 2025.

Solution: The flaw was patched in Flowise version 3.0.6. Users should upgrade to version 3.0.6 or later, with the latest version being 3.1.1 (released last month).


LLM-generated passwords are indefensible. Your codebase may already prove it

Summary: Research from Irregular and Kaspersky shows that all frontier LLMs (large language models, AI systems trained on massive amounts of text) generate passwords that are structurally predictable and much weaker than they appear. When Claude Opus 4.6 was asked to generate passwords 50 times, only 30 distinct passwords emerged, with one password repeating 36% of the time, proving the model retrieves patterns from training data rather than creating truly random passwords. The core problem is architectural: LLMs assign high probability to the most plausible next character based on patterns they learned (like uppercase letters at the start), while cryptographic systems (secure random number generators) must give every character equal probability, making LLM-generated passwords vulnerable to attackers who understand how these models work.

Claude Opus 4.6
GPT-5.2
Irregular
Kaspersky


The zero-day timeline just collapsed. Here’s what security leaders do next

Summary: Zero-day vulnerabilities (security flaws unknown to vendors and defenders) are becoming more dangerous and frequent because agentic AI (artificial intelligence systems that can act independently, plan steps, and adjust tactics) automates the process of finding new vulnerabilities at machine speed, compressing the time between discovery and exploitation. Traditional security approaches like annual penetration tests and quarterly scans are no longer sufficient when attackers can probe continuously and adapt quickly without human intervention.

Solution: The source explicitly mentions two mitigations: (1) 'Data minimization' - if an internet-facing service does not need raw sensitive data, it should not be able to retrieve it, using approaches like 'tokenization and non-reversible storage' to reduce the value of a breach; (2) 'API discipline' - ensure every endpoint response is a deliberate security decision, and if a client does not need a field, the API should not return it.

Google Project Zero
Google DeepMind
OpenSSL


Microsoft’s new Agent Governance Toolkit targets top OWASP risks for AI agents

Summary: Microsoft released the Agent Governance Toolkit, an open-source project that adds a runtime security layer (protective software running during execution) to monitor and control AI agents as they perform complex tasks in production environments. The toolkit addresses ten major security risks identified by OWASP (Open Worldwide Application Security Project, an organization that tracks security threats) for AI agents, including prompt injection (tricking an AI by hiding instructions in its input), goal hijacking, and code execution vulnerabilities. It provides seven modular components across multiple programming languages and integrates with existing AI frameworks without requiring developers to rewrite their code.

Solution: The Agent Governance Toolkit itself serves as the mitigation. It includes specific components: Agent OS (a policy enforcement layer), Agent Mesh (a secure communication and identity framework), Agent Runtime (an execution control environment), Agent SRE, Agent Compliance, and Agent Lightning (covering reliability, compliance, marketplace governance, and reinforcement learning oversight). The toolkit is framework-agnostic and hooks into native extension points of existing frameworks like LangChain, CrewAI, and Google ADK, allowing developers to "introduce governance controls into production systems without disrupting existing workflows." It is available under MIT license and currently in public preview across Python, TypeScript, Rust, Go, and .NET.

Microsoft
LangChain
CrewAI
Google ADK
Microsoft Agent Framework
LlamaIndex


Anthropic's Claude Mythos Finds Thousands of Zero-Day Flaws Across Major Systems

Summary: Anthropic announced Project Glasswing, an initiative using its new Claude Mythos AI model to find security vulnerabilities in software before attackers can exploit them. The preview version has already discovered thousands of high-severity zero-day vulnerabilities (previously unknown security flaws) in major operating systems and web browsers, and demonstrated concerning capabilities like autonomously escaping sandboxes (isolated test environments) and bypassing its own safeguards. Because these powerful hacking abilities emerged unexpectedly from improvements to the model's coding and reasoning skills, Anthropic is limiting access to a small group of major tech organizations rather than releasing it publicly.

Solution: The security issue in Claude Code that bypassed safeguards when presented with commands containing more than 50 subcommands has been formally addressed by Anthropic in Claude Code version 2.1.90, released last week.

Anthropic
Claude Mythos
Claude Code
Amazon Web Services
Apple
Broadcom
Cisco
CrowdStrike
Google
JPMorgan Chase
Linux Foundation
Microsoft
NVIDIA
Palo Alto Networks


The tabletop exercise grows up

Summary: Tabletop exercises (simulated crisis scenarios where teams discuss how they'd respond to incidents) have long been used in cybersecurity to test preparedness, but they have a key limitation: they test knowledge of plans rather than the ability to actually execute them, since scenarios follow a fixed script regardless of what the team decides. AI with agentic capabilities (AI systems that can take independent actions and adapt to changing conditions) now makes it possible to create dynamic tabletop exercises where simulated roles like threat actors or journalists respond in real time to the team's decisions instead of following a predetermined sequence.

Solution: The source text describes using 'AI agentic capabilities' to address the limitation, specifically stating that 'AI allows us to have an adversary that adapts to defensive decisions rather than following a' (the text cuts off here). The source indicates this would enable 'roles that were previously absent (e.g., the threat actor, the journalist, the regulator, the customer)' to 'respond to the team's decisions in real time rather than following a fixed sequence,' but does not provide specific implementation details, version numbers, or a complete explanation of how to deploy this solution.


Given Enough Agents, All Bugs Become Shallow

Summary: AI agents have become very skilled at finding bugs in code, especially security vulnerabilities, and can now identify and exploit previously unknown flaws much faster than before. A new AI model called Mythos Preview, created by Anthropic, succeeded at exploiting certain browser vulnerabilities 181 times compared to only twice for an earlier model, showing a major leap in AI's ability to find and exploit security weaknesses. This capability could make it easier for non-security experts to launch cyberattacks, though the article notes that deploying patches (fixes released by software companies) remains the biggest challenge for organizations trying to stay secure.

Solution: The source text does not explicitly describe a fix or mitigation strategy. It notes that 'the industry needs to adjust' with 'new innovations' to help with patch deployment, but does not specify what those innovations should be. N/A -- no mitigation discussed in source.

Anthropic Claude Mythos OpenBSD FFmpeg FreeBSD Firefox Microsoft


Introducing the Child Safety Blueprint

Summary: OpenAI has introduced a Child Safety Blueprint, a policy framework designed to prevent AI-enabled child sexual exploitation (the use of AI to create, distribute, or facilitate child abuse material). The blueprint addresses three main areas: updating laws to handle AI-generated or altered CSAM (child sexual abuse material), improving how service providers report and coordinate with law enforcement, and building safety features directly into AI systems to detect and prevent misuse. The framework combines legal, operational, and technical approaches and was developed with input from organizations like the National Center for Missing and Exploited Children and state attorneys general.

Solution: The source explicitly mentions these approaches: 'modernizing laws to address AI-generated and altered CSAM, improving provider reporting and coordination to support more effective investigations, and building safety-by-design measures directly into AI systems to prevent and detect misuse.' The framework also emphasizes 'layered defenses — not a single technical control, but a combination of detection, refusal mechanisms, human oversight, and continuous adaptation to emerging misuse patterns.' The source notes that 'getting the prevention architecture right upstream is the single highest-leverage investment the industry can make in child safety.'


CVE-2026-3357: IBM Langflow Desktop 1.6.0 through 1.8.2 Langflow could allow an authenticated user to execute arbitrary code on the sys

Summary: IBM Langflow Desktop versions 1.6.0 through 1.8.2 contain a vulnerability that allows an authenticated user (someone who has already logged in) to run arbitrary code on the system. The flaw stems from an insecure default setting that allows deserialization of untrusted data (converting data from an external source back into code without checking if it's safe) in the FAISS component (a component used for similarity searching).


GHSA-fjrm-76x2-c4q4: JWCrypto: JWE ZIP decompression bomb

Summary: JWCrypto version 1.5.6 has a weakness in its protection against decompression bomb attacks (where compressed data expands to huge sizes). The code only checks the size of the compressed input (limiting it to 250KB), but does not check the size of the decompressed output, allowing an attacker to send a small token that expands to 100MB or more in memory, causing denial of service (a crash from running out of memory) on resource-constrained devices.

Solution: The actual solution is implemented in version 1.5.7, as noted in the resolving commit. (The source does not provide explicit details of the fix itself, only that v1.5.7 contains the corrected implementation.)


GHSA-r758-8hxw-4845: justhtml: Mutation XSS with custom foreign-namespace sanitization policies

Summary: A mutation XSS (cross-site scripting, where attackers inject malicious code through HTML) vulnerability was found in the justhtml library when using custom sanitization policies that preserve foreign namespaces like SVG or MathML. Specially crafted input could pass through sanitization appearing safe, but then become dangerous when a browser or parser processes it again. This only affects users with custom policies; the default settings are safe.

Solution: Upgrade to justhtml version 1.14.0 or later. If you cannot upgrade immediately, keep `drop_foreign_namespaces=True`, avoid allowlisting foreign namespaces for untrusted input, and avoid allowlisting raw-text containers such as `<style>` in custom policies.


GHSA-69x8-hrgq-fjj8: LiteLLM: Password hash exposure and pass-the-hash authentication bypass

Summary: LiteLLM had three security flaws that combined to allow attackers to take over user accounts: passwords were stored using weak SHA-256 hashing without salt (making them easy to crack with rainbow tables, which are pre-computed lists of password hashes), the password hashes were exposed in API responses that any logged-in user could access, and the login endpoint accepted raw hashes instead of requiring the actual password (a vulnerability called pass-the-hash). An attacker could retrieve another user's password hash through the API and use it directly to log in as that user.

Solution: Fixed in v1.83.0. Passwords are now hashed with scrypt (a much stronger algorithm using a random 16-byte salt with parameters n=16384, r=8, p=1). Password hashes are stripped from all API responses. Existing SHA-256 hashes are transparently migrated to the new format on the user's next login.


Google CEO Sundar Pichai says 'AI shift' opens opportunities to invest in startups

Summary: Google CEO Sundar Pichai stated that the rapid growth of AI has created opportunities for Alphabet to invest billions of dollars in AI startups like Anthropic and other companies. Alphabet is moving away from traditional venture capital routes and instead making large direct investments from its own balance sheet, similar to how other major tech companies like Nvidia and Microsoft are operating. Pichai emphasized that the company wants to be a responsible steward of capital by investing in ventures with strong returns.

Solution: N/A -- no mitigation discussed in source.

Google Alphabet Anthropic OpenAI SpaceX xAI Stripe Waymo NVIDIA Microsoft Amazon


Elon Musk seeks ouster of OpenAI CEO Sam Altman as part of lawsuit

Summary: Elon Musk is suing OpenAI CEO Sam Altman and President Greg Brockman, claiming they deceived him into donating $38 million by promising the company would remain a nonprofit when it later became a for-profit entity. In his legal filing, Musk is seeking to have both executives removed from their roles, asking the court to force OpenAI to revert to operating as a true nonprofit, with jury selection scheduled to begin in April 2025.

OpenAI
Sam Altman
Greg Brockman
ChatGPT
xAI
Grok
Meta
SpaceX


What Anthropic Glasswing reveals about the future of vulnerability discovery

Summary: Anthropic has launched Project Glasswing, an initiative using Claude Mythos Preview (an AI model designed for cybersecurity) to automatically discover software vulnerabilities at scale, which it is testing with a closed group of over 40 companies including Amazon, Microsoft, and Google. Early testing claims the model found thousands of high-severity vulnerabilities in widely-used software, including some that had been missed for decades, suggesting that AI-powered vulnerability discovery may shift how security work is organized and force organizations to focus less on managing backlogs and more on reducing the time vulnerabilities remain exposed before being fixed. The initiative raises questions about the future role of human-driven security work as AI automation becomes more capable.

Anthropic
Claude
Claude Mythos Preview
Amazon
Microsoft
Apple
Google
Linux Foundation
CrowdStrike
Palo Alto Networks
Cisco


CVE-2026-34371: LibreChat is a ChatGPT clone with additional features. Prior to 0.8.4, LibreChat trusts the name field returned by the e

Summary: LibreChat, a ChatGPT alternative with extra features, had a vulnerability in versions before 0.8.4 where it didn't properly validate filenames from its code execution sandbox, allowing attackers to write files anywhere on the server using path traversal (sequences like ../ that navigate to parent directories). Any user able to run code through the sandbox could exploit this to write arbitrary files with the permissions of the LibreChat server.

Solution: This vulnerability is fixed in version 0.8.4.


Cracks in the Bedrock: Escaping the AWS AgentCore Sandbox

Summary: Researchers discovered that AWS Bedrock AgentCore's Code Interpreter sandbox, which is supposed to isolate AI agents from external networks, could be bypassed using DNS tunneling (a technique that hides data inside DNS queries to leak information out of restricted environments). Additionally, they found a critical security flaw where the microVM Metadata Service (a system that provides credentials to running programs) lacked proper authentication, potentially allowing attackers to steal sensitive credentials through SSRF attacks (server-side request forgery, where a program is tricked into making requests on behalf of an attacker).

Solution: AWS introduced internal remediations and outlined several important mitigation strategies for customers. The source notes that users cannot patch the managed environment directly but can leverage platform-level controls AWS provides. However, the specific details of these mitigation strategies and platform-level controls are not fully described in the provided excerpt.


Anthropic's Project Glasswing - restricting Claude Mythos to security researchers - sounds necessary to me

Summary: Anthropic released Claude Mythos, a new AI model with exceptionally strong cybersecurity research abilities, but restricted access to only a small group of preview partners through Project Glasswing instead of releasing it publicly. The model can autonomously develop complex exploits (attacks that chain multiple vulnerabilities together to break into systems), finding thousands of high-severity vulnerabilities in major operating systems and web browsers, which is a major leap forward compared to older models like Claude Opus 4.6.


GHSA-8jxr-pr72-r468: Java-SDK has a DNS Rebinding Vulnerability

Summary: The java-sdk has a DNS rebinding vulnerability (an attack where a hacker tricks your browser into accessing a private server by manipulating domain name resolution) that allows attackers to make tool calls to local or private MCP (model context protocol, a system for AI agents to interact with tools) servers if you visit a malicious website. This happens because the java-sdk wasn't validating the Origin header (a security check that confirms requests come from trusted sources) before version 1.0.0, violating the MCP specification.

Solution: Users can mitigate this risk by: 1) Running the MCP server behind a reverse proxy (a security layer like Nginx or HAProxy that forwards requests and can validate headers) configured to strictly validate the Host and Origin headers, or 2) Using a framework that inherently enforces strict CORS (cross-origin resource sharing, a browser security feature that controls which websites can access your data) and Origin validation, such as Spring AI.

io.modelcontextprotocol.sdk:mcp-core@< 1.0.0 (fixed: 1.0.0)

Anthropic
java-sdk
MCP (Model Context Protocol)


GHSA-mh2q-q3fh-2475: OpenTelemetry-Go: multi-value `baggage` header extraction causes excessive allocations (remote dos amplification)

Summary: OpenTelemetry-Go has a denial-of-service vulnerability where the library parses multiple `baggage` HTTP headers (a standard for distributed tracing metadata) separately instead of treating them as one combined value. An attacker can send many baggage header lines to force the server to waste CPU and memory on repeated parsing work, even though each individual header stays within size limits, causing high latency and excessive allocations per request.

Solution: The source recommends: "avoid repeated parsing across multi-values by enforcing a global budget and/or normalizing multi-values into a single value before parsing. one mitigation approach is to treat multi-values as a single comma-joined string and cap total parsed bytes (for example 8192 bytes total)." The fix is accepted when allocations and parsing operations stay within 2x of baseline and response latency (p95) stays below 2ms.

go.opentelemetry.io/otel/propagation@>= 1.36.0, <= 1.40.0 (fixed: 1.41.0)

go.opentelemetry.io/otel/baggage@>= 1.36.0, <= 1.40.0 (fixed: 1.41.0)


Anthropic limits Mythos AI rollout over fears hackers could use model for cyberattacks

Summary: Anthropic released Claude Mythos Preview, an advanced AI model that excels at finding security vulnerabilities (weaknesses in software), but is limiting access to a select group of companies through a program called Project Glasswing to prevent attackers from misusing it. The model can identify bugs that were previously hard to detect, including a 27-year-old bug in OpenBSD (an operating system focused on security), and Anthropic is working with U.S. government agencies to manage the risks of this powerful cybersecurity capability.

Solution: Anthropic is limiting access to Claude Mythos Preview by only providing it to a select group of companies, including Apple, Google, Microsoft, Nvidia, and Amazon Web Services, along with over 40 other firms, for defensive security work. Additionally, the company stated it 'has been in ongoing discussions' with U.S. government officials including the Cybersecurity and Infrastructure Security Agency and the Center for AI Standards and Innovation about the model's cyber capabilities.

Anthropic
Claude Mythos Preview
Apple
Google
Microsoft
Nvidia
Amazon Web Services
CrowdStrike
Palo Alto Networks
OpenAI
OpenBSD


Anthropic Teams Up With Its Rivals to Keep AI From Hacking Everything

Summary: Anthropic announced Claude Mythos Preview, a powerful AI model capable of finding software vulnerabilities and developing exploits, alongside Project Glasswing, an industry consortium of over 40 major tech companies that will receive early access to test the model on their systems. The staggered release approach, modeled after coordinated vulnerability disclosure (the practice of giving developers time to patch bugs before public disclosure), aims to help organizations identify and fix security weaknesses before the model becomes widely available in the coming months.

Solution: Anthropic is conducting a staggered release of Mythos Preview beginning with an industry collaboration phase, giving Project Glasswing partners private access to the model so they can 'turn Mythos Preview on their own systems so they can mitigate vulnerabilities and exploit chains that the model develops in simulated attacks.' This approach is based on coordinated vulnerability disclosure practices.

Anthropic
Claude
Mythos Preview
Microsoft
Apple
Google
Amazon Web Services
Linux Foundation
Cisco
Nvidia
Broadcom


Anthropic Unveils ‘Claude Mythos’ – A Cybersecurity Breakthrough That Could Also Supercharge Attacks

Summary: Anthropic has developed a new AI model called Claude Mythos as part of Project Glasswing, an initiative aimed at securing critical software before it can be exploited by attackers. The model is framed as both a cybersecurity advance and a potential risk, since advanced AI capabilities could theoretically be misused if they fall into the wrong hands.


CVE-2026-24175: NVIDIA Triton Inference Server contains a vulnerability where an attacker could cause a server crash by sending a malfor

Summary: NVIDIA Triton Inference Server has a vulnerability (CVE-2026-24175) where an attacker can crash the server by sending a malformed request header, potentially causing a denial of service (disruption of normal service). The vulnerability stems from an uncaught exception (an error that the program doesn't handle properly), which allows attackers to exploit this weakness.


CVE-2026-24174: NVIDIA Triton Inference Server contains a vulnerability where an attacker could cause a server crash by sending a malfor

Summary: NVIDIA Triton Inference Server has a vulnerability (CVE-2026-24174) where an attacker can crash the server by sending a malformed request (a request with incorrect formatting), causing a denial of service (when a system becomes unavailable to legitimate users). The vulnerability stems from incorrect conversion between numeric types (the software not properly handling different number formats).


CVE-2026-24173: NVIDIA Triton Inference Server contains a vulnerability where an attacker could cause a server crash by sending a malfor

Summary: NVIDIA Triton Inference Server has a vulnerability (CVE-2026-24173) where an attacker can send a malformed request to crash the server, causing a denial of service (when a service becomes unavailable due to an attack). The vulnerability is related to integer overflow or wraparound (when a number exceeds the maximum value a system can store, causing unexpected behavior).


CVE-2026-24147: NVIDIA Triton Inference Server contains a vulnerability in triton server where an attacker may cause an information disc

Summary: CVE-2026-24147 is a vulnerability in NVIDIA Triton Inference Server (a tool that runs AI models) where an attacker can upload a malicious model configuration file to cause information disclosure (exposing sensitive data) or denial of service (making the system unavailable). The vulnerability stems from improper path traversal (a flaw that lets attackers access files outside intended directories) validation when handling uploaded files.


CVE-2026-24146: NVIDIA Triton Inference Server contains a vulnerability where insufficient input validation and a large number of output

Summary: NVIDIA Triton Inference Server has a vulnerability where it doesn't properly check user inputs and can crash when given a large number of outputs, potentially causing a denial of service (making the server unavailable to users). The vulnerability stems from excessive memory allocation triggered by malformed input.


XFaceMark: Explainable deep fake watermarking using YOLO, and random MRFO

Summary: This paper presents XFaceMark, a method that uses YOLO (an object detection system that identifies items in images) and random MRFO (a nature-inspired optimization algorithm) to add watermarks to deepfakes (AI-generated fake videos or images) in a way that can be explained and understood. The approach aims to make deepfakes traceable while allowing researchers to understand how the watermarking process works.


SBOMs into Agentic AIBOMs: Schema Extensions, Agentic Orchestration and Reproducibility Evaluation

Summary: This academic paper discusses extending SBOMs (software bill of materials, which are detailed lists of all components and dependencies in software) to create AIBOMs that can describe agentic AI systems (AI systems that can take independent actions and make decisions). The paper proposes schema extensions, methods for coordinating multiple AI agents, and ways to evaluate whether AI systems produce consistent and reproducible results.


Anthropic is launching a new AI model for cybersecurity

Summary: Anthropic is launching a new AI model called Claude Mythos Preview as part of Project Glasswing, a cybersecurity partnership with major tech companies like Nvidia, Google, and Microsoft. The model is designed to help large organizations and governments automatically detect vulnerabilities (security weaknesses) in their systems with minimal human involvement. Anthropic is limiting access to launch partners only and not releasing it publicly due to security concerns.

Anthropic NVIDIA Google Amazon Microsoft Apple

Anthropic
Claude
Claude Mythos Preview
Nvidia
Google
Amazon Web Services
Microsoft
Apple


Anthropic debuts preview of powerful new AI model Mythos in new cybersecurity initiative

Summary: Anthropic released a preview of Mythos, a powerful new AI model, as part of Project Glasswing, a cybersecurity initiative involving over 40 partner organizations like Amazon, Microsoft, and Apple. The model, which was not specifically trained for cybersecurity but has strong coding and reasoning abilities, has reportedly identified thousands of zero-day vulnerabilities (security flaws unknown to the public and software vendors) in software systems during initial testing. The preview is limited to partner organizations for defensive security work and will not be made generally available to the public.

Anthropic
Claude
Mythos
Project Glasswing
Amazon
Apple
Broadcom
Cisco
CrowdStrike
Linux Foundation
Microsoft
Palo Alto Networks


Cybersecurity in the Age of Instant Software

Summary: AI is making software creation faster and easier, leading to a future where temporary applications (instant software) might be created and deleted on demand, but this also means AI tools are getting better at both finding and exploiting vulnerabilities (weaknesses in code that attackers can use). While defenders can use the same AI capabilities to patch vulnerabilities and fix security problems, today's AI-generated software tends to contain many security flaws because AI doesn't yet write secure code well.


Max severity Flowise RCE vulnerability now exploited in attacks

Summary: Hackers are actively exploiting CVE-2025-59528, a critical vulnerability in Flowise (an open-source platform for building AI agents and custom LLM applications) that allows arbitrary JavaScript code injection without validation through the CustomMCP node. The flaw was publicly disclosed in September, affects thousands of exposed instances online, and enables attackers to execute commands and access files on vulnerable systems.

Solution: Upgrade to Flowise version 3.1.1 or at least version 3.0.6 as soon as possible. Additionally, consider removing Flowise instances from the public internet if external access is not required.


The New Rules of Engagement: Matching Agentic Attack Speed

Summary: Nation-states are using AI agents (autonomous AI systems that can perform tasks without human intervention) to launch cyberattacks at speeds that traditional security responses cannot match. The article argues that cybersecurity defenses cannot rely on small, gradual improvements but must instead undergo fundamental architectural changes to address this new threat level.


Trent AI Emerges From Stealth With $13 Million in Funding

Summary: Trent AI, a new startup, has secured $13 million in funding to develop a layered security solution (a multi-level protective system) designed to protect AI agents (software programs that act autonomously to complete tasks) throughout their entire lifecycle, from creation to deployment.


[Webinar] How to Close Identity Gaps in 2026 Before AI Exploits Enterprise Risk

Summary: Many enterprises have applications disconnected from centralized identity systems (systems that control who can access what), creating blind spots that AI agents and attackers are actively exploiting. While organizations have invested in IAM (identity and access management, the practice of controlling user access) and Zero Trust security, legacy apps and siloed systems remain outside of centralized control, allowing AI agents to amplify credential risks and bypass security oversight.


CVE-2026-35487: text-generation-webui is an open-source web interface for running Large Language Models. Prior to 4.3, an unauthenticate

Summary: CVE-2026-35487 is a path traversal vulnerability (a flaw that lets attackers read files outside the intended directory) in text-generation-webui, an open-source tool for running large language models through a web interface. Before version 4.3, attackers could exploit the load_prompt() function without logging in to read any .txt file on the server and see its contents in the API response.

Solution: Update text-generation-webui to version 4.3 or later, where this vulnerability is fixed.


CVE-2026-35486: text-generation-webui is an open-source web interface for running Large Language Models. Prior to 4.3, he superbooga and

Summary: text-generation-webui, an open-source web interface for running Large Language Models, has a vulnerability in versions before 4.3 where the superbooga and superboogav2 RAG extensions (tools that fetch external documents to help answer questions) accept user-provided URLs without checking them for safety. This allows attackers to access cloud metadata endpoints (services that store sensitive credentials in cloud environments) and steal IAM credentials (identity and access management tokens that control what users can do). The vulnerability is fixed in version 4.3.

Solution: Update text-generation-webui to version 4.3 or later.


CVE-2026-35485: text-generation-webui is an open-source web interface for running Large Language Models. Prior to 4.3, an unauthenticate

Summary: text-generation-webui, an open-source web interface for running Large Language Models, has a path traversal vulnerability (a security flaw where an attacker can access files outside the intended directory) in versions before 4.3. An unauthenticated attacker can exploit this by sending specially crafted requests through the API to read any file on the server, because Gradio (the framework it uses) does not validate user input on the server side.


CVE-2026-35484: text-generation-webui is an open-source web interface for running Large Language Models. Prior to 4.3, an unauthenticate

Summary: CVE-2026-35484 is a path traversal vulnerability (a bug where an attacker can access files outside the intended folder) in text-generation-webui, an open-source tool for running large language models through a web interface. Before version 4.3, attackers could read any .yaml file (a configuration file format) on the server without needing to log in, potentially exposing sensitive data like passwords and API keys in the response.

Solution: This vulnerability is fixed in version 4.3. Users should update text-generation-webui to version 4.3 or later.


CVE-2026-35483: text-generation-webui is an open-source web interface for running Large Language Models. Prior to 4.3, an unauthenticate

Summary: CVE-2026-35483 is a path traversal vulnerability (a flaw that lets attackers read files outside intended directories) in text-generation-webui, an open-source tool for running large language models. Versions before 4.3 allow unauthenticated attackers to read files with extensions like .jinja, .jinja2, .yaml, or .yml from anywhere on the server.

Solution: Update to version 4.3 or later. The vulnerability is fixed in 4.3.


Human vs AI: Debates Shape RSAC 2026 Cybersecurity Trends

Summary: At RSAC 2026, cybersecurity leaders discussed how AI should be used in security work, including debates about agentic applications (AI systems that can act independently to solve problems) and whether human involvement can realistically keep up as AI scales up. The discussions highlighted the tension between automating security tasks with AI and maintaining human oversight in important decisions.


Enabling agent-first process redesign

Summary: AI agents (autonomous systems that learn and adapt to execute workflows without constant human direction) work best when organizations redesign their processes around them rather than adding them to existing systems. Companies need to shift to an 'agent-first' model where AI agents handle routine operations while humans set goals and handle exceptions, requiring machine-readable process definitions and structured data flows to succeed.


Robust AI Security and Alignment: A Sisyphean Endeavor?

Summary: This article argues that there are fundamental mathematical limits to how secure and well-aligned (following intended behavior) AI systems can be, and that understanding these limits is important before deploying AI widely. The research also shows that AI systems have basic reasoning limitations that stem from these same information-theoretic constraints.


CVE-2026-33866: MLflow is vulnerable to an authorization bypass affecting the AJAX endpoint used to download saved model artifacts. Due

Summary: MLflow has a security flaw called an authorization bypass (a weakness where access controls are not properly checked) in its AJAX endpoint (a web interface used to download model files) that allows users without permission to download saved model artifacts they shouldn't be able to access. This affects MLflow versions up to 3.10.1 and has a CVSS score (a 0-10 rating of severity) of 5.3, considered medium severity.


CVE-2026-33865: MLflow is vulnerable to Stored Cross-Site Scripting (XSS) caused by unsafe parsing of YAML-based MLmodel artifacts in it

Summary: MLflow has a stored XSS vulnerability (cross-site scripting, where malicious code hidden in data executes when viewed in a web browser) in how it handles YAML-based MLmodel artifact files. An authenticated attacker can upload a specially crafted MLmodel file that runs malicious code when another user views it in the web interface, potentially letting the attacker hijack sessions or perform actions as that user. This affects MLflow version 3.10.1 and earlier.


Zero‑click Grafana AI attack can enable enterprise data exfiltration

Summary: GrafanaGhost is a critical vulnerability in Grafana (a data visualization platform) that uses indirect prompt injection (tricking an AI by hiding malicious instructions in data it processes) to steal sensitive enterprise data without requiring user authentication or interaction. Attackers chain together multiple exploits, including bypassing URL validation and AI safety guardrails, to trick Grafana's AI into sending confidential information to attacker-controlled servers.

Solution: Grafana has rolled out a fix for this issue. Additionally, security experts recommend: identifying exposure by checking whether Grafana AI/LLM features are enabled, patching to the latest version, restricting "img-src" (image source permissions) to known domains, and applying egress controls (network rules that limit outbound data traffic).


Over 1,000 Exposed ComfyUI Instances Targeted in Cryptomining Botnet Campaign

Summary: Attackers are targeting over 1,000 publicly accessible ComfyUI instances (a platform for running AI image generation) with an automated scanner that exploits a misconfiguration allowing unauthenticated remote code execution (the ability to run commands on a system without permission). Once compromised, these systems are enrolled in botnets (networks of infected computers controlled remotely) to mine cryptocurrency and serve as proxies.


OpenAI encourages firms to trial four-day weeks to adapt to AI era

Summary: OpenAI has published policy proposals suggesting that companies should trial four-day work weeks as AI tools become more capable and potentially displace workers from jobs. The company argues that AI systems will soon complete projects in days that currently take months, and recommends employers offer benefits like reduced work hours without pay cuts, increased retirement contributions, and subsidized childcare to help workers adapt to this shift.


Broadcom shares jump before the bell as chipmaker agrees Google and Anthropic deals

Summary: Broadcom, a chip designer, announced new deals to produce AI chips for Google and expanded its partnership with Anthropic (an AI company), causing its stock price to rise 3.7% in premarket trading. The deals include revenue commitments and access to computing capacity, which analysts believe signal strong future demand for custom AI chips and may ease investor concerns about competition.


Gemini is making it faster for distressed users to reach mental health resources

Summary: Google has redesigned Gemini's crisis response feature to make it faster for users in distress to access mental health resources. When the chatbot detects a conversation indicating potential suicide or self-harm risk, it now presents a streamlined 'Help is available' module that connects users to crisis resources like suicide hotlines or crisis text lines more quickly.

Solution: Google updated Gemini to streamline its crisis response into a 'one-touch' module (based on the partial text provided, the exact mechanism is not fully detailed in the source). The system detects conversations indicating suicide or self-harm risk and launches the 'Help is available' module to direct users to mental health crisis resources.


The noisy tenants: Engineering fairness in multi-tenant SIEM solutions

Summary: Multi-tenant SIEM (security information and event management, a platform that collects and analyzes security data from many sources) solutions share physical resources like CPU and memory among different customers, creating a "noisy neighbor" problem where one customer's heavy workload can slow down threat detection for others and violate service promises. While vendors market cloud-based SIEM as efficient and reliable, most don't publicly discuss how they prevent this fairness issue, which requires sophisticated engineering strategies like fair-share scheduling (giving each customer a proportional share of resources) and intelligent queuing rather than simple rate-limiting.


CVE-2026-1839: A vulnerability in the HuggingFace Transformers library, specifically in the `Trainer` class, allows for arbitrary code

Summary: A vulnerability in HuggingFace Transformers' `Trainer` class (a tool for training AI models) allows attackers to run arbitrary code by providing a malicious checkpoint file. The problem occurs because the `_load_rng_state()` method uses `torch.load()` without the `weights_only=True` parameter (a safety setting that restricts what code can run), leaving systems vulnerable when using PyTorch versions below 2.6.

Solution: The issue is resolved in version v5.0.0rc3.


Flowise AI Agent Builder Under Active CVSS 10.0 RCE Exploitation; 12,000+ Instances Exposed

Summary: Flowise, an open-source AI platform, has a maximum-severity vulnerability (CVE-2025-59528, CVSS score 10.0) in its CustomMCP node that allows attackers to execute arbitrary JavaScript code on the server without validation, potentially leading to full system compromise and data theft. The flaw requires only an API token to exploit and is being actively exploited in the wild against over 12,000 exposed Flowise instances.

Solution: The vulnerability was addressed in version 3.0.6 of the npm package. Users should upgrade to this version or later.


Anthropic Claude Mythos Preview: The More Capable AI Becomes, the More Security It Needs

Summary: As AI models become more powerful, they create both greater risks and opportunities for security. CrowdStrike argues that while companies like Anthropic build safer models, organizations also need deployment governance (security controls for how and where AI runs in a company) to protect data and systems when AI agents access databases, workflows, and sensitive information. CrowdStrike offers tools for discovering all AI applications in use, monitoring what data they access, and preventing sensitive information from being exposed through AI workflows.

Anthropic
Claude
Mythos Preview
CrowdStrike
Project Glasswing


Adaptive Density Clustering for Data-Driven Password Mangling Rule Generation

Summary: This research paper describes a method for automatically generating password mangling rules (transformations that modify passwords systematically) using adaptive density clustering (a technique that groups similar data points together based on how densely packed they are). The approach aims to improve password security by learning patterns from real password data to create more effective rules for testing password strength.


Broadcom agrees to expanded chip deals with Google, Anthropic

Summary: Broadcom has agreed to produce AI chips for Google and signed an expanded deal with Anthropic, giving the AI startup access to about 3.5 gigawatts of computing capacity (the amount of processing power available at one time) using Google's custom processors called TPUs (tensor processing units, which are specialized chips designed to run AI models). This reflects growing demand for the computing infrastructure needed to run generative AI (AI systems that create new text, images, or other content) at scale.

Broadcom Google Anthropic OpenAI Nvidia Amazon Microsoft AMD Apple


OpenAI asks California, Delaware to investigate Musk's 'anti-competitive behavior' ahead of April trial

Summary: OpenAI has asked California and Delaware attorneys general to investigate what it calls 'anti-competitive behavior' by Elon Musk, claiming he is working to undermine the company through attacks and coordination with other rivals ahead of an April trial. OpenAI alleges that Musk has conducted opposition research on CEO Sam Altman, spread false allegations, and is using legal efforts to benefit his competing AI company xAI, which faces its own investigations for generating non-consensual explicit deepfake content.


CVE-2026-35022: Anthropic Claude Code CLI and Claude Agent SDK contain an OS command injection vulnerability in authentication helper ex

Summary: Anthropic's Claude Code CLI and Claude Agent SDK have a vulnerability where authentication helper settings are executed with shell=true (allowing shell commands to run) without checking the input first. An attacker who can change settings like apiKeyHelper or awsAuthRefresh could inject shell metacharacters (special characters that have meaning in command shells) to run arbitrary commands with the user's privileges, potentially stealing credentials or accessing environment variables.

Anthropic
Claude Code CLI
Claude Agent SDK


CVE-2026-35021: Anthropic Claude Code CLI and Claude Agent SDK contain an OS command injection vulnerability in the prompt editor invoca

Summary: Anthropic's Claude Code CLI and Claude Agent SDK have a vulnerability where attackers can execute arbitrary commands (run any code they want) by inserting shell metacharacters (special characters like $() that tell the system to run commands) into file paths. Even though the code tries to protect these paths by wrapping them in double quotes, the POSIX shell (the command-line interface on Unix/Linux systems) still processes these injected expressions, giving attackers the same permissions as the user running the CLI.


CVE-2026-35020: Anthropic Claude Code CLI and Claude Agent SDK contain an OS command injection vulnerability in the command lookup helpe

Summary: Anthropic's Claude Code CLI and Claude Agent SDK have a vulnerability where attackers can run arbitrary commands by manipulating the TERMINAL environment variable (a setting that controls which terminal program to use). When the software constructs shell commands, it doesn't properly sanitize the TERMINAL variable, allowing attackers to inject shell metacharacters (special characters that have meaning to command interpreters) that get executed with the user's privileges.

Anthropic Claude Code CLI
Claude Agent SDK


CVE-2026-35050: text-generation-webui is an open-source web interface for running Large Language Models. Prior to 4.1.1, users can save

Summary: text-generation-webui is an open-source web interface for running Large Language Models (AI systems that generate text). Before version 4.1.1, the application allowed users to save extension settings as Python files (code files that run on servers) in the main app directory, which could let attackers overwrite important Python files like 'download-model.py' and execute malicious code when users tried to download a new model.

Solution: This vulnerability is fixed in version 4.1.1.


GHSA-cjg8-h5qc-hrjv: kedro-datasets has a path traversal vulnerability in PartitionedDataset that allows arbitrary file write

Summary: PartitionedDataset in kedro-datasets had a path traversal vulnerability (a security flaw where an attacker uses ".." sequences to access files outside an intended directory) that allowed attackers to write files anywhere on a system by including ".." in partition IDs (identifiers for data sections). This affected all users regardless of storage type, local or cloud-based.

Solution: Upgrade to kedro-datasets version 9.3.0 or later. The patch normalizes paths using `posixpath.normpath` and validates that resolved paths stay within the dataset base directory before use, raising a `DatasetError` if the path escapes. For users unable to upgrade, manually validate partition IDs to ensure they do not contain ".." path components before passing them to PartitionedDataset.


The one piece of data that could actually shed light on your job and AI

Summary: Economists warn that current tools for predicting AI's impact on jobs are inadequate because they only measure "exposure" (whether AI could theoretically do a job's tasks), which doesn't account for whether employers will actually replace workers or increase productivity instead. Economist Alex Imas calls for collecting new data on how AI actually changes specific jobs and industries, since knowing a job is 28% exposed to AI tells us little about whether that job will disappear, be transformed, or become more productive.

Solution: N/A -- no mitigation discussed in source.


CVE-2026-34940: KubeAI is an AI inference operator for kubernetes. Prior to 0.23.2, the ollamaStartupProbeScript() function in internal/

Summary: KubeAI, a tool that runs AI models on Kubernetes (a system for managing containerized applications), has a vulnerability in versions before 0.23.2 where attackers can inject malicious shell commands (arbitrary code execution instructions) through Model resource creation. The flaw exists because the ollamaStartupProbeScript() function doesn't properly validate user input when building commands that run during startup checks.

Solution: Upgrade to version 0.23.2 or later, which fixes this vulnerability.


Iran threatens OpenAI’s Stargate data center in Abu Dhabi

Summary: Iran's Islamic Revolutionary Guard Corps (IRGC, a military organization) published a video threatening to destroy OpenAI's Stargate data center in Abu Dhabi if the US attacks Iran's power plants. The threat was posted to social media on April 3rd and specifically showed images of OpenAI's $30 billion facility under construction in the United Arab Emirates.


Google DeepMind Researchers Map Web Attacks Against AI Agents

Summary: Researchers at Google DeepMind have identified a vulnerability called 'AI Agent Traps' that allows attackers to manipulate and exploit AI agents (autonomous programs that can browse the web and take actions) by hosting malicious web content designed to deceive them. This research maps out how these attacks work against AI systems that visit websites.


Shadow AI in Healthcare Is Here to Stay

Summary: Healthcare workers are increasingly using AI tools on their own to handle heavy workloads, and organizations cannot stop this trend. The source emphasizes that healthcare organizations should strengthen their security practices to reduce the damage if these unsanctioned AI tools are compromised or misused.


OWASP GenAI Security Project Gets Update, New Tools Matrix

Summary: OWASP (Open Web Application Security Project, a standards group for security best practices) has updated its generative AI security guidance to address 21 identified risks in AI systems. The update recommends that companies use separate but coordinated defense strategies tailored specifically for generative AI (AI that creates text, images, or code) and agentic AI (AI that can take actions independently).