New tools, products, platforms, funding rounds, and company developments in AI security.
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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, 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.
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.
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.
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.
Fix: 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).
CSO OnlineResearch 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.
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.
Fix: 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.
CSO OnlineMicrosoft 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.
Fix: 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.
CSO OnlineAnthropic 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.
Fix: 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.
The Hacker NewsTabletop 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.
Fix: 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.
CSO OnlineAI 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.
Fix: 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.
Embrace The RedOpenAI 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.
Fix: 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.'
OpenAI BlogAnthropic 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.
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).
Fix: 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.
Palo Alto Unit 42Anthropic 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.
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.
Fix: 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.
CNBC TechnologyAnthropic 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.
Fix: 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.
Wired (Security)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.
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.