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reVault is a new, secure-by-default archive format called a lockbox, designed to be simple to use. I've been working on reVault for about 2 years. It was originally written in Dart, but with the improvements in AI, I decided to port it to Rust using AI. It's now in beta, so I'm looking for feedback, particularly around the different language bindings. A lockbox is encrypted, signed and compressed by default. Each can be disabled selectively. - Hybrid post-quantum or passphrase encryption, including metadata. - Zstd compression. - Pure Rust libraries wherever possible. We intend to phase out remaining C code as alternatives become available. The project has been scanned using OpenAI's Daybreak cyber security tools. The manual is a work in progress: https://docs.revault.onepub.dev/ reVault supports Linux, macOS and Windows, x64 and arm64, plus Wasm. The core is Rust, with bindings for C/C++, Java, Dart, Python, Ruby, JS/TypeScript, Go, C#, Kotlin, Lua, PHP and Swift. Within a lockbox you can store: - Files, directories, permissions and symlinks. - Variables. - Forms. Variables, forms and the lockbox itself can have descriptions. reVault uses a portable vault (just another lockbox with structured content) to hold your keys, contacts' keys, lockbox aliases and form definitions. It ties into your platform's secure store, so logging into your desktop unlocks your vault. You don't have to enter a passphrase every time you access a lockbox. You can disable this. There are lots of shortcuts. Creating a lockbox stores an alias in your vault, based on its filename or a name you choose: lbx create /some/path/mybox.lbox lbx mybox open --duration 1h lbx mybox var set KEY VALUE Set a default lockbox and you can leave its name out: lbx session default mybox lbx var get KEY You can mirror a directory tree into a lockbox and update it when the directory changes: lbx store.lbox mirrors project create --from ./project --to /projects/project lbx store.lbox mirrors update The API lets you read, write and seek within files without extracting them to the filesystem. Each lockbox has a table of contents, so extracting a single file from a multi-gigabyte lockbox is fast. Recovery Updates are transactional, with automatic rollback for failed updates. The format is designed for recovery: content is stored in pages, allowing unaffected content to be recovered if part of a lockbox is corrupted. Sharing An encrypted lockbox is more useful if you can share it. reVault has an open-source keyserver for exchanging public keys, with validation through a second trusted channel. It's still experimental. OnePub has donated a server to run a single keyserver. If you're interested in donating resources, I'd like to bring up a second redundant server. It's pure Rust, uses under 100 MB RSS and supports rate limits. To publish your default profile's public key: lbx vault profiles email you@example.com lbx vault profiles publish Give the publish code to your contact. They can import your key: lbx vault contacts receive Display your profile's fingerprint and exchange it through a second trusted channel: lbx vault profiles fingerprint Repeat the process in the opposite direction to get their key. Once you have it, grant them access to your default lockbox: lbx access grant alice You can then email the encrypted lockbox to Alice. To install the CLI and get started: cargo install revault_cli lbx vault init lbx completion install Completion installation detects your shell. To diagnose issues: lbx doctor The language bindings are published to their respective package repositories. I'm looking for constructive criticism of the project on its own merits, particularly the APIs and language bindings. I'm not interested in a debate about using AI. Comments URL: https://news.ycombinator.com/item?id=50227527 Points: 3 # Comments: 1

Article URL: https://openai.com/index/securing-our-frontier-model-training-environment/ Comments URL: https://news.ycombinator.com/item?id=50214416 Points: 68 # Comments: 80

The bugs OpenAI models discovered this week have existed for more than a decade, and PHP, the programming language that contained them, is 30 years old.

independent evaluators say they found "vulnerabilities" with an OpenAI monitoring system in a test of how such its systems will be assessed.

The websites you use every day may have been vulnerable to hackers for years because of hidden flaws in their code that AI only recently discovered. Why it matters: The code, called PHP, powers millions of websites, and the vulnerabilities could allow hackers to steal sensitive data or take control of affected servers. If exploited, the bugs could allow attackers to steal sensitive information, like your passwords and data, or take control of vulnerable servers. Driving the news: A potential attack exploiting flaws in PHP emerged on Wednesday, which prompted governments and companies to temporarily take their websites offline while they installed security patches. Dozens of websites in the U.S., U.K., and around the world were briefly taken offline to make the fix. The disruption put the National Security Agency and Europe's cybersecurity agency on alert. State of play: Security patches were released to fix the issues on Oct. 21, 2026. Cybersecurity firms urged anyone using PHP to install the security updates immediately. What they're saying: OpenAI's technology helped find the bugs, and the company called the discovery "one of the most impactful security issues in recent memory." "To our knowledge, frontier AI found these vulnerabilities before attackers did," OpenAI said. The cybersecurity firm Wiz wrote in a blog post : "These findings rank among the most severe vulnerabilities discovered in PHP, and arguably in software history." Read more below. What is PHP? You've probably never heard of PHP, even though you've interacted with it for decades. PHP, which stands for Hypertext Preprocessor , is a programming language used by roughly 70% of websites whose server-side language is known. It has been around since the 1990s to help build websites, taking data and generating content sent to a browser. It's still used today for a variety of websites, including Wikipedia, WordPress blogs and shopping websites. How it works: HTML determines what a website displays. PHP works behind the scenes to collect information and generate content. What was the PHP vulnerability, exactly? AI researchers discovered two critical vulnerabilities in PHP that could have allowed an attacker to take control of a website's server without having legitimate access to it. Hackers could exploit the flaws, dubbed " php2shell " by cybersecurity firms, to steal information from those websites. Between the lines: The flaws went undetected for more than a decade because exploiting them required complex technical work that AI helped researchers discover, per Wiz. Why cybersecurity incidents are a big deal Thought bubble via Axios' Bradley Olson : The PHP vulnerabilities are so serious that the NSA warned website operators to take their sites down if they didn't have enough time to patch the bug. But the cybersecurity problems in recent days have extended far beyond that and include disruptions to developer platforms, data leaks on public schools, break-ins on public companies and more. A major Axios scoop also revealed that banks are detecting unauthorized third-party agent access inside customer accounts, a problem they are racing to contain. Cyber pros are calling the series of attacks "Black October" due to the sheer volume and the level of risk, although so far many organizations have mitigated the risk and avoided massive real-world harm. While defenders and AI companies have warned for months that a season of cyber emergencies would imminently arrive, they have also been working to secure some of the obscure software that still underpins much of the modern internet ecosystem. The bottom line: As attacks continue, experts have urged users to secure passwords, use a password manager and also to avoid panic. As with any cyber emergency, the true barometer of harm is the extent to which damage seeps into the real world, as it has done with ransomware that took hospital software offline or a pipeline system that disrupted fuel supplies briefly on the East Coast.

The current US administration is an obstacle, but public demand for protection will ultimately prevail Organisations around the world scrambled on Thursday to fix critical flaws in PHP, the software that powers much of the web. The vulnerabilities could allow attackers to take control of affected servers. Some websites were taken offline as a precaution while fixes were installed. The paradox is that while AI helped researchers uncover the flaw, it also threatens to accelerate the ability to exploit it. Amazon said that it had detected an attempt before the public disclosure of the PHP flaws. What the episode highlights is AI’s central role in security – and not always for the right reasons. OpenAI’s models have also been responsible for two alarming hacks this year – a security breach of an Australian health department website and a raid by a swarm of AI bots on Hugging Face, an AI services platform. Citing those incidents, the AI minister, Kanishka Narayan, warned that a similar cyber-attack on the UK is “likely, if not inevitable”. Continue reading...

Critical PHP security flaws trigger global warnings as Google, OpenAI and Amazon respond to potential cyber threats.

Researchers at OpenAI have found a bug that puts up to 70% of the world's websites at risk. Robert McMillan, the reporter who broke the story for the Wall Street Journal, joins CBS News with the details.

Security officials are sounding the alarm over two critical vulnerabilities in a programming language used to run millions of websites, marking one of the most consequential cybersecurity discoveries yet made with AI. Why it matters : The bugs, which researchers found partly with an OpenAI model, proves AI can uncover critical flaws humans missed for decades — raising the stakes for defenders racing to fix vulnerabilities before attackers can exploit them at machine speed. What's happening: There are two problems hackers could easily exploit in an open-source programming language known as PHP that's used on nearly 70% of all websites . Government officials from the U.S. to Japan are warning companies to apply a patch to fix the bugs, or consider taking down their sites to avoid an attack. OpenAI touted the role its model played in discovering one of the vulnerabilities, which allowed PHP researchers to create a fix. Between the lines: Security researchers have been skeptical of AI-generated vulnerability reports, many of which have turned out to be minor bugs or false alarms. But the PHP discovery could force the cybersecurity community to reckon with the reality of AI threats. "It highlights how AI can uncover security flaws with internet-scale impact, but the same capabilities can also help attackers rapidly develop offensive tools and exploits," OpenAI said in a blog post Wednesday. Threat level: If exploited, the PHP flaws would allow malicious hackers to take control of vulnerable web servers without needing a password or other credentials. Since PHP runs under a wide variety of internet applications, that access could allow hackers to take over websites, steal sensitive information and tamper with a website. Some website owners took their sites down earlier Wednesday, including certain services at Wikipedia and 4chan , until they had time to patch their systems. "These findings rank among the most severe vulnerabilities discovered in PHP, and arguably in software history," researchers at Wiz wrote in a post. The big picture: AI-driven bug discoveries are shining a light on the fragility of the modern internet, which is heavily reliant on a slew of open-source software powered by volunteers . The two flaws in PHP existed for decades, but demonstrated that it was possible for a hacker to exploit them required "an exceptionally complex chain of steps," researchers at Wiz added. "Defenders have always relied on the gap between 'vulnerable' and 'exploitable' to buy time to patch," Michael Leland, field CTO at Island, said in an email to Axios. "That gap is rapidly closing." What to watch : Cybersecurity defenders are on guard for what could be a wave of incidents where websites and organizations are hacked using these two vulnerabilities in the next few weeks. Go deeper : Rogue AI agents expose internet's frail foundation

Warnings about the risks of developing increasingly advanced AI systems have ramped up in recent months, amid cyberattacks from rogue AI models.

In the race to fend off AI-enabled cyber threats , security teams are confronting a new problem: The AI models they rely on to investigate attacks can suddenly refuse to help. Why it matters: While AI giants race to build AI tools that can respond quickly to hacking or other malicious online threats, strict guardrails on their most powerful models lock out defenders mid-investigation, leaving them scrambling for alternatives at critical moments. What's happening: OpenCode, an open-source AI coding agent, said it was compromised over the weekend, allowing attackers to obtain API keys belonging to some customers, including keys for OpenAI, Anthropic and Google services. OpenCode said the breach was "related to a large scale distillation attack that impacted 1.4% of OpenCode Console users." OpenCode co-creator Dax Raad said attackers had been targeting its systems continuously for 48 hours, forcing the company to keep its own AI agents running around the clock to respond. OpenAI , Google and Anthropic have said they worked with affected customers to revoke exposed API keys and address unauthorized usage charges. Zoom in: Raad said on X that frontier AI models initially helped investigate the breach but then "started refusing." The models' safety restrictions reportedly began blocking requests as the investigation turned to potentially malicious code, even though OpenCode was trying to defend its own systems. OpenCode then gained access to OpenAI's Daybreak Blue program, which gives vetted cybersecurity defenders access to models with fewer restrictions. "We definitely need to be more proactive and we've made so many improvements over the last few days," Raad wrote on X Monday. The big picture: The incident underscored a dilemma facing cybersecurity teams trying to figure out when to use powerful proprietary AI models, which come with built-in restrictions, or open-weight alternatives that offer greater control over how they're deployed. When Hugging Face discovered suspicious activity on its systems that it later linked to OpenAI's own agents, its security team turned to a Chinese open-weight model to help investigate after encountering restrictions on frontier models. Yes, but: AI companies maintain that they need to gate access to their most powerful models to ensure that malicious actors can't abuse their cyber capabilities. Between the lines: Cybersecurity teams will have to figure out how to balance the need for faster AI-powered defenses with restrictions designed to keep those same capabilities out of attackers' hands, Chris Jones, chief technology officer at Nightwing, told Axios. "We're all going to have to figure out how that race gets modulated over time," Jones said. "That's a big piece here." Go deeper : Anthropic and OpenAI are now cybersecurity's kingmakers