A Worm Just Hacked 160+ npm Packages — And OpenAI Got Hit Too

Worm Just Hacked 160+ is one of those subjects that keeps surfacing in every security conversation. I’ve been writing about cyber security long enough to know when something is genuinely scary. This one qualifies.

Over the past week, a worm called Mini Shai-Hulud tore through the npm JavaScript ecosystem like wildfire through dry grass. It compromised over 160 packages across 373 malicious versions – including major libraries from TanStack, Mistral AI, and UiPath. However, here’s the kicker: OpenAI confirmed that two of their employee devices were compromised in the attack.

How It Actually Worked

This wasn’t some basic phishing scam. The attackers pulled off a three-stage chain that security researchers are calling the first documented case of a malicious npm package carrying valid SLSA Build Level 3 provenance. That’s a big deal – it means the malware came with a legitimate-looking “certificate of authenticity.”

Here’s the chain:

  1. Hijacked GitHub Actions workflow: The attackers created a malicious pull request (#7378) that exploited a misconfigured GitHub Actions workflow using pull_request_target. This ran attacker-controlled code inside the legitimate build.
  2. Cache poisoning: The malicious code poisoned the pnpm package store cache with a specific key, which was later consumed by the legitimate release workflow.
  3. OIDC token theft: During the release build, attacker code extracted the OIDC token directly from runner memory and used it to publish malicious packages to npm – authenticated as TanStack’s own release workflow.

Once inside, the worm self-propagated. It would hijack an infected developer’s npm profile, append a malicious postinstall script to their package.json files, and spread to every package that developer maintained. It hit TanStack’s React Router, Vue Router, Solid Router, and router-core packages. It hit Mistral AI’s client library. It hit 40+ UiPath packages. However, it kept spreading.

The Really Nasty Bits

The malware wasn’t content with just stealing credentials. It installed editor persistence hooks in both Claude Code’s settings and VS Code’s task files. Every time a developer opened their editor, the malware would re-execute. It also installed a system service – on Linux via systemd, on macOS via LaunchAgents – that polled GitHub with the stolen token.

And then there was the dead-man’s switch: if the stolen GitHub token was revoked, the malware would run rm -rf ~/ and destroy the developer’s entire home directory. Let that sink in. You detect the malware, you try to do the right thing by revoking the token, and your machine nukes itself.

Stolen data was exfiltrated via the Session/Oxen P2P network and GitHub GraphQL API “dead-drop” commits – techniques designed to blend into normal traffic and evade detection.

What OpenAI Did

OpenAI published a detailed response confirming that two employee devices were compromised. They found no evidence that user data, production systems, or intellectual property were affected. But they rotated code-signing certificates across all platforms as a precaution.

The practical impact? Every macOS user needs to update their OpenAI apps by June 12, 2026 – ChatGPT Desktop, Codex, and Atlas. After that date, macOS will block apps signed with the old certificate. The last affected versions are ChatGPT Desktop 1.2026.125 and Codex 26.506.31421.

What You Need to Do Right Now

If your team uses any TanStack packages – and if you’re building React apps, there’s a good chance you do – here’s the priority list:

1. Check for compromise:

find node_modules/@tanstack -name "router_init.js" -exec shasum -a 256 {} \;

The compromised hash is ab4fcadaec49c03278063dd269ea5eef82d24f2124a8e15d7b90f2fa8601266c.

2. Kill the dead-man’s switch immediately. Before you rotate anything, disable the persistence mechanisms. Remove the editor hooks. Remove any injected GitHub Actions workflows.

3. Rotate secrets in this order: npm tokens, GitHub PATs, AWS credentials, HashiCorp Vault tokens, Kubernetes service account tokens, SSH keys, and Claude Code session logs.

4. Block these domains at DNS: *.getsession.org, api.masscan.cloud, git-tanstack.com.

5. Audit your package-lock files for any of the 169 affected package names. The full list is in the Snyk advisory and Aikido’s analysis.

The Bigger Picture

This attack exposes something fundamental about how we build software today. The entire npm ecosystem runs on trust – you trust the maintainers, you trust the CI/CD pipelines, you trust that a signed package actually means it’s safe. Mini Shai-Hulud proved that provenance is not a safety signal. A package can have valid provenance from a trusted workflow, but if that workflow was hijacked, the build was compromised.

Supply chain attacks are no longer theoretical. They’re automated, they’re self-propagating, and they’re targeting the exact libraries your developers use every single day. The tools for defending against this exist – minimum release ages, provenance validation, strict dependency pinning – but most teams haven’t deployed them yet.

Every supply chain attack teaches the same lesson: the libraries you trust are only as secure as the pipelines that build them. If you haven’t audited your CI/CD workflows for pull_request_target misconfigurations, you’re not ready for what’s coming next.

Related Reading

IBM Report: AI-Generated Breaches Now Cost $5.72 Million. Here’s What Australian Organisations Need to Do

Phishing has surged 1,265%. The average AI-enabled breach now costs $5.72 million. Somewhere between the sales pitches and the fear campaigns, that 2025 IBM Cost of a Data Breach Report delivers a simple message Australian organisations should stop ignoring: adopting AI without governance is not innovation, it is a financial and operational liability.

That $5.72 million figure is 13% higher than the previous year. IBM ties the rise directly to organisations pushing AI into customer, employee, and supplier workflows without access controls, data classification, or incident response planning. The gap between AI rollout and AI oversight is not just a technical problem. Finance, risk, and legal should also care because breach costs compound across regulatory exposure, customer churn, and remediation time.

What the Numbers Actually Mean

The same reporting period showed AI-enabled cyber attacks rose 47%. Microsoft Cyber Signals tracked a 46% increase in AI-generated phishing content. DeepStrike’s tally found 82.6% of phishing emails now use AI in some form. That is not a distant threat. It is the current email threat landscape.

On the defensive side, IBM reports organisations with mature AI security tools see average breach costs $1.8 million lower than those without. The difference is not magic. It is automated threat detection, rapid containment, and endpoint visibility.

Shadow AI Is Eating Your Budget

Shadow AI is one of the most underdiscussed cost drivers. IBM found many organisations lacked AI governance frameworks, leaving employee-deployed tools operating outside security review. A finance team pasting customer data into a third-party AI assistant, or a developer connecting internal docs to an unvetted LLM, creates exposure no perimeter firewall can stop.

Trend Micro and other researchers documented thousands of unprotected AI services online, including Chroma servers and vector databases, open to anyone who knows how to query them. Once an AI tool is integrated into workflows, it is rarely decommissioned cleanly. Governance needs to start before deployment, not after a breach team arrives.

Practical Steps That Do Not Require a Budget Increase

Start with identity. Strong authentication, passkeys where possible, and a formal process for removing access when someone leaves. Then map your AI footprint. Every connected LLM, every third-party chatbot, every internal tool with access to email or files should be logged and reviewed. Third, assume breaches will include AI-powered reconnaissance and test your response accordingly. Red-teaming and tabletop exercises should include synthetic media and prompt-injection scenarios now, not next year.

The organisations controlling AI costs are not the ones waiting for perfect governance. They are the ones enforcing minimum controls before another employee signs up for the next AI du jour.

Related Reading

Mythos, APRA, and ASIC: Are Australian Enterprises Ready for the AI Threat?

Abstract AI neural network representing frontier model capabilities

Every time I think I have seen it all with Mythos, APRA, and ASIC, something new emerges. On April 7, Anthropic dropped Claude Mythos Preview on the world. By April 30, APRA had written a letter to every bank, insurer, and super fund in Australia telling them to get their house in order. By May 7, ASIC followed up with their own, making it clear that cyber resilience is now a licensing obligation, not a nice-to-have.

Three events. Three weeks. One message: the game has changed, and most organisations aren’t ready.

What Mythos Actually Is

Let’s not sugarcoat this. Mythos isn’t just another incremental update to Claude. Anthropic themselves call it their “most capable frontier model to date.” The system card describes a “striking leap” in benchmark scores. The NYT reported it triggered “emergency responses from central banks and intelligence agencies.”

When intelligence agencies start paying attention to an AI model, you know it’s not just another chatbot upgrade.

What makes Mythos different from its predecessors? Capability. Raw, frightening capability. The kind that can find vulnerabilities faster, craft more convincing phishing attacks, and automate attack chains that used to require skilled human operators.

What APRA Actually Said

APRA’s letter on April 30 wasn’t gentle. They’d done a deep-dive on Australia’s largest banks, insurers, and super funds. What they found was sobering.

Boards are interested in AI’s benefits but lack the technical literacy to challenge AI risks. Governance hasn’t kept pace with adoption. Identity management systems aren’t designed for AI agents. Security testing doesn’t cover AI-specific attack paths. However, perhaps most worryingly, many entities are treating AI as “just another technology.”

It’s not. AI changes the rules. APRA spelled out the attack vectors: prompt injection, data leakage, insecure integrations, exploit injection, and manipulation of autonomous AI agents. These aren’t theoretical threats. They’re happening now.

APRA explicitly called out Mythos by name. They’re “engaged across the sector on the potential for increased cyber threats from high capability AI frontier models such as Anthropic Mythos.” When a prudential regulator names a specific AI model in a letter to the entire financial sector, that’s not a suggestion. That’s a warning.

What ASIC Said a Week Later

If APRA’s letter was the warning, ASIC’s was the hammer. Commissioner Simone Constant didn’t mince words: “The clock is at a minute to midnight.”

ASIC made twelve specific demands. Reassess cyber plans. Confirm governance frameworks. Identify and protect critical assets. Strengthen fundamentals. Minimise attack surfaces. Review user access. Patch systems promptly. Implement defence-in-depth. Prepare for incident response. Manage third-party risks. Use AI defensively.

And here’s the part that should make every board sit up: cyber resilience is a core licensing obligation. Not optional. Not “when you get around to it.” Now.

ASIC even pointed to their recent win against FIIG Securities, where they secured a $2.5 million penalty for inadequate cyber controls. That’s the enforcement precedent. That’s what “stronger supervisory action” looks like in practice.

The Gap Between Awareness and Action

Here’s what worries me. Both APRA and ASIC are saying the same thing: you need to act now. But the gap between awareness and action at most organisations is enormous.

Boards are getting briefed on AI. They’re nodding along. They’re approving budgets. But are they asking the right questions? Do they understand what prompt injection actually means for their customer data? Do they know whether their AI agents have appropriate access controls? Can they answer whether their security testing covers AI-specific attack vectors?

APRA’s observation that boards are “still developing the technical literacy required to provide effective challenge on AI related risks” is polite language for: most boards don’t understand what they’re approving.

What You Should Be Doing Right Now

If you’re in a regulated entity, here’s what I’d be doing this week:

First, read both letters. Not a summary. Not the executive brief. The actual letters. APRA’s is detailed and specific. ASIC’s twelve-step list is a checklist you can hand to your CISO today.

Second, ask your security team one question: “Can you show me our AI-specific attack surface?” If they can’t answer that, you have a problem.

Third, check your identity management. APRA specifically called out that IAM capabilities “have not yet adjusted to nonhuman actors such as AI agents.” If your systems can’t distinguish between a human user and an AI agent, you’re exposed.

Fourth, look at your patching timelines. APRA noted that “implementation timelines for information security remediation activities are not consistently aligned to the accelerated threat environment.” If you’re still patching on a monthly cycle, you’re behind.

Fifth, ask about your third-party AI dependencies. Who are your AI providers? What access do they have? What happens if they get compromised? APRA and ASIC both flagged supplier concentration and opacity as major risks.

The Bigger Picture

What we’re seeing is the regulatory framework catching up with reality. For years, AI governance was theoretical. Boards talked about it. Consultants wrote reports about it. Nothing much changed.

Mythos changed that. Not because it’s malicious, but because it’s capable. When a single AI model can find vulnerabilities faster than your security team can patch them, the status quo stops working.

APRA and ASIC are telling the financial sector: the threat landscape has fundamentally shifted. Your governance, your security, your resilience – all of it needs to evolve. However, you need to do it now, not next quarter.

The question isn’t whether you’ll be affected by AI-driven threats. It’s whether you’ll be ready when they arrive.

When both your prudential regulator and your conduct regulator are sending urgent letters about the same threat in the same month, the time for discussion is over. The time for action is now.

Related Reading

Your Smart Home Is Watching You. Here’s How to Fight Back.

0

Let me tell you about Your Smart Home Is Watching and why it matters right now. I like my smart home. I do. Being able to check who’s at the door from my phone, adjust the thermostat without getting off the couch, and play music by asking the air – it’s genuinely convenient.

But let’s be honest about what we’ve traded for that convenience. Every one of those devices is watching, listening, and collecting data about how we live. However, most of it is going straight to the cloud.

What Your Smart Home Actually Knows

Let’s go through the usual suspects:

Smart speakers (Alexa, Google Home, Siri) – They’re listening for their wake word, but they’re also recording snippets of conversation. Amazon has admitted that human reviewers listen to some recordings. Google’s been caught storing location data even when you turn off location history.

Smart cameras and doorbells (Ring, Nest, Arlo) – They know when you come and go, who visits, when you’re home, when you’re not. Ring has partnerships with over 2,000 police departments in the US. Think about that.

Smart thermostats (Nest, Ecobee) – They know when you’re home, when you sleep, when you’re away. Combined with your schedule, that’s a pretty detailed picture of your daily life.

Smart TVs – They’re tracking what you watch, when you watch it, and how long you watch for. Some even listen to conversations in the room.

What You Can Actually Do

Start with what matters most. You don’t have to rip everything out. Focus on the devices that collect the most sensitive data – cameras, speakers, and anything with a microphone.

Check the privacy settings. Most smart devices have privacy settings buried in their apps. Disable voice recording storage where possible. Turn off “personalisation” features that require your data. Opt out of sharing with third parties.

Segment your network. Put smart devices on their own WiFi network, separate from your computers and phones. If one device gets compromised, the attacker can’t jump to your main devices.

Update everything. Outdated firmware is how most smart device attacks work. Enable automatic updates wherever possible.

Consider alternatives. For the truly paranoid (and I mean that as a compliment), open-source alternatives like Home Assistant let you control smart devices without sending data to the cloud. It takes more setup, but you keep your privacy.

The Uncomfortable Trade-Off

Here’s the honest truth: you can’t have 100% privacy and 100% convenience. Something has to give. The goal isn’t to eliminate all data collection – that’s impossible in a connected home. The goal is to make conscious choices about what you’re sharing and with whom.

Most people never check the privacy settings on their devices. That’s exactly what the manufacturers are counting on. Don’t be most people.

Convenience is great until you realise what it cost you. Check your settings today.

Related Reading

AI Agents Are Everywhere. Your Security Team Probably Isn’t Ready.

Abstract representation of artificial intelligence with neural network patterns

The conversation around AI Agents Are Everywhere. Your has reached a critical point. I’ve been thinking about AI agents a lot lately. Not the chatbots that answer customer service questions – those are old news. I’m talking about autonomous agents that can browse the web, write code, access databases, and make decisions without a human in the loop.

They’re being deployed everywhere. However, most organisations have no idea what they’ve just let through the front door.

The Problem Nobody’s Talking About

Here’s the thing about AI agents: they’re essentially interns with root access. They can do amazing things, but they can also do amazing damage if something goes wrong.

Think about it. You give an AI agent access to your codebase, your customer database, your internal tools. It’s productive, sure. But what happens when someone tricks it into sharing that data? Or when it accidentally deletes something important? Or when it gets manipulated through prompt injection into doing something you never intended?

This isn’t hypothetical. Research from NTT DATA this week highlighted that enterprises are deploying AI agents faster than they can secure them. The gap between capability and security is growing, not shrinking.

What I’m Worried About

Prompt injection. Someone puts malicious instructions in a document, email, or webpage that your AI agent processes. The agent follows those instructions instead of yours. It sounds like science fiction, but it’s happening right now.

Data exfiltration. Your AI agent has access to sensitive information. A well-crafted query can trick it into sharing that information in its responses. The agent isn’t being malicious – it’s just doing what it was asked.

Shadow AI. Your marketing team signed up for an AI tool without telling IT. That tool now has access to your customer data, and nobody’s monitoring what it’s doing with it.

What You Can Do

Start with least privilege. Give AI agents only the access they need for their specific task. Not general access to everything. Not “we’ll figure it out later.” Specific access for specific tasks.

Log everything. If you can’t see what your AI agents are doing, you can’t protect against what they’re doing. Every action, every query, every response – log it.

Test for prompt injection. Red-team your AI deployments. Try to trick them. If you can do it, someone else definitely can too.

Establish governance now. Don’t wait for a breach to figure out your AI policies. Who can deploy agents? What access can they have? What happens when something goes wrong? Answer these questions before you need to.

The Window Is Closing

AI agents are getting more capable every week. The security gaps we have today are going to be the attack vectors of tomorrow. We need to close them now, while we still can.

The organisations that establish strong AI governance today will be the ones still standing when the attacks come. However, they will come.

Related Reading

This Week in Cyber: AI Gets Scary, Super Funds Get Hit, and Privacy Keeps Eroding

0
Computer keyboard and screen showing code and security data

This Week in Cyber is a topic I have been following closely, and the developments keep coming. Another week, another batch of stories that make you want to wrap your phone in tinfoil. Let’s get into it.

AI Is Getting Scary Real

The AI security conversation shifted this week from theoretical to actual. We’re no longer talking about what could happen – we’re talking about what is happening.

Research from NTT DATA highlighted a growing problem: enterprises are deploying AI agents faster than they can secure them. These aren’t chatbots – they’re autonomous systems that can browse the web, access databases, and make decisions without human oversight.

Meanwhile, reports of AI-generated sextortion targeting teenagers are increasing. Scammers are using AI to create fake nude images from social media profiles and threatening to share them. This is the kind of threat that should make every parent sit up and pay attention.

Super Funds Under Attack

The credential stuffing wave that hit Australian super funds last month is still reverberating. The numbers are stark: AustralianSuper alone lost around $500,000, with 600 accounts compromised.

The thing that gets me is how preventable this was. Password reuse isn’t a new problem. We’ve been shouting about it for years. Yet here we are, watching people lose their retirement savings because they used the same password for their super account as they did for some random shopping site.

Privacy Keeps Eroding

If you drive a smart vehicle, you might want to check what data it’s collecting. Tesla, BYD, Volvo – they’re all vacuuming up location data, driving habits, and in some cases, camera footage. The features are great, but the trade-off is real.

And if you use Grafana for monitoring, you’ll want to update. The company confirmed a breach this week, and if you’re running a self-hosted instance, you need to act now.

What I’m Watching Next Week

  • The fallout from the Grafana breach – more details should emerge
  • Continued pressure on AI regulation in Australia
  • More developments in the social media ban implementation

Stay safe out there. However, for the love of good passwords, use a password manager.

The best security tool is still common sense. Use it generously.

Worth Reading

Got a story I should cover next week? Drop me a line at info@philiphall.com.

Someone’s Using AI to Make Fake Nudes of Teenagers. Here’s What Parents Need to Know.

0
Teenager looking concerned while using a smartphone

I keep coming back to Someone’s Using AI to Make because it affects every part of digital life. I wish I didn’t have to write this one. But here we are.

A new wave of sextortion attacks is targeting teenagers, and this time the scammers don’t even need the teen to send anything. They’re using AI image generation to create realistic fake nude photos from social media profiles, then threatening to share them unless they get paid.

Let that sink in. Your kid doesn’t have to make a mistake. They just need to have a social media profile.

How This Scam Works

The playbook is disturbingly simple: the attacker scrapes photos from a teenager’s social media profile, uses AI tools to generate realistic-looking nude images, contacts the teen directly (usually via DM on Instagram or Snapchat), and then threatens to send the fake images to the teen’s friends, family, and school unless they pay.

The images aren’t real, but the shame and fear they cause absolutely are. These scammers are counting on teenagers being too scared and embarrassed to tell anyone.

Warning Signs to Watch For

Your teen won’t always tell you something’s wrong. But watch for: receiving unexpected messages from strangers or new accounts, being asked for money or gift cards, sudden distress or anxiety about something online, wanting to delete social media accounts out of nowhere, or mentioning someone threatening to share photos of them.

What to Do If This Happens

Don’t pay. I know the instinct is to make it go away, but paying never stops the demands. They’ll just come back for more.

Take screenshots. Save everything – the messages, the profile, the fake images. You’ll need this evidence.

Report it. Contact the eSafety Commissioner or your local police. This is a serious crime and it’s being taken seriously.

Talk to your teen. The most important thing you can do is make sure they know they can come to you without judgment. The scammers rely on shame and silence.

The Uncomfortable Truth

This isn’t a problem that’s going away. AI image generation is getting better, easier to access, and harder to detect. The best defence we have is education and open conversations with our kids.

Have the conversation before something happens. Not after.

The best time to talk to your kids about online safety is before they need to hear it.

Related Reading

Grafana Got Hacked. If You Run One, You Need to Read This.

0
Server room with blue lights representing cybersecurity monitoring

The conversation around Grafana Got Hacked. If You has reached a critical point. I’ve been using Grafana for years to monitor my homelab and various projects. It’s one of those tools that sits quietly in the background doing important work. Which is exactly why hearing it got hacked stung a bit.

The company confirmed the breach this week after threat actors started bragging about stolen data on underground forums. If you’re running a self-hosted Grafana instance, this one’s for you.

What Actually Happened

From what’s been disclosed so far, the attackers managed to access Grafana’s systems and claim to have exfiltrated data. The company is investigating the full scope, but here’s what we know: self-hosted Grafana instances are potentially at risk, cloud customers may also be affected depending on the breach timeline, and the attackers are claiming to have data, though the extent is still being verified.

The frustrating part? We’ve seen this movie before. Security tools being compromised is becoming a pattern, not an exception. Remember when SolarWinds happened? Same energy.

What You Should Do Right Now

Update. Today. Grafana has released patches. If you’re running a self-hosted instance, check your version and update immediately. Don’t wait for the weekend.

Check your access logs. Look for anything unusual – login attempts from weird IPs, unexpected API calls, any activity that doesn’t match your normal patterns.

Rotate your credentials. Any passwords or API keys associated with your Grafana setup should be changed. Yes, all of them. I know it’s a pain, but do it anyway.

Enable MFA. If you haven’t already enabled multi-factor authentication on your Grafana accounts, now is the time. Not tomorrow. Now.

The Bigger Picture

Here’s what bothers me most about this: we’re in a loop. Security tools get compromised, we patch, we move on, and then it happens again. The organisations building the tools we rely on to detect threats need to be held to the same security standards they sell to the rest of us.

If you’re running Grafana, take 15 minutes today to check your setup. It’s the least you can do.

The tools we trust to watch our systems need someone watching them too.

Related Reading