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Tech and Humanity

When Anthropic Accidentally Opened Its Own Vault: The Claude Code Leak of March 31, 2026

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….And what it reveals about AI, human fallibility, and the road ahead

By Folu Adebayo

The Day the Source Walked Out the Door

On the morning of March 31, 2026, a 59.8 MB JavaScript source map file intended for internal debugging was accidentally included in version 2.1.88 of the @anthropic-ai/claude-code package published to the public npm registry.

It wasn’t a hack. No sophisticated adversary breached Anthropic’s defences. Anthropic confirmed the incident themselves, stating: “This was a release packaging issue caused by human error, not a security breach.”
One misconfigured file. One missing line in. npmignore. And suddenly, 512,000 lines of TypeScript code across 1,906 files — and 44 hidden feature flags — were sitting on a public registry for anyone to download.
Security researcher Chaofan Shou was first to discover and disclose it, and the community set up multiple GitHub mirrors within hours, which garnered over 1,100 stars. By mid-morning, Anthropic’s internal codebase had become the most-studied piece of software on the internet.

What Was Actually Exposed?

This was not a breach of user data or model weights. Anthropic was clear that no sensitive customer data or credentials were involved.  But what was exposed was arguably more strategically damaging the engineering blueprint of their fastest-growing product.

The source code leak exposed around 500,000 lines of code across roughly 1,900 files. At least some of Claude Code’s capabilities come not from the underlying large language model itself, but from the software “harness” that sits around it instructing it how to use tools and providing the guardrails that govern its behaviour. That harness was now public.

The Hidden Features Nobody Was Supposed to See

KAIROS The Always-On Agent While current AI tools are largely reactive, KAIROS allows Claude Code to operate as an always-on background agent. It handles background sessions and employs a process called autoDream where the agent performs “memory consolidation” while the user is idle, merging disparate observations, removing logical contradictions, and converting vague insights into absolute facts.

BUDDY, The AI Pet BUDDY is a Tamagotchi-style AI companion that lives in a speech bubble next to the input box, with cosmetic hats and a deterministic species generation system meaning the same user always hatches the same buddy, whose name and personality are written by Claude on first hatch.

Undercover Mode The Most Ironic Discovery Perhaps the most discussed technical detail is “Undercover Mode” a feature revealing that Anthropic uses Claude Code for “stealth” contributions to public open-source repositories. The system prompt warns the model not to let any Anthropic-internal information appear in public git logs.

The funniest part: there is an entire system called “Undercover Mode” specifically designed to prevent Anthropic’s internal information from leaking — and then the entire source shipped in a .map file.  The irony was not lost on the developer community.

The Capybara Model The source code confirmed that “Capybara” is the internal codename for a Claude 4.6 variant, with “Fennec” mapping to Opus 4.6 and the unreleased “Numbat” still in testing.

The Compounding Security Crisis

The leak did not arrive alone. If you installed or updated Claude Code via npm on March 31, 2026, between 00:21 and 03:29 UTC, you may have inadvertently pulled in a malicious version of the axios HTTP library containing a Remote Access Trojan (RAT).

The malicious archive circulating on GitHub included ClaudeCode_x64.exe, a Rust-based dropper that, on execution, installs Vidar v18.7 and GhostSocks malware used to steal credentials and proxy network traffic.
The message to any developer who updated Claude Code that morning: treat the host machine as fully compromised.

AI Is Still Controlled by Humans and That’s the Point

There’s a deeper lesson here that cuts through all the technical drama.

This incident was not caused by AI going rogue. It was not an autonomous system making a dangerous decision. A file used internally for debugging was accidentally bundled into a routine update and pushed to the public registry by a human.

A human forgot a line of configuration. A human approved the release. A human error, the same category of mistake that has preceded every major data breach, every nuclear near-miss, every preventable industrial disaster in history.

The narrative that AI is some uncontrollable force is, in this case, precisely backwards. The AI did what it was instructed to do. The humans around it made the mistake. This is not a condemnation of Anthropic it is a reminder that as AI systems grow more powerful, the quality of human oversight must scale with them. The weakest link is still, reliably, human.

The Strategic Fallout

The leak hands competitors a detailed unreleased feature roadmap and deepens questions about operational security at a company that sells itself as the safety-first AI lab.

The latest security lapse is potentially more damaging than an earlier accidental exposure of a draft blog post about a forthcoming model. While it did not expose the weights of the Claude model itself, it allowed people with technical knowledge to extract additional internal information from the codebase.

The leak won’t sink Anthropic, but it gives every competitor a free engineering education on how to build a production-grade AI coding agent and what tools to focus on next.

What This Means for the Future of AI

1. Agentic AI demands agentic security. The attack surface exposed by the Claude Code leak is not a Claude-specific problem, it is a window into the systemic vulnerabilities of agentic AI at large. The same compaction pipelines, permission chains, and MCP interfaces exist across every enterprise agent deployment. What changed on March 31 is that the attack research cost collapsed overnight.

2. The “always-on AI” era is already being built. Features like KAIROS and BUDDY signal that the next generation of AI tools will not wait to be asked. They will watch, remember, and act in the background. This raises profound questions about consent, privacy, and the nature of the human-AI relationship that regulators and ethicists are not yet equipped to answer.

3. Transparency may be the only viable long-term strategy. While negative for Anthropic in the short term due to the exposure of trade secrets, it is a net positive for the industry in the long run providing the first complete, production-grade AI Agent architecture reference, which could potentially drive ecosystem development much like the open-sourcing of Android.

4. AI governance is not optional. For any organisation deploying or building on AI systems, this incident is a case study in why governance frameworks, release pipeline controls, and security-by-design are not bureaucratic overhead they are existential necessities.

The Claude Code leak is a story about a brilliant company, moving fast, in a highly competitive market, staffed by talented humans who are still, at the end of the day, fallible. That is not a criticism. It is the human condition.

The question the industry must now answer is not whether AI can be trusted. It is whether the humans building, deploying, and governing AI have earned that trust themselves. March 31, 2026 suggests there is still significant work to do.

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Tech and Humanity

The Dreams That Died, and the Son Who Was Worth More Than All of Them

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By Folu Adebayo

Almost thirty years ago, I held a healthy baby boy in my arms and I began to write his life.

Not on paper. In my chest. The way every mother does in those first hours, when the weight of a newborn is still strange and the future feels like something you can simply decide. We named him Akintade. And in the quiet of that hospital room, I wrote the whole story out.

I saw the first day of school. The blazer a little too big for his shoulders, the gap-toothed grin, my hand letting go of his at the gate. I saw a graduation, a gown, a name read out, a cap thrown into the air. I saw a wedding day. I saw grandchildren I would spoil and hand back sticky and overtired. I had written every chapter before he had lived a single day.

I just did not know that I was dreaming about a son who did not yet exist.

Akintade is autistic. He communicates without words.

And one by one, the chapters I had written began to be erased. The school gate I had imagined did not look the way I had pictured it. The graduation. The wedding. For a long time, I grieved each one as if it were a death. Because in a way, it was. Quietly, privately, in a grief I did not have permission to speak aloud, I mourned a future that was never going to arrive.

I want to be honest about that grief, because so many parents carry it in silence and are made to feel ashamed of it. We are told we should only feel grateful, only feel love. And we do feel those things, fiercely. But alongside them, in the early years, there was mourning. And pretending otherwise helps no parent who is sitting tonight where I once sat.

 

“What died was never my son. What died was the script I wrote before I ever knew him.”

 

Here is what took me years to understand, and what I would give anything to tell my younger self in that hospital room.

What died was never my son. What died was the script I had written before I knew him. Those were my dreams. My expectations. I had handed a newborn a stack of plans he never asked to carry, and when life gave me a different story, I mourned my version of him as though it were a real person who had been taken away.

It was not. He was here the whole time. The real one. And the real one was never the tragedy. The tragedy existed only in the comparison, only in measuring the son I was given against the son I had invented.

The day I finally put the script down; I got my son back.

And the son I got back was worth more than every dream I had lost.

Let me tell you about the real Akintade, the one I almost missed while grieving the imaginary one. He is jovial. He communicates using Picture Exchange Communication (PECS) and Makaton signs (by the way, all of us in my household are makaton experts, thanks to Akintade) He is full of life. He has a spot on the sofa that is his, where he settles when he comes home. He loves good food. His whole face changes when Afrobeats comes on, a joy so complete and so unguarded that it puts the rest of us to shame, we who have learned to hold our happiness back.

He may never speak full sentence to me. But without a single word, this man has taught me more about human worth than anyone I have ever met. He has redrawn my understanding of what success means, of what a life is for, of how to love without condition and without expectation of return. The dreams I lost were small, ordinary, borrowed from everyone else’s idea of a good life. What he gave me instead was something I did not know to dream of.

He may never speak a sentence. But without a single word, he has changed how I understand human worth.”

I am writing this in a Nigerian paper deliberately, because I know how autism is too often spoken of among my people. In hushed tones. As shame. As something to hide, to pray away, to be ashamed of in front of relatives. I have seen families isolate these children, and I have seen the children pay the price for our silence and our fear.

So let me say it plainly, as a Nigerian mother, in a Nigerian paper. My autistic son is not a punishment. He is not a curse. He is not a lesser version of a real child. He is a whole human being, of immense worth, who has enriched my life beyond anything I could have planned. And the shame that surrounds children like him belongs not to them, but to a society that has not yet learned to see them.

This is the work I have given my life to. Becoming his voice in every room he cannot speak in. Building a centre that bears his name. And trying, in whatever way I can, to change how our people see these extraordinary children, so that the next mother holding a baby like mine is met with understanding instead of pity, and welcome instead of shame.

If you are a parent reading this tonight, sitting in the chair I once sat in, mourning a future you had already written, I want to say one thing to you.

Put the script down. Gently, and without guilt. The grief is real and you are allowed it. But do not let it keep you from the child who is actually in front of you, the real one, who has been waiting this whole time to be met as he is rather than as you imagined him.

Go and meet your actual child. You may find, as I did, that the son you were given is worth more than all the dreams you lost. A man called Akintade is here. He has changed me. And if his story changes how even one family sees their own child, then every dream I once grieved was a small price for the one I was given instead.

Folu is the mother of Akintade, a Tech Leader, founder of Tade Autism Centre, Neurohelp.ai, and ATSI Charity. She is an autism advocate working to change how autism is understood and embraced.

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Tech and Humanity

Tech and Humanity: The Tribunal Ruling That Should Change How Africa Thinks About AI

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By Folu Adebayo

A lawyer in the United Kingdom needed to summarise a confidential client document. Forty pages. A busy day. So they did what millions of professionals around the world now do without a second thought.

They pasted it into an AI tool.

Faster than reading it line by line. Nobody had told them not to. Nobody had told them they could. There was no policy. No training.

No record of the decision.

It seemed harmless. It was not.

A UK tribunal has now ruled that uploading confidential documents to an AI tool can be treated as the equivalent of placing them in the public domain. The legal privilege protecting those documents, the confidentiality that is the very foundation of the relationship between a professional and their client was lost. Permanently.

Not because anyone acted in bad faith. Because the tool did what such tools do the moment information is entered into them.

“The employee was not trying to do anything wrong. They were trying to work faster.”

Why this matters far beyond the United Kingdom

It would be easy for African business leaders to read this as a distant story. A British tribunal. A British case. A British problem.

That would be a mistake.

The behaviour at the centre of this ruling a professional pasting confidential information into an AI tool to save time is happening in every law firm, every bank, every hospital, every government office, and every consultancy in Lagos, Nairobi, Accra, and Johannesburg right now. Today. As you read this.

The technology does not respect borders. The behaviour does not respect borders. The risk does not respect borders.

The only thing that varies from country to country is whether there is a governance framework in place to manage it and whether the people using these tools have been told, clearly, what is and is not permitted.

In most African organisations, that framework does not yet exist.

The quiet leak

Consider what is most likely happening inside your own organisation as you read this.

A member of staff has a long report to summarise. They paste it into a free AI tool.

A colleague is drafting a difficult email and asks an AI assistant to improve the wording including the confidential context. Someone in finance uploads a spreadsheet of sensitive figures to ask the AI to analyse it. A junior employee, eager and capable, uploads a client contract to extract the key terms quickly.

None of these people are acting maliciously. Every one of them is trying to do their job well.

And every one of them may be moving confidential information client data, commercial secrets, personal information, privileged material outside the protected boundary of the organisation.

This is not a hypothetical risk. Industry research suggests that the overwhelming majority of organisations have employees using AI tools, while only a small minority have any policy governing what may be entered into them. The gap between adoption and governance is not narrowing. It is widening.

“The technology does not respect borders. Neither does the risk.”

Why Africa is particularly exposed
There are three reasons this risk is especially acute across African markets.

First, AI adoption across Africa has been rapid, mobile-first, and largely informal. Professionals have embraced AI tools with energy and ingenuity often ahead of the organisations they work for. That is a strength. But it means usage is running far ahead of governance.

Second, many African organisations do not yet have the data protection infrastructure, the internal compliance functions, or the governance frameworks that would, in other markets, provide at least some guardrails. The legal frameworks are developing , Nigeria, Kenya, Ghana and South Africa have all made significant progress on data protection but the translation of law into day-to-day organisational practice remains incomplete.
Third, the consequences of a confidentiality breach are severe in any market, but in markets where trust is hard-won and reputational damage spreads quickly, the cost can be existential. A bank that leaks customer data, a law firm that loses privilege over client documents, a hospital that exposes patient information these are not recoverable inconveniences. They are breaches of the trust on which the entire business depends.

What African leaders must do now
The good news is that the solution is neither expensive nor complex. It does not require new technology. It requires leadership, clarity, and a small amount of disciplined effort.

First, establish a clear AI usage policy. A single, plain-language document that states what types of information may and may not be entered into AI tools. It does not need to be sophisticated. It needs to exist, and it needs to be communicated.

Second, train your people. Not a lengthy programme a clear, honest conversation. Most employees who create AI-related risk do so because nobody has explained the danger to them. Once they understand, the overwhelming majority adjust their behaviour immediately.

Third, create a record. The UK tribunal ruling makes clear that when accountability is tested, organisations will be expected to demonstrate that their people understood the rules. A simple, dated record showing that staff have received and acknowledged the AI usage policy is no longer an administrative nicety. It is a protection.

Fourth, lead by example. When senior leaders talk openly about responsible AI use, it gives everyone else permission to ask the questions they are currently afraid to ask.

The opportunity inside the warning
It would be easy to read this column as a reason to fear AI, or to restrict it. That is not my intention.

AI is one of the most powerful tools African professionals have ever had access to. It can close capability gaps, accelerate work, and allow small organisations to compete with much larger ones. The answer is not to ban it. The answer is to govern it.

The organisations that will thrive in the African AI economy are not the ones that move fastest or the ones that move most cautiously. They are the ones that move deliberately adopting AI with energy, and governing it with discipline.

The UK tribunal ruling is a warning. But it is a warning delivered early enough to act on. African leaders who read it, understand it, and act on it now will protect their organisations, their clients, and their reputations.

Those who treat it as someone else’s story will learn the same lesson later and at a far higher price.

The choice, as always, belongs to leadership.

Folu is AI Architect & Risk & Governance Director, United Kingdom, Founder of AIExpertsPro, and an AI governance advisor to UK and African financial institutions, and can be reached via aiexpertspro.co.uk/folu@aiexpertspro.co.uk

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Tech and Humanity

Tech and Humanity: The AI That Fired 1,000 People And Nobody Could Explain Why

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By Folu Adebayo 

Imagine arriving at work one morning to find that a decision has been made about your future. Not by your manager. Not by your CEO. Not even by a committee that reviewed your performance, your contributions, or your years of service.

By an algorithm.

And when you ask why, when you look across the room at the people who deployed that algorithm and ask them to explain how it reached its conclusion, they cannot tell you.

Not because they are hiding something. But because nobody thought to ask that question before they pressed the button.

This is not a hypothetical. It is happening right now. And it is coming to Africa faster than most leaders realise.

The numbers are staggering

In 2025 alone, nearly 55,000 job cuts were directly attributed to AI, according to Challenger, Gray & Christmas, out of a total 1.17 million layoffs, the highest level since the 2020 pandemic. The companies involved read like a who’s who of global business. Amazon. Workday. Meta. Google.

In early 2026, major firms including Meta, Google, Amazon, Block, Atlassian, Pinterest, and Salesforce announced significant layoffs while explicitly linking cuts to productivity gains from AI tools. Block cut close to 40% of its workforce more than 4,000 roles with leadership arguing that AI tools and flatter organisational structures are changing how companies are built and run.

Baker McKenzie, the global law firm, laid off between 600 and 1,000 employees up to 10% of its global workforce e4 as part of a shift towards AI, primarily affecting support staff including roles across research, marketing, and secretarial functions.

These are not small numbers. These are people’s livelihoods. Families’ security. Communities’ stability.

And in almost every case, the same question went unanswered: on what basis, exactly, did AI determine that these specific people should go?

“When an AI system makes a decision and those who deployed it cannot explain its reasoning, accountability evaporates.”

The accountability black box

Many AI systems operate as black boxes, obscuring decision-making processes that affect employment. This opacity complicates responsibility attribution when AI systems produce harmful outcomes.

This is the governance crisis hiding inside the AI revolution.

When a human manager makes a redundancy decision, there is a process. There is documentation. There is a legal obligation to demonstrate fairness. There is, at minimum, a person who must look the employee in the eye and take responsibility for the decision.

When an AI system makes or influences that same decision and the people who deployed it cannot explain its reasoning accountability evaporates. The employee loses their livelihood. The organisation faces reputational and legal risk. And somewhere in between, the question of who is responsible gets lost in the technical complexity.

This is not just a legal problem. It is a moral one.

AI-washing the new corporate cover

A January 2026 Forrester report was blunt: many companies announcing AI-related layoffs do not have mature, vetted AI systems. The term “AI-washing” has entered the business lexicon to describe companies that attribute workforce reductions to AI-driven efficiencies when the underlying reasons are more financially pedestrian.

In other words: some of these organisations are not using AI to make better decisions. They are using AI as a convenient explanation for decisions they had already made for other reasons.

This is a governance failure of a different kind. Not the failure to control AI but the failure to be honest about what AI is actually doing, or not doing, inside your organisation.

The research that should stop every board in its tracks

Companies reporting high ROI from AI were not the same ones reporting AI-related workforce reductions. “That’s not where the value is,” said one Gartner analyst. “That’s not where the productivity gains are going to be.”

Instead, the study found companies with the highest gains were those using AI as a form of people amplification implementing the technology to make workers more productive rather than outright replacing them.

Read that again.

The organisations getting the most value from AI are not the ones firing people. They are the ones making their people better.

The organisations firing people and attributing it to AI are, in many cases, getting worse returns, not better ones.

The narrative that AI necessarily means fewer people is not just ethically questionable. It is, according to the evidence, strategically wrong.

“Africa has a choice that companies already down this road did not fully exercise.”

What this means for African businesses

I want Nigerian and African business leaders to sit with this carefully.

The pressure to deploy AI is real. The competitive and cost arguments are real. And the global trend toward leaner organisations is real.

But Africa has something that the companies making these decisions in Silicon Valley and London often lack: the wisdom born of building in difficult conditions, the understanding that people are not just costs to be optimised, and the institutional memory of what happens to communities when employment disappears without accountability or explanation.

AI is not killing jobs outright, it is hollowing them out, steadily absorbing discrete tasks, narrowing roles, and compressing wages. Those whose work depends on judgment, context, and accountability may find a useful collaborator in AI. Everyone else may find themselves doing less, earning less, and wondering how it happened.

African organisations have a choice that the companies already down this road did not fully exercise. They can build AI governance frameworks that require explainability before deployment. They can insist that any AI system influencing employment decisions must be able to justify those decisions in plain language. They can hold their technology providers accountable for the outputs not just the inputs of their systems.

And they can choose, deliberately and explicitly, to use AI as the research suggests it works best: not to replace people, but to make them more capable.

The question every board must answer

If your organisation is using or planning to use AI in any process that touches employment — recruitment, performance management, workforce planning, redundancy selection — you must be able to answer one question before you proceed.

If an employee asks why this decision was made about them, can you explain it?

Not in technical terms. Not by pointing to a model. In plain, honest language that a reasonable person could evaluate and challenge if they believed it was wrong.

If you cannot answer that question, you are not ready to deploy that system.

The AI that fired 1,000 people and nobody could explain why a story about technology is not just.

It is a story about what happens when organisations deploy power without accountability.

Africa has seen that story before. In different forms, through different instruments.

We do not need to repeat it.

Folu is AI Risk & Governance Director, United Kingdom, Founder of AIExpertsPro, Neuohelp.ai, AI governance advisor to UK and African financial institutions. She writes weekly on AI governance and responsible technology for The Boss Newspaper.

aiexpertspro.co.uk  |  folu@aiexpertspro.co.uk

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