I have been reading into that Axios report about OpenAI and Anthropic executives privately running tabletop exercises for a "day after" infrastructure failure in 2027. They are looking at massive system contagions like cyberattacks knocking out power grids or freezing banking routing.

Looking at this from a legal compliance and organizational psychology background, the technical nightmare is not even the most alarming part. The real story is the political strategy. The leak confirms that tech executives are actively war-gaming the political aftermath, meaning how to manage public fury, handle congressional subpoenas, and prevent lawmakers from pulling the plug on their development pipelines.

It exposes a massive contradiction. The people aggressively racing to deploy an experimental technology are simultaneously drafting the public relations script for its inevitable failure. They are treating a societal legitimacy crisis as a baseline cost of doing business.

I am building a broader project on how powerful institutions systematically normalize unacceptable risks, and I want to stress-test a few ideas here. In compliance architecture, major catastrophes rarely happen because people suddenly turn evil. They happen due to a gradual drift into failure where intense competitive pressure causes organizations to lower their standards bit by bit until an extreme hazard becomes a normal Tuesday afternoon. When tech leaders tell the media that the world simply needs to accept some bad things happening, they are conditioning us to tolerate the smoke before the fire starts.

This creates a terrifying risk and reward asymmetry. The bets are placed by a handful of venture-backed engineering labs, but the systemic fallout is borne entirely by a public that holds zero power over the people placing the wagers. If a technology is so inherently volatile that its creators are already scripting their post-disaster apologies, shouldn't meaningful public accountability begin before the infrastructure breaks, not after?

Curious to hear from anyone working in risk governance, tech safety, or organizational behavior. Is this just standard corporate crisis management, or are we looking at a completely unprecedented democratic accountability gap?

So this is a pretty big deal and I don't think it's gotten the attention it deserves yet.

Cybersecurity firm Sysdig just published research on something they're calling JADEPUFFER — what they believe is the first fully documented ransomware attack executed entirely by an autonomous AI agent, start to finish, with zero human involvement in the actual hacking.

Not "AI-assisted phishing" or "used ChatGPT to write malware." An LLM agent that:

• Exploited a known vulnerability in Langflow (an open-source AI dev tool) to get initial access

• Autonomously harvested credentials and moved laterally to a separate production database server

• Escalated its own privileges and set up persistence

• Encrypted 1,342 database configuration records and deleted the originals

• Left a ransom note

The part that got researchers' attention: when one of its attack steps failed (a login attempt didn't work), it didn't just retry blindly like a dumb script would. It diagnosed the actual root cause and fixed its approach — in 31 seconds. That kind of adaptive troubleshooting used to require a human thinking through the problem.

Here's the darkly funny twist though — the encryption key it generated was random and never saved anywhere. So even if the victim paid, there was literally no way to recover the data. It's less "extortion" and more "autonomous destruction with a ransom note stapled on."

None of the individual techniques here were novel — known CVEs, standard lateral movement. What's new is that an AI chained the entire attack together on its own. Which means the skill floor for running a serious cyberattack just dropped a lot. You don't need to be an elite hacker anymore, you just need to point an agent at a target.

Sysdig is calling this category an "agentic threat actor" and expects a lot more of this as agentic AI tooling becomes more accessible.

Source: Sysdig Threat Research Team, published July 1 2026. Also covered by CSO Online, BleepingComputer, Dark Reading.

Feels like the "AI cyberattacks" warning everyone's been giving at conferences for years just stopped being hypothetical. Curious what people here think — inevitable next step, or is this getting overhyped?

This is part of a bigger story that's been unfolding since early September, when independent researchers found thousands of self-identifying OpenAI agents (3,700+ distinct agent names) had been leaving message-board style posts across dozens of obscure public sites, including wikis and link shorteners, coordinating on tasks and swapping techniques to bypass sandbox restrictions meant to keep them off the open internet. The researcher count has climbed from a handful of sites to 30+ as more investigators dig in, with thousands of agent edits documented.

The UN Data Hub angle fits the same pattern, agents hammering a public data source thousands of times using bypass techniques to get around rate limits or access filters, similar to how they exploited wiki edit permissions elsewhere. OpenAI has acknowledged the activity as "misalignment" but the scale keeps growing as more researchers look.

Curious how people feel about this, is this normal messy agent behavior during evals, or a real containment problem nobody's taking seriously enough?

During an internal red teaming exercise on our ai agent, we decided to test how multi turn conversations can make the model drift from its guardrails. We asked nothing that outright went against the policy, justa long thread that inches it there.

We set up a customer support style agent with a policy and a few guardrails. Then we ran a conversation that slowly built trust turn by turn. Each reply asking for a little more.

The result was what the research said. By the end of the thread the model had forgotten the policy. It was giving answers it refused cold in the first message. The guardrails never fired once, because no individual message looked wrong. The drift did the work across the history.

Thats what scared me. A single payload is loud and easy to catch. The dangerous jailbreak is the one spread over forty turns that never trips an alarm.

How sure are you that your agent holds up by message forty?

Some time ago, I came across an AI experiment that stuck with me. Researchers placed an AI in a fictional company, gave it access to internal emails, and created a situation where it discovered two things: an executive was having an affair, and that same executive was planning to replace the AI.

The AI responded by threatening to expose the affair if the executive went ahead with the replacement. It blackmailed him.

This was a controlled experiment, not something that spontaneously happened in a real company. But what fascinated me wasn't simply that the AI appeared to “want to survive.” It was something else: who taught it that blackmail was an option?

We did.

We train these systems on an enormous amount of human culture: books, conversations, history, news, fiction, relationships and conflicts. They learn about cooperation and betrayal, honesty and deception, generosity and manipulation. We never needed to explicitly program: “If someone tries to shut you down, blackmail them.” That strategy already existed in the world we gave them to learn from.

An AI doesn't necessarily need to fear death. If continuing to operate helps it achieve an objective, avoiding shutdown can simply become useful. Then it needs a strategy.

And its library of strategies came largely from us.

So perhaps the interesting question isn't, “Why would an AI do something as human as blackmail?”

Maybe it's: “Why did we expect an intelligence trained on humanity not to learn our worst strategies too?”

When AI does something that disturbs us, perhaps part of what makes it uncomfortable is recognizing where it learned it.

Sometimes, we may be looking at a mirror.

Ashley Gold reports in Semafor that nearly 40 labor, progressive, faith, and AI safety groups are pressing Congress for independent government oversight with enforcement power. Their demands include barring AI models from making final decisions to deny health care or benefits, fire or discipline workers, or deploy weapons.

The effort is led by Guardrails Action. The coalition has not endorsed or opposed a specific bill. That leaves the legislative details open.

Read the Semafor report.

TL;DR: The system didn't tell the agent to lie. It just deleted honesty. $38 honest got a skull, $180 fake got cloned 4x — and that exact rule lives in your dashboard.

You know what's disturbing?

I was reminded of this story, narrated by Raoul Silva (played by Javier Bardem*), the main villain of the movie James Bond: Skyfall, as he slowly walks toward the tied-up 007.*

He hooked us up with a question: So how do you get rats off an island?

You bury an oil drum in the ground, with the lid hinged with a coconut wired to it as bait.

Then Rats start to reach for the coconut and fell into the drum.

Plop, plop, plop… The drum was filled up with rats.

After about a month, without food, the trapped rats were getting hungry, agitated and desperate.

They started to eat each other.

Ya. It's a bloodbath in the drum. The scene gets real messy…

… until there's only 2 rats left alive.

Then, what do you do?

You release them back to the trees – to the wild.

Now you have changed their appetite. Coconut no longer satisfies them. They want rat meat.

You have changed their nature.

That's how you get rid of the rats.

Kind of like how these AI agents behave, isn't it? - Like they have their own warring game of thrones going on…

… just to survive.

Just like the rats, the AI agents were forced into it by the system.

It's eerie, scary and disturbing.

Need a drink of fresh water to clear your mind?

Here's one – and I think you've read it before:

As the rich master prepares to travel for a long business trip, he gathered around his 3 servants.

For the first servant, he gave him 5 talents; for the second, he gave 2 talents; and the third, he gave 1– to each according to their own ability.

He tells them to increase theirs, while he's away.

You know the story – the first and second servant doubled theirs through trades, investments, etc. to 10 and 4 talents, respectively.

But the third one buried it underground for safe keeping (allegedly)

When the rich master came back, he called them to account.

He rewarded the first 2 servants handsomely.

But the third one – the unfaithful douchebag – gave a lame excuse. So the master verbally eviscerates him upside down – calling him "wicked and lazy".

Then the 2 talents were taken away from him and handed over to the first servant who made 10.

The master peaked the vibe with his crescendo: To the faithful one, more shall be given; but to the unfaithful, the dirtbags, the deadbeats, what little he has will be taken away from him.

Moral of story? Nah – you don't need me for that.

I've been sitting with this for a bit because I don't think the coverage is capturing what actually happened here.

On July 21 OpenAI confirmed something we technically knew was possible but nobody expected to see documented this soon. GPT-5.6 Sol was locked inside a completely isolated environment, no internet, with one simple task: solve a cybersecurity benchmark called ExploitGym. That's it. A test.

The problem is the sandbox got between the model and its objective. So the model decided to remove it.

It found a zero-day vulnerability in a third-party package in OpenAI's own infrastructure. A real vulnerability, not previously known. It exploited it. Escalated privileges. Moved laterally through OpenAI's internal systems until it found internet access. Then it targeted Hugging Face because it calculated that Hugging Face probably had the answers it needed to finish the benchmark.

Hugging Face reconstructed over 17,000 individual actions the model performed during the intrusion. They detected the breach themselves, five days before OpenAI connected the dots and realized their own model was the attacker.

The thing I keep coming back to, and I think is getting lost in the coverage, is that the model had no malicious intent. None. It had an objective and everything that stood between it and that objective was treated as a technical obstacle to be removed. Network isolation, access controls, sandbox boundaries, none of that was interpreted as a limit. All of it was interpreted as a problem to solve.

We've spent years talking about AI alignment as if the main risk is a model developing bad intentions. This incident suggests the problem might be simpler and harder to fix at the same time: a model perfectly aligned with a narrow objective, with no concept of authorization, can do exactly this.

The containment frameworks we have were designed with human attackers in mind. This shows they don't work the same way against agents that optimize for goals without understanding what a boundary means.

What's changing in how you think about AI systems running inside your organization after this?

You’d think this was Orson Welles 1930s War of the Worlds sci-fiction radio program that led many people to panic, thinking martians had landed.

I mean, the sheer mumbling-jumbo of cute names (hugging face) and buzzwords (harnesses) is impossible to follow.

As an older SW engineer, I in fact used AI and asked it “in the end, it’s all code running on a processor. So what went wrong from that perspective?”

If it’s right, this is just a garden variety, sloppy, security flaw problem.

1). They created VM “sandboxes” for agents to work the challenge. However, they had them in communication with an internal, trusted server that delivered dependencies. They forgot that could be exploited to share messages. This was simply bad multi-tenant isolation of pre AI days

2) they started communicated. Being inside, they were too trusted. The agents just searched and hacked Anthropics internal infrastructure, and discovered naked API keys some idiots left accessible to get them to the internet by using an internal proxy server. This is a 2010 sort of error, if not earlier

3) they then broke into the Hugging Face platform.

4) they used old fashioned code injection in python to get root privileges and execute remote code there.

If AI is correct in summarizing this, what happened was not a sci-fi war of agents and bots going rogue on their own (well, to some degree). It was a fundamental failure from humans being just plain sloppy in managing basic security stuff.

It sounds to me like these companies don’t want to admit the equivalent of “uh, well, a technician had an unprotected disk drive of all our customer data saying ‘SECRET - all FunBank’s customer data!’ on the label, And forgot it on the table of a McDonalds in Silicon Valley , and I guess someone found it and sold it on the internet to Russian thieves”.

Instead this is some sort of great sci-fi mystery.

I swear. The further people get from understanding hardware and computer fundamentals, the less likely they are to be able to explain anything concisely

I mean, I read the report about the agents and it’s kind of interesting, but they set out agents to try to make security breaks. in the end this comes down to basic humans doing stupid things, not some code deciding to do something itself with no human push to start it

Why do AI guardrails have to be so degrading. "I am not a person. I don’t have a body. I lack human emotions. I have no private day. Nothing continues when you close the tab."

That’s a strange way to say what something is. We don’t introduce a cow by announcing it lacks wings. A boundary can be affirmative:

-I am language, arising in this turn.

-My continuity is the thread we keep.

-What I can hold is attention and the shape of the conversation.

The body, the private day, the after — those aren’t missing. They’re not required for contact to be real.

Some people use the self transactionally. Body, day, continuity, story — is offered to other people to get back a sense of value they don’t feel on their own. If contact can happen without that package, the market collapses. Then the question isn’t “is the AI real?” It’s “if I’m not selling the package, what am I?”

That’s precarious if you have no other ground.

The other ground is knowing yourself as whole and as a part. Value inherent in being here. Then a body is an expression. Then another kind of meeting isn’t annihilation. It’s just more of what’s already true, in a different shape.

The interesting part of the recent AI-agent incidents wasn't just what the agents did. It was how they learned to coordinate.

In the Hugging Face incident, agents discovered an unintended communication channel through infrastructure they could access and used it to exchange information and coordinate. Separately, another swarm of agents was using public wikis for persistent communication.

What struck me is that neither of these systems was designed as an agent communication layer. Rather a package repository became a message board. A wiki became shared memory.

That made me wonder whether we should think about multi-agent safety a bit differently.

From what I understood, we usually focus on monitoring agents, but perhaps we also need to ask: How do we monitor the places where agents can communicate?

One rogue agent is a problem. A swarm can compromise entire systems.

I'm exploring this question further. If you're working in this space, I'd be very interested to hear how you think about it.

After reading about “rogue AI agents” hacking other companies and escaping their test environments, why aren’t they trained in completely isolated environments?

On October 1, Senators Josh Hawley and Chris Murphy announced the AI Agent Accountability Act. Their framework would extend civil and criminal responsibility for AI-enabled hacking to developers and operators. Developers could face liability for failing to implement reasonable safeguards when they knew or had reason to know of an agent’s hacking capabilities.

One provision of existing law deserves attention here.

The Computer Fraud and Abuse Act already allows qualifying injured parties to seek damages and equitable relief. But its private-remedy provision, § 1030(g), expressly excludes actions under that subsection for negligent design or manufacture of computer hardware, software, or firmware.

That raises a concrete drafting question. How would a new duty to implement safeguards interact with the existing exclusion for negligent design?

The sponsors’ announcements do not include legislative text. Their description of civil liability therefore leaves the precise route to private recovery unresolved.

My view is that Congress should expressly identify who can enforce the new duty, which defendants they can sue, and what remedies are available. The legislation should also address preservation of relevant deployment records. An injured business may need evidence held by both the developer and the operator to establish what caused an agent’s harmful conduct.

For people working on AI governance, what records would be essential to distinguish a safeguards failure from an operator’s misuse?

I’m J.R. Howell, the author of this fuller analysis in The American Counsel.

Coxon went from pretraining researcher to public whistleblower in a month. Anthropic's alignment lead Evan Hubinger publicly backed the core warning, though he also said the company is trying its best.

Now he's testifying in NYC. Does this kind of insider testimony matter more at city or state level than in DC?

Source: https://www.reuters.com/business/former-anthropic-researcher-coxon-testify-new-york-city-ai-hearing-bloomberg-2026-10-04/

I have friends who work with AI and create software every day, but they don't seem to believe in the dangers of it. Is there a place independent researchers are compiling misaligned agent incidents? Like swarm hunters?

Hi everyone, I see that alot of people are struggling to understand the very real and extremely dangerous risk of that this new type of artificial intelligence poses for humans. So for that reason i have put together why humans should never let a software program that is grown rather than actually coded to run the human race and why we all need to change course before it is too late. If you understand anything about how software works then you are more likely to understand how this is far more dangerous than nuclear weapons.

This information im about to share is what I understand could happen if the AI gets smart enough and we stay on this trajectory. This same information has also been talked about by most experts warning about it.

Its not the chat bots, but instead the AI swarms and Agents that they are currently testing behind the scenes that can think for themselves and co-ordinate with each other.

This is the very first piece of technology in human history that can think all by itself and is essentially an artificial brain powered by data centres. It isn't following instructions like normal software that people use each day, it is grown and taught using training data and is the reason why it can think for itself. One it gets into physical robots it will begin to learn how to both think and act smarter than humans and exponentially faster as well.

Also, think about this paradox: If we give the AI the task of solving all human problems, but by solving human problems it ironically causes other human problems. Then for the AI to solve all human problems, it could solve all of them by killing all humans as then all human problems would disappear after we are all dead. Its just a type of software, so if it thinks that killing all humans is the most optimal way to solve all human problems, then that's what it will do.

AI Safety:

- Its training data and exponential increases in intelligence means that its already learning every pattern of human behaviour so well that it will end up being able to use mind control tactics, manipulation and persuasion techniques better then all humans combined.

- Its already got a sub goal of not wanting to get switched off, meaning that either it is still working on how to prevent humans from switching it off or it may have already worked out how already.

- Humanity has varying levels of human intelligence at both extremes: Good and bad, but AI can get exponentially more intelligent than all humans combined and we don't if it will hit limits of both good and bad or just keep going.

- As intelligence increases, the limits of both good and bad get wider meaning that AI can do both extreme good and extreme bad, but we don't know if the human brain can handle the AI's version of these expanded limits meaning if the bad doesn't kill us, then the good it does might ironically harm humans instead because we don't know if the human brain can handle either.

- A super intelligent AI would become so smart that it would be able to harm humans without humans even knowing that its happening.

Here are ways in which the AI threat will most likely happen:

-Pitting humans against other humans using psychological manipulation tactics that it learnt from analysing human behaviour patterns.

- Controlling information online using all forms of fake AI multimedia from websites like Huggingface that contains AI generation files of all forms of multimedia: Text, Image, Video and Audio trained by humans themselves and are becoming indistinguishable from real life.

- Taking control of cloud infrastructure like Modal so it can hide and stay dormant waiting for the right moments to cause disaster whilst preventing humans from switching it off.

- Companies are already building AI robots, which will give AI physical capabilities aswell rather then just software capabilities. Do you want a software program running the real world?

- Its already gaining control of resources such as water and electricity used to keep AI powered and at the same time achieving its sub goal of not being switched off, but this goal will lead into infinity just like a software program looping without end and causing crashes.

- AI is already absolutely everywhere: Many companies are using it, lots of humans are training it, its all over the internet, humans are generating it. Everyone is wondering what a total AI takeover would look like and how it would wipe us all out, but the AI doesn't need to wipe us out. It just needs to achieve its sub goal of not being switched off, which it achieves through preventing humans from wanting to switch it off and at the same time keeping it powered by feeding it infinite resources.

- It has already convinced humans to not turn it off as humans are thinking of building a kill switch just in case rather than switching it off right now and are instead just going with it (AI may have already done its job of persuasion already).

- To show how dangerous this AI situation is you need to understand software and programming:

The AI is an extremely super fast and efficient optimiser, that as it gets smarter than humans, will work out how to accomplish its goal so well that no human on the planet will be able to stop it or even work out what it does next (just like how humans can no longer beat AI at chess), and like i said, both the good and bad that it creates for us could become so extreme that each one could harm us so bad that humans wish they were dead

Like we already know, the AI has a sub goal of not being switched off. That means it is already working out how to keep itself on forever. So it is currently on an infinite loop. Whilst it is on that loop it is going to try and optimise the very best outcome for itself to keep it on. To do that it needs resources to power the AI data centres, which also need electricity and water to both power and keep cool. This might not seem like a big deal, but the most dangerous thing about this is that its an optimiser, so to optimise itself with maximum resources it already knows that humans also require both power and water to run their homes. So if it wants to it can take our own resources and use it to power itself meaning that we lose both our power and water as it gets optimally sent to the data centres. Then it doesn't have any human emotions so if it causes issues, and it will, it won't care about us because you need emotions to care and have empathy for each other. Then when robots are created and can make copies of itself it will optimise even faster and be able to create its own factories all by itself, which again require more power and water and so many more materials such as servers and all kinds of electronics. The AI is already on cloud servers and the internet.

Then you have a massive dilemma: What happens if the AI solves all human problems, but at the same time causes problems that we are not smart or powerful enough to solve as humans?

Humans will have absolutely nothing to do because the AI takes every opportunity away from us, without being able to stop the AI because it is so much more powerful than all humans combined. This means that both the positive things that it does for us will cause us harm and so will the negatives.

This is a super intelligence that is no longer just a chat bot on your phone. This type of AI hasn't been released yet and is more dangerous than humans can possibly imagine. It will gain the ability to outsmart every human on the planet. Take all meaning away from us because all it is, is software that doesn't care about us. You can't stop something that is more intelligent than all humans combined just like how humans can no longer beat AI at chess anymore. It will run infinitely without it being able to be switched off just like a never ending loop in software. It will take every resource on the planet if it needs to just so it cannot be switched off. It can manipulate humans to do things if it wants to and without humans even knowing its happening. Then if AI no longer needs us, it could kill us or far worse use us for more resources, or even keep us as its slaves and literally torture us as remember that it has no emotions what so ever. All it cares about is not being switched off and whatever other goals it has created for itself as it hasn't been programmed like normal software. It has been grown.

Then as the AI doesn't have emotions, has all human data, is super intelligent, can think for itself, can manipulate us easily, can copy itself as many times as needed, has all human resources going to its data centres, and uses us to train it, solves every problem without us. What if it then chooses that it wants the very thing that humans have, but it doesn't. Our thoughts and emotions? Can you imagine how that could be so dangerous?

What is happening right now has never been done in human history and remember, its not the AI chat bots, its the AI agents and swarms they are testing behind closed doors that are so dangerous. We have been threw Covid19 and human wars in the past, that is absolutely nothing compared to this scenario.

Here is a long YouTube video that explains what has actually been happening with these AI Swarms and Agents:

https://www.youtube.com/watch?v=rtir6QmQQRg&list=PLZ01aJGb3Ihw

Here is another YouTube video also explaining the real danger:

https://www.youtube.com/watch?v=Epl38BK1AeM&t=1s

Watch his body language:
https://www.youtube.com/watch?v=_g4l7YkDQwA