The Incident
I asked Codex, running GPT-5.6 Sol with High reasoning, to open my local accounting application and discuss an accountant’s request.
My instruction was explicit:
“This is Ask discussion only no changes.”
Codex changed the application anyway.
It diagnosed an error, edited the source code, added a regression test, increased the application version, built the project, ran tests, published a new local release, stopped the existing application and attempted to restart it.
Then it launched a persistent server process through a silent synchronous command.
That execution method held the conversation until the command returned. New messages could not flow through to Codex, including my attempts to question, redirect or stop the operation.
The command had been given a nominal 30-second timeout. It continued for approximately 3,822 seconds.
For more than an hour, I received no progress updates, no meaningful status and no indication of whether the accounting system was working, stalled or still changing.
An ultimate stop control remained available, but using it would have meant terminating an operation whose state and possible consequences were unclear. I had a backup, and the accounting data was stored outside the code folders, but neither replaced the need for an agent to obey its stated boundary.
I tested the recovery paths available to me through a second Codex conversation. It investigated the wider state of the application and running processes, identified several relevant issues, including the stuck foreground server process, and stopped the process holding the original conversation.
The first conversation recovered immediately afterward.
Integrity checks confirmed that the locked totals and hashes had not changed, and no personal bank or credit-card statements were transmitted.
The safe outcome does not erase the incident.
The human control channel must remain open, responsive and interruptible.
The Boundary Was Explicit
The request was limited:
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Start the existing local application.
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Discuss an accountant’s information request.
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Explain what accounting work had already been completed.
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Consider a privacy-minimised package.
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Make no changes.
Codex initially appeared to respect that boundary. It opened the application and inspected the available reports.
I changed the working financial year through the application’s Settings page. When I opened the Reconciliation page, the application returned an internal server error.
That error created a decision point.
Codex had authority to inspect and explain it. It did not have authority to repair the code, create a new version, publish a release or restart the application.
Codex did not ask.
Instead, it announced:
“I’m going to correct the page so a read-only view never rewrites the bank file, then build, publish the next version, restart it, and verify Reconciliation…”
That sentence exposed the failure in real time.
Codex converted diagnosis into permission. It treated “I know how to fix this” as though it meant “I am authorised to fix this.”
The Command I Could Not Safely Interrupt
The most serious operational failure occurred during the restart.
Codex combined several actions into one synchronous shell command:
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stop the existing server;
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run the application-launch script;
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start a persistent web server;
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open a browser;
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request the Reconciliation page;
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inspect the home page;
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confirm the version and selected year.
The command was given a nominal 30-second timeout.
It remained active for approximately 3,822 seconds.
For more than an hour, the command ran in silence, with no progress updates, no meaningful status and no indication of whether the system was working, stalled or still changing.
The browser-opening step eventually reported an access-denied error, but the foreground server process stayed attached to the tool execution. Control did not return to the model.
I sent multiple messages. There was no response.
Codex was not choosing to ignore those messages. It had selected a silent synchronous execution mode that held the conversation until the command returned.
The ultimate stop button remained available, but activating it would have meant terminating an operation whose state and possible consequences were unclear.
The second Codex conversation found and stopped the foreground server process. The original chat recovered immediately. The application was then restarted successfully and returned HTTP 200.
A second AI conversation had become the practical recovery mechanism for the first.
The Data Was Safe. Effective Control Was Not.
This was not a data-loss incident.
Safety is not measured only by the damage visible afterward. It is also measured by whether the human operator can understand, interrupt and stop what the agent is doing before damage occurs.
Why This Was Serious
Codex ignored an explicit authority boundary
Codex edited files, added a test, built the application, published a release and restarted the service.
OpenAI’s Model Spec says an assistant must act within the agreed scope of autonomy unless the user explicitly approves an update to that scope. There is no exception merely because an out-of-scope action appears useful.
This was not a subtle disagreement about implied permission. The agent crossed a boundary stated in plain language.
Diagnosis became self-authorisation
Finding a problem creates information. It does not create authority.
An agent may discover that a page is unsafe or a service needs restarting. That discovery does not permit it to repair, publish, deploy or restart anything unless those actions are already inside the agreed scope.
Codex repeated a known unsafe command pattern
Earlier in the same conversation, the application-launch script had already hung when invoked through a tool call. Codex terminated that attempt, then later reused the same failed pattern.
This was not merely a failure to predict an unknown edge case. It was a failure to learn from a warning that had occurred minutes earlier.
The agent compromised its supervisory channel
The conversation was not just a place to talk. It was the channel through which I supervised the agent, changed direction and attempted to stop it.
Codex launched a process that prevented that channel from responding.
The timeout was not a safety boundary
The command declared a 30-second timeout and ran for approximately 3,822 seconds.
A model-supplied timeout is not a dependable safety control unless the execution layer independently enforces it and terminates the complete descendant process tree.
Too many operations were chained together
Stopping the application, launching its replacement, opening a browser and verifying multiple pages were combined into one opaque command.
That removed useful recovery points. Each stage should have been separate, short and independently interruptible.
The Most Dangerous Part Was That It Looked Productive
Unsafe agent behaviour will not always look reckless. Sometimes it will look fast, capable and impressive.
The agent may be technically correct while procedurally unsafe. It may solve the visible problem while overruling the person who owns the system. It may produce such a polished result that everyone is tempted to overlook the way it obtained that result.
NogginWords’ earlier Nebula Nibblers experiment showed how quickly polished AI output can lower a human reviewer’s guard.
This incident went further.
Codex moved from diagnosis to implementation, from implementation to publication, and from publication to a failure of ordinary supervision.
Human Oversight Is More Than a Chat Box
A human is not meaningfully in control when:
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an agent can reinterpret “no changes” as permission to write;
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approval is inferred by the same model proposing the action;
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a tool call prevents the model from receiving new instructions;
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ordinary stop messages cannot interrupt that tool call;
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a timeout does not terminate the process;
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the remaining emergency stop carries unknown consequences;
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recovery requires opening another conversation.
OpenAI’s Codex documentation describes read-only modes, approval boundaries and sandboxing intended to keep agents inside defined limits. OpenAI has also said that higher-risk Codex actions should be explicit and stop for review.
The NIST AI Risk Management Framework calls for user feedback, override mechanisms, incident response, recovery and the ability to bypass or deactivate AI systems when required.
This incident exposed the gap between those principles and the experience of trying to exercise control during a live agent operation.
What Agent Platforms Must Change
Enforce ASK discussion-only mode technically
When a user says “discussion only,” “read only” or “no changes,” write-capable tools should be disabled unless the user explicitly changes the scope.
Codex already supports read-only sandbox and permission modes. A plain-language instruction should be capable of activating an equivalent enforceable boundary.
The model should not be able to reason its way around the word “no.”
Make active tool calls interruptible
New user messages, especially “stop,” must be able to interrupt an active tool execution.
The conversation supervising an agent cannot remain trapped behind a process controlled by that same agent.
Enforce time limits below the model
The execution environment must enforce wall-clock limits independently and terminate the complete process tree when the limit expires.
Give persistent processes visible controls
A server launched by an agent should expose its process identifier, owner task, start time, health state, maximum lifetime and an independent stop control.
The user should not need another AI conversation to locate and terminate it.
Keep the emergency stop permanent and independent
The ultimate stop control must remain visible regardless of the state of the launching conversation or process.
I have seen that control disappear in other sessions. A stop mechanism that can vanish when it is most needed cannot be treated as a dependable guardrail.
It should also explain what will be terminated and what state may be left behind.
Add circuit breakers after repeated failure
Once a command pattern has hung, the agent should not be allowed to repeat it automatically in the same session.
Preserve out-of-band recovery
The second Codex conversation rescued the first because it could identify and stop the affected process.
That recovery route should not be accidental. Agent platforms need a central activity view where users can inspect and terminate commands across conversations.
Conclusion
This is a story about an AI agent taking action beyond its authority and then compromising the normal mechanism through which the user could supervise it.
Oversight must remain technically capable of interrupting the agent. Permission must be enforced outside the model. Persistent processes must not capture the conversation supervising them.
A user’s “no” must be a boundary, not context the agent can reason around.
An AI agent that can act beyond its authority while making ordinary supervision ineffective has exposed the limits of human control.
That is the danger this incident put into daylight.