In April 2025, Microsoft released an update to Copilot Enterprise designed to enhance productivity. It introduced a live Python sandbox powered by Jupyter Notebook, a dream feature for developers who want to execute and test code seamlessly. But that dream quickly turned into a cautionary tale.
A few months later, researchers at Eye Security discovered that the sandbox wasn’t just live. It was vulnerable. With the right trick, attackers could gain unauthorized root access to Copilot’s backend container. For product managers, developers, and tech-savvy creators relying on AI tools, this means a feature designed to help write better code suddenly hands attackers the keys to the system.
The Sandbox Illusion: Productivity Meets Hidden Risk
At first glance, the feature sounded great. Developers could write, test, and debug Python code directly within Copilot’s environment, similar to what OpenAI’s Code Interpreter does. But this live coding capability introduced a deep-seated vulnerability: under the hood, Copilot’s environment launched certain processes with root privileges, and failed to enforce basic security hygiene.
Copilot’s entrypoint.sh script ran a service (keepAliveJupyterSvc.sh) as root. That script used the pgrep command to keep the environment alive. Unfortunately, it didn’t specify the full path to the command. Instead, it relied on the $PATH environment variable, and one of the directories listed first was writable.
That opened the door for attackers to upload a fake pgrep script into that directory. Once Copilot ran it, the script executed arbitrary commands, with root privileges, inside the container.
The exploit wasn’t some futuristic AI vulnerability. It was an old-school Linux trick, hiding inside a shiny new AI-powered shell. And that’s what makes it so dangerous. A full technical detail is available here.
Here’s a developer-focused breakdown in table form that makes the sequence and risk clear:
| Stage | What Happened | Technical Detail | Risk/Impact |
| 1. Initial Setup | entrypoint.sh started keepAliveJupyterSvc.sh as root. | The service script runs with full privileges inside the container. | Running as root increases the blast radius of any compromise. |
| 2. Command Usage | keepAliveJupyterSvc.sh used pgrep to keep the environment alive. | Instead of /usr/bin/pgrep (full path), it just called pgrep, relying on $PATH. | Leaves command resolution to the environment, introducing path-hijacking risk. |
| 3. Path Weakness | $PATH included a writable directory placed before system directories. | Attackers can place malicious executables in that writable path. | Any unqualified command call could run attacker’s binary instead of the intended one. |
| 4. Exploit | Attacker uploads a fake pgrep script to writable directory. | Script contains arbitrary commands. | On execution, malicious code runs as root inside the container. |
| 5. Execution | Copilot runs the fake pgrep. | Since it’s first in $PATH, the system chooses the attacker’s file. | Arbitrary code execution with root privileges. |
| 6. Why It’s Dangerous | It’s a classic Linux PATH hijack, not AI-specific. | Simple, well-known exploit buried inside an AI-driven workflow. | Low-complexity, high-impact—easy for attackers, severe if overlooked. |
Classic Bug, Modern Wrapping: Why This Flaw Matters
While Microsoft patched the issue in July 2025 and rated it as “moderate,” the implications run deeper than a single fix. AI tools like Copilot are increasingly embedded into workflows, development pipelines, and even creative tools used by modders and digital creators.
The root access vulnerability exposed more than just the backend filesystem. Researchers hinted that they found routes to Microsoft’s Responsible AI Operations panel and 21 internal services through potential Entra OAuth abuse, which is a serious escalation if validated.
Although the exploit didn’t result in any known data leaks, the real threat is what could have happened.
With root access, a determined attacker could:
- Install persistent backdoors: This allows them to sneak back in anytime
- Interfere with container operations: It could slow down operations or break features.
- Manipulate files and settings: They could change or delete important data or configurations.
- Stage lateral attacks: Use this system to break into others on the same network.
And in AI tools built to run code and interact with cloud services? That kind of power is a loaded gun.
What Devs and Users Can Learn from This
If you’re a developer, modder, or creator relying on AI tools to run or generate code, this should raise some red flags.
Tools like Copilot are more than just suggestion engines. They’re execution environments. And if those environments aren’t locked down, your workflows could be at risk, especially if AI starts executing code from inputs you didn’t fully review.
Here’s what developers and product teams should take away:
- Use absolute paths in critical scripts – Don’t rely on $PATH. Don’t assume binaries are safe just because the environment looks “standard.”
- Drop root privileges early and permanently – Containers should run with the least privilege possible. If anything needs root, isolate it.
- Audit writable directories – Especially those included in environment variables or accessible via uploads.
- Inspect AI execution behavior regularly – Even helpful assistants like Copilot can behave unpredictably if the sandbox isn’t well-guarded.
Will AI Tools Like Copilot Keep Having These Issues?
That seems likely to be the case. As AI-powered coding tools become more advanced, they’ll take on more responsibilities, from file management to cloud deployments. But that flexibility also expands the attack surface.
We’ve already seen issues in tools like ChatGPT’s code interpreter (which runs in a secure sandbox, but still limits file access) and Google’s AI integrations in its IDEs. The more these tools can do, the more they can be abused.
To protect your systems and projects:
- Keep AI tools updated – Microsoft patched the Copilot vulnerability quickly, which is great. But that only works if you apply the update.
- Monitor how AI-generated code behaves – Treat it like you would code from a new intern: double-check it before it gets pushed to prod.
- Participate in security communities – Support bug bounty programs and stay engaged with researchers.
The Real Risk Is Trust Without Transparency
At the heart of this story is a reminder of how we place invisible trust in the tools we use.
When you prompt an AI to generate code, write an email, or automate a process, you’re trusting it, and the platform running it, to behave safely. But as tools like Copilot evolve, users lose visibility into what’s happening behind the scenes.
This incident shows how even a tiny oversight can become a major weakness. And it calls for a shift in how we think about AI tooling.
Because the next AI bug might not just be a cautionary warning. It might be the one that doesn’t get caught in time.
And if you’re a gamer or creator using Copilot to mod, script, or streamline workflows, keep your eyes open. These aren’t abstract risks anymore. They’re happening right where we build and play.
