The $100,000 Token: How a ChatGPT Flaw Exposed Azure and Why Your Cloud Identity is Next


 A newly disclosed vulnerability inside ChatGPT has revealed how even the most advanced AI platforms can expose underlying cloud infrastructure — and why every business relying on cloud or AI services must pay attention.

Jacob Krut, a security engineer and bug bounty researcher at Open Security, uncovered the flaw while building a custom GPT, a personalized version of ChatGPT. The issue originated in the “Actions” feature — the part of custom GPTs that connects AI workflows to external services through APIs.

The problem?
These Actions relied on user-provided URLs that were not properly validated, creating a classic opening for a Server-Side Request Forgery (SSRF) attack.

SSRF vulnerabilities allow attackers to make unauthorized internal network calls using manipulated URLs — requests they should never have the ability to perform. In this case, the researcher used the flaw to access a local Azure Instance Metadata Service (IMDS) endpoint, a critical Azure component responsible for cloud instance configuration and identity management.

By querying IMDS, he was able to retrieve the Azure identity access token used by ChatGPT itself — a token that, if abused, could offer access to parts of the underlying Azure cloud infrastructure powering the platform.

OpenAI marked the vulnerability high severity and patched it quickly after receiving the report through its BugCrowd bug bounty program. While payouts for critical issues can reach up to $100,000, the researcher noted that average rewards recently have been under $800 — highlighting a gap between vulnerability impact and industry compensation norms.

Security experts say this is far from an isolated issue.
Christopher Jess, senior R&D manager at Black Duck, called it:

“A textbook example of how small validation gaps at the framework layer can cascade into cloud-level exposure… SSRF has been in the OWASP Top 10 since 2021 precisely because a single server-side request can pivot into internal services, metadata endpoints, and privileged cloud identities.”

This incident is a wake-up call: If an AI platform can be breached through something as small as a URL field, every business using cloud-connected apps or AI automation must rethink its security posture.

 

What Happened — A Deep Dive into the Vulnerability

A bug bounty researcher found a server-side request forgery (SSRF) flaw in the custom GPT “Actions” feature of ChatGPT.
Here’s how the exploit worked:

  1. The “Actions” section allowed users to input URLs which the GPT engine would call. Because user-provided URLs weren’t properly validated, that open endpoint became an SSRF vector.

  2. The attacker used this SSRF to access the cloud environment’s instance metadata service (IMDS). IMDS is designed for internal service identity and configuration, but here it was used to obtain identity credentials.

  3. By capturing an access token tied to the identity, the researcher demonstrated the potential for access to underlying cloud resources.

  4. The vendor rated the issue as “high severity” and patched the exploit after disclosure.

This kind of vulnerability shows how a feature meant for convenience (custom GPTs and external API calls) can suddenly place entire cloud workloads at risk.

Why This Is a Business Problem (Not Just a Tech Issue)

1. Cloud resources and identities are now prime targets

Businesses rely heavily on cloud platforms. If an attacker can hijack an internal identity token, they could pivot to your cloud workloads, data stores, AI models, or even internal networks—especially in multi-tenant or connected architectures.

2. AI/Chatbot features blur the attack surface

If your business uses AI assistants, custom integrations, or third-party webhooks, you may have opened a parameter or URL that can be abused just like the vulnerability above. The incident shows that “trusting the vendor” isn’t enough on its own.

3. Regulatory, compliance and reputational risk

If your cloud infrastructure or identity is compromised, you may face data breaches, non-compliance with HIPAA, SOC 2, ISO 27001 or other frameworks, and vendor-risk exposure. These are business risks that move beyond pure IT.

4. The hidden cost: exposure you didn’t know you had

This flaw didn’t require a direct device attack—it exploited backend service identity. Many businesses are focused on endpoint or network protections but overlook internal cloud service identity and API controls.

Solutions — How to Defend Your Business Now

A. Audit AI integrations & external API fields

  • Map every AI/chatbot tool and integration in your business that calls external URLs or APIs.

  • Ensure all URL parameters and webhooks are validated and restricted.

  • Lock down any metadata service endpoints, identity endpoints or internal cloud configuration interfaces.

  • Apply least-privilege roles to all service accounts and tokens.

B. Govern cloud identity & metadata endpoints

  • Verify that Instance Metadata Services (IMDS) in cloud platforms are properly restricted—not publicly reachable.

  • Use monitoring to detect unusual token requests, identity usage patterns or privilege jumps.

  • Enforce zero-trust rules: every requesting identity must be verified, logged, and limited to minimal access.

C. Strengthen API & SSRF controls

  • Conduct SSRF and parameter-manipulation tests on all webhooks, URL fields and AI integration points.

  • Deploy a Web Application Firewall (WAF) or API gateway with rules to restrict internal HTTP calls and block unauthorized endpoints.

  • Include regular API security assessments in your testing strategy—not just network or endpoint scans.

D. Perform vendor & AI service risk-assessment

  • Add third-party AI/ML platforms and custom integrations to your vendor risk register.

  • Ask vendors for evidence of their SSRF testing, metadata endpoint controls, service-account security and token management.

  • Ensure contract language reflects your right to audit or review their integration security controls.

E. Update your incident response & cloud-governance playbook

  • Include scenarios where cloud service tokens are compromised through SSRF or API abuse.

  • Ensure your response plan covers cloud workload isolation, token revocation, service identity change and privilege audit.

  • Conduct simulation drills that include the possibility of identity or metadata service abuses—not just classic endpoint breaches.

 

Final Thoughts

The vulnerability in ChatGPT’s architecture may have been discovered in a vendor system—but the risk it highlights touches every business using cloud services, AI integrations, or external APIs.

If you rely on AI tools, webhooks, cloud platforms or third-party integrations, your risk profile has just grown. Now is the time to audit, govern and reinforce your cloud/API defenses.

Don’t wait for your vendor’s bug bounty story to become your business’s nightmare.

Source: https://www.securityweek.com/chatgpt-vulnerability-exposed-underlying-cloud-infrastructure/


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