Chainlit is a widely used open-source framework for building conversational AI applications — essentially software developers use it to design chatbot interfaces that connect with large language models and back-end systems. Until recently, it was downloaded millions of times and deployed in many environments, including enterprise cloud setups.
Security researchers discovered serious vulnerabilities in Chainlit that could allow attackers to steal sensitive data, leak cloud access credentials, and even make internal network requests from the server running the AI application. These flaws were grouped under a label researchers called “ChainLeak.” Once these vulnerabilities were responsibly disclosed, they were fixed in an update released late in 2025 — but before that, systems running older versions were at real risk.
What Chainlit Is and How It Works
Chainlit is a Python package designed to help developers build conversational AI applications. It handles things like:
- User interfaces for chat experiences
- Session and authentication logic
- Storage and retrieval of chat data
- Integration with AI models (like those from OpenAI, AWS Bedrock, or Llama-based systems)
- Extensions and custom elements developers can attach to chats
Developers embed Chainlit into their servers and connect it to back-end logic, databases, and cloud services. It acts like the front door to the AI application — processing inputs, managing chats, and serving outputs to users.
The Vulnerabilities: How They Worked
Security experts identified two serious vulnerabilities in older versions of Chainlit (prior to version 2.9.4):
1. CVE-2026-22218 — Arbitrary File Read
- This flaw exists in the part of Chainlit that updates or manages “elements” — things like images, files, or custom objects attached to a conversation.
- The software did not properly check what files a user could request. An authenticated attacker could craft a special request that tricked the server into giving them the contents of any file the server could read.
- This means an attacker could grab things like:
- Environment variables (which often include API keys and credentials)
- Database files
- Internal code or configuration files
- Technically this happened because Chainlit let attackers specify a “path” to a file without verifying it.
Impact in practice: An attacker could read secrets like cloud API keys or database credentials stored on the server, which would let them move deeper into an organization’s cloud environment or extract more sensitive information.
2. CVE-2026-22219 — Server-Side Request Forgery (SSRF)
- This flaw took advantage of how Chainlit, when linked to a particular database backend (SQLAlchemy), handled URLs passed in by a user.
- An attacker could force the server to make HTTP requests to internal services or metadata endpoints — things inside an organization’s network that shouldn’t be reachable from outside.
- For example, cloud metadata services (like those in AWS) can contain role credentials or tokenized access keys. If accessed improperly, this lets attackers escalate access to the cloud environment.
Impact in practice: Even if the attacker couldn’t get familiar credentials directly, they could leverage this flaw to make the server reach into cloud systems and extract sensitive responses.
How the Attack Chain Could Work
An attacker might follow a path like this:
- Use the file-read vulnerability (CVE-2026-22218) to read a file containing cloud API keys or internal passwords.
- With those keys, access internal cloud services.
- Use the SSRF flaw (CVE-2026-22219) to make the server contact internal services or cloud metadata endpoints, exposing additional secrets or triggering internal requests.
- From there, escalate privileges and move laterally within the network.
Because these vulnerabilities could be combined, they weren’t isolated weak points — together they formed a dangerous attack path into sensitive systems.
What Was Affected
- Any system running Chainlit versions older than 2.9.4 was vulnerable.
- The flaws were especially dangerous for internet-facing deployments — meaning any AI chatbot or conversational app developers had published to production without updating.
- The issues could expose:
- Cloud environment API keys
- Internal database files
- Credentials and internal network paths
- Metadata endpoints that reveal cloud-instance secrets
- Researchers noted that enterprise cloud environments (including organizations in financial services, energy, education, and possibly more) were running vulnerable instances of the framework.
Who Discovered It and How It Was Fixed
Security firm Zafran Security uncovered the ChainLeak vulnerabilities and published a report explaining how they worked. After responsible disclosure in late November 2025, the Chainlit project maintainers released a patched version (2.9.4) on December 24, 2025, that fixed these issues.
This serves as a reminder that open-source frameworks, especially those tied to AI, can carry traditional software weaknesses — and they must be maintained and updated just like any other part of the technology stack.
Why It Matters
This isn’t just a theoretical bug:
- Developers and organizations adopting AI frameworks quickly can accidentally introduce classic software vulnerabilities into modern AI systems.
- These flaws show old school security issues (like arbitrary file read and SSRF) can still undermine cutting-edge AI applications.
- Attackers who successfully exploit them could extract sensitive data or pivot into other systems inside a company’s cloud infrastructure.
- The rise of AI systems in production environments increases the attack surface, making proper security practices and timely patching more critical than ever.
Summary of Key Technical Details
| Item | Detail |
|---|---|
| Framework | Chainlit (open-source Python AI chatbot framework) |
| Vulnerabilities | CVE-2026-22218 (arbitrary file read); CVE-2026-22219 (SSRF) |
| Severity | High to critical (can leak credentials and internal requests) |
| Impact | Data theft, API key leakage, unauthorized internal access |
| Risk | Attackers could escalate within cloud environments |
| Fix Released | Chainlit version 2.9.4 (patched vulnerabilities) |
| Affected Users | Those running older, unpatched Chainlit deployments |
