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GHSA-73hc-m4hx-79pj

MEDIUM

mcp-memory-service Vulnerable to System Information Disclosure via Health Endpoint

Also known asCVE-2026-29787
Published
Mar 5, 2026
Updated
Mar 9, 2026
Affected
1 pkg
Patched
1 / 1
Exploits
None indexed

EPSS Exploitation Probability

via FIRST.org ↗
0.4%probability of exploitation in next 30 days
Lower Risk29th percentile+0.34%
0.00%0.29%0.58%0.87%0.0%0.0%0.0%0.4%Apr 26Jun 26Jun 26

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

1 pkg affected
🐍mcp-memory-service

Real-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

The /api/health/detailed endpoint returns detailed system information including OS version, Python version, CPU count, memory totals, disk usage, and the full database filesystem path. When MCP_ALLOW_ANONYMOUS_ACCESS=true is set (required for the HTTP server to function without OAuth/API key), this endpoint is accessible without authentication. Combined with the default 0.0.0.0 binding, this exposes sensitive reconnaissance data to the entire network.

Details

Vulnerable Code

health.py:90-101 - System information collection

system_info = {
    "platform": platform.system(),              # e.g., "Linux", "Darwin"
    "platform_version": platform.version(),     # Full OS kernel version string
    "python_version": platform.python_version(),# e.g., "3.12.1"
    "cpu_count": psutil.cpu_count(),            # CPU core count
    "memory_total_gb": round(memory_info.total / (1024**3), 2),
    "memory_available_gb": round(memory_info.available / (1024**3), 2),
    "memory_percent": memory_info.percent,
    "disk_total_gb": round(disk_info.total / (1024**3), 2),
    "disk_free_gb": round(disk_info.free / (1024**3), 2),
    "disk_percent": round((disk_info.used / disk_info.total) * 100, 2)
}

health.py:131-132 - Database path disclosure

if hasattr(storage, 'db_path'):
    storage_info["database_path"] = storage.db_path  # Full filesystem path

Authentication Bypass Path

The /api/health/detailed endpoint uses require_read_access which calls get_current_user. When MCP_ALLOW_ANONYMOUS_ACCESS=true, the auth middleware grants access:

# middleware.py:372-379
if ALLOW_ANONYMOUS_ACCESS:
    logger.debug("Anonymous access explicitly enabled, granting read-only access")
    return AuthenticationResult(
        authenticated=True,
        client_id="anonymous",
        scope="read",
        auth_method="none"
    )

Note: The basic /health endpoint (line 68) has no auth dependency at all and returns version and uptime information unconditionally.

Information Exposed

FieldExample ValueReconnaissance Value
platform"Linux"OS fingerprinting
platform_version"#1 SMP PREEMPT_DYNAMIC..."Kernel version → CVE targeting
python_version"3.12.1"Python CVE targeting
cpu_count8Resource enumeration
memory_total_gb32.0Infrastructure profiling
database_path"/home/user/.mcp-memory/memories.db"Username + file path disclosure
database_size_mb45.2Data volume estimation

Attack Scenario

  1. Attacker scans the local network for services on port 8000
  2. Finds mcp-memory-service with HTTP enabled and anonymous access
  3. Calls GET /api/health/detailed (no credentials needed)
  4. Receives OS version, Python version, full database path (revealing username), system resources
  5. Uses this information to:
    • Target known CVEs for the specific OS/Python version
    • Identify the database file location for potential direct access
    • Profile the system for further attacks

PoC

# Show the system info that would be exposed
import platform, psutil

system_info = {
    "platform": platform.system(),
    "platform_version": platform.version(),
    "python_version": platform.python_version(),
    "cpu_count": psutil.cpu_count(),
    "memory_total_gb": round(psutil.virtual_memory().total / (1024**3), 2),
}
print(system_info)  # All of this is returned to unauthenticated users

Impact

  • OS fingerprinting: Exact OS and kernel version enables targeted exploit selection
  • Path disclosure: Database path reveals username, home directory structure, and file locations
  • Resource enumeration: CPU, memory, and disk info reveal infrastructure scale
  • Reconnaissance enablement: Combined information significantly reduces attacker effort for follow-up attacks

Remediation

  1. Remove system details from default health endpoint - return only status, version, uptime:
@router.get("/health/detailed")
async def detailed_health_check(
    storage: MemoryStorage = Depends(get_storage),
    user: AuthenticationResult = Depends(require_write_access)  # Require admin/write access
):
    # Only return storage stats, not system info
    ...
  1. Do not expose database_path - this leaks the filesystem structure:
# Remove or redact
# storage_info["database_path"] = storage.db_path  # REMOVE THIS
  1. Add auth to basic /health or limit it to status-only (no version):
@router.get("/health")
async def health_check():
    return {"status": "healthy"}  # No version, no uptime

Alternatively, Bind to 127.0.0.1 by default instead of 0.0.0.0, preventing network-based reconnaissance entirely:

# In config.py — change default from '0.0.0.0' to '127.0.0.1'
HTTP_HOST = os.getenv('MCP_HTTP_HOST', '127.0.0.1')

Users who need network access can explicitly set MCP_HTTP_HOST=0.0.0.0, making the exposure a conscious opt-in rather than a default.

Affected Packages

1 total 1 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPImcp-memory-serviceall versions10.21.0

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for mcp-memory-service. 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.

  2. Fix

    Update mcp-memory-service to 10.21.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-73hc-m4hx-79pj is resolved across your whole dependency graph.

  3. 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.

  4. How O3 protects you

    O3 pinpoints whether GHSA-73hc-m4hx-79pj 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-73hc-m4hx-79pj. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

### Summary The `/api/health/detailed` endpoint returns detailed system information including OS version, Python version, CPU count, memory totals, disk usage, and the full database filesystem path. When `MCP_ALLOW_ANONYMOUS_ACCESS=true` is set (required for the HTTP server to function without OAuth/API key), this endpoint is accessible without authentication. Combined with the default `0.0.0.0` binding, this exposes sensitive reconnaissance data to the entire network. ### Details ### Vulnerable Code **`health.py:90-101` - System information collection** ```python system_info = { "platf
O3 Security · Impact-Aware SCA

Is GHSA-73hc-m4hx-79pj in your dependencies?

O3 detects GHSA-73hc-m4hx-79pj across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.

GHSA-73hc-m4hx-79pj: mcp-memory-service Authentication Bypass… | O3 Security