PYSEC-2026-2623

Vulnerability from pysec - Published: 2026-07-13 14:36 - Updated: 2026-07-13 16:04
VLAI
Details

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

Field Example Value Reconnaissance Value
platform "Linux" OS fingerprinting
platform_version "#1 SMP PREEMPT_DYNAMIC..." Kernel version → CVE targeting
python_version "3.12.1" Python CVE targeting
cpu_count 8 Resource enumeration
memory_total_gb 32.0 Infrastructure profiling
database_path "/home/user/.mcp-memory/memories.db" Username + file path disclosure
database_size_mb 45.2 Data 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:
  6. Target known CVEs for the specific OS/Python version
  7. Identify the database file location for potential direct access
  8. 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.

Severity
5.3 (Medium)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N
Impacted products
Name purl
mcp-memory-service pkg:pypi/mcp-memory-service
Aliases
To clipboard 

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "mcp-memory-service",
        "purl": "pkg:pypi/mcp-memory-service"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "10.21.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "10.0.0",
        "10.0.1",
        "10.0.2",
        "10.0.3",
        "10.1.0",
        "10.1.1",
        "10.1.2",
        "10.10.0",
        "10.10.1",
        "10.10.2",
        "10.10.3",
        "10.10.4",
        "10.10.5",
        "10.10.6",
        "10.11.0",
        "10.11.1",
        "10.11.2",
        "10.12.0",
        "10.12.1",
        "10.13.0",
        "10.13.1",
        "10.13.2",
        "10.14.0",
        "10.15.0",
        "10.15.1",
        "10.16.0",
        "10.16.1",
        "10.17.0",
        "10.17.10",
        "10.17.12",
        "10.17.13",
        "10.17.14",
        "10.17.15",
        "10.17.16",
        "10.17.2",
        "10.17.3",
        "10.17.4",
        "10.17.5",
        "10.17.6",
        "10.17.7",
        "10.17.8",
        "10.17.9",
        "10.18.0",
        "10.18.1",
        "10.18.2",
        "10.18.3",
        "10.19.0",
        "10.2.0",
        "10.2.1",
        "10.20.0",
        "10.20.1",
        "10.20.2",
        "10.20.4",
        "10.20.5",
        "10.20.6",
        "10.3.0",
        "10.4.0",
        "10.4.1",
        "10.4.2",
        "10.4.3",
        "10.4.4",
        "10.4.5",
        "10.4.6",
        "10.5.0",
        "10.5.1",
        "10.6.0",
        "10.6.1",
        "10.7.0",
        "10.7.1",
        "10.7.2",
        "10.8.0",
        "10.9.0",
        "8.24.0",
        "8.25.1",
        "8.25.2",
        "8.26.0",
        "8.27.0",
        "8.27.1",
        "8.27.2",
        "8.28.0",
        "8.28.1",
        "8.29.0",
        "8.30.0",
        "8.31.0",
        "8.32.0",
        "8.33.0",
        "8.34.0",
        "8.35.0",
        "8.36.0",
        "8.36.1",
        "8.37.0",
        "8.38.0",
        "8.38.1",
        "8.39.0",
        "8.39.1",
        "8.40.0",
        "8.41.0",
        "8.41.1",
        "8.41.2",
        "8.42.0",
        "8.42.1",
        "8.43.0",
        "8.44.0",
        "8.45.0",
        "8.45.1",
        "8.45.2",
        "8.45.3",
        "8.46.0",
        "8.46.1",
        "8.46.2",
        "8.46.3",
        "8.47.0",
        "8.47.1",
        "8.48.0",
        "8.48.1",
        "8.48.2",
        "8.48.3",
        "8.48.4",
        "8.49.0",
        "8.50.0",
        "8.50.1",
        "8.51.0",
        "8.52.0",
        "8.52.1",
        "8.52.2",
        "8.53.0",
        "8.54.0",
        "8.54.1",
        "8.54.2",
        "8.54.3",
        "8.54.4",
        "8.55.0",
        "8.57.1",
        "8.58.0",
        "8.59.0",
        "8.60.0",
        "8.61.0",
        "8.61.1",
        "8.61.2",
        "8.62.0",
        "8.62.1",
        "8.62.10",
        "8.62.11",
        "8.62.12",
        "8.62.13",
        "8.62.2",
        "8.62.3",
        "8.62.4",
        "8.62.5",
        "8.62.6",
        "8.62.7",
        "8.62.8",
        "8.62.9",
        "8.63.0",
        "8.63.1",
        "8.64.0",
        "8.65.0",
        "8.66.0",
        "8.67.0",
        "8.68.0",
        "8.68.1",
        "8.68.2",
        "8.69.0",
        "8.70.0",
        "8.71.0",
        "8.72.0",
        "8.73.0",
        "8.74.0",
        "8.75.0",
        "8.75.1",
        "8.76.0",
        "9.0.0",
        "9.0.1",
        "9.0.2",
        "9.0.3",
        "9.0.4",
        "9.0.5",
        "9.0.6",
        "9.2.0",
        "9.2.1",
        "9.3.1"
      ]
    }
  ],
  "aliases": [
    "CVE-2026-29787",
    "GHSA-73hc-m4hx-79pj"
  ],
  "details": "### Summary\nThe `/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.\n\n### Details\n### Vulnerable Code\n\n**`health.py:90-101` - System information collection**\n\n```python\nsystem_info = {\n    \"platform\": platform.system(),              # e.g., \"Linux\", \"Darwin\"\n    \"platform_version\": platform.version(),     # Full OS kernel version string\n    \"python_version\": platform.python_version(),# e.g., \"3.12.1\"\n    \"cpu_count\": psutil.cpu_count(),            # CPU core count\n    \"memory_total_gb\": round(memory_info.total / (1024**3), 2),\n    \"memory_available_gb\": round(memory_info.available / (1024**3), 2),\n    \"memory_percent\": memory_info.percent,\n    \"disk_total_gb\": round(disk_info.total / (1024**3), 2),\n    \"disk_free_gb\": round(disk_info.free / (1024**3), 2),\n    \"disk_percent\": round((disk_info.used / disk_info.total) * 100, 2)\n}\n```\n\n**`health.py:131-132` - Database path disclosure**\n\n```python\nif hasattr(storage, \u0027db_path\u0027):\n    storage_info[\"database_path\"] = storage.db_path  # Full filesystem path\n```\n\n### Authentication Bypass Path\n\nThe `/api/health/detailed` endpoint uses `require_read_access` which calls `get_current_user`. When `MCP_ALLOW_ANONYMOUS_ACCESS=true`, the auth middleware grants access:\n\n```python\n# middleware.py:372-379\nif ALLOW_ANONYMOUS_ACCESS:\n    logger.debug(\"Anonymous access explicitly enabled, granting read-only access\")\n    return AuthenticationResult(\n        authenticated=True,\n        client_id=\"anonymous\",\n        scope=\"read\",\n        auth_method=\"none\"\n    )\n```\n\n**Note**: The basic `/health` endpoint (line 68) has **no auth dependency at all** and returns version and uptime information unconditionally.\n\n### Information Exposed\n\n| Field | Example Value | Reconnaissance Value |\n|-------|--------------|---------------------|\n| `platform` | `\"Linux\"` | OS fingerprinting |\n| `platform_version` | `\"#1 SMP PREEMPT_DYNAMIC...\"` | Kernel version \u2192 CVE targeting |\n| `python_version` | `\"3.12.1\"` | Python CVE targeting |\n| `cpu_count` | `8` | Resource enumeration |\n| `memory_total_gb` | `32.0` | Infrastructure profiling |\n| `database_path` | `\"/home/user/.mcp-memory/memories.db\"` | Username + file path disclosure |\n| `database_size_mb` | `45.2` | Data volume estimation |\n\n### Attack Scenario\n\n1. Attacker scans the local network for services on port 8000\n2. Finds mcp-memory-service with HTTP enabled and anonymous access\n3. Calls `GET /api/health/detailed`  (no credentials needed)\n4. Receives OS version, Python version, full database path (revealing username), system resources\n5. Uses this information to:\n   - Target known CVEs for the specific OS/Python version\n   - Identify the database file location for potential direct access\n   - Profile the system for further attacks\n \n### PoC\n\n```python\n# Show the system info that would be exposed\nimport platform, psutil\n\nsystem_info = {\n    \"platform\": platform.system(),\n    \"platform_version\": platform.version(),\n    \"python_version\": platform.python_version(),\n    \"cpu_count\": psutil.cpu_count(),\n    \"memory_total_gb\": round(psutil.virtual_memory().total / (1024**3), 2),\n}\nprint(system_info)  # All of this is returned to unauthenticated users\n```\n\n### Impact\n- **OS fingerprinting**: Exact OS and kernel version enables targeted exploit selection\n- **Path disclosure**: Database path reveals username, home directory structure, and file locations\n- **Resource enumeration**: CPU, memory, and disk info reveal infrastructure scale\n- **Reconnaissance enablement**: Combined information significantly reduces attacker effort for follow-up attacks\n\n## Remediation\n\n1. **Remove system details from default health endpoint** - return only `status`, `version`, `uptime`:\n\n```python\n@router.get(\"/health/detailed\")\nasync def detailed_health_check(\n    storage: MemoryStorage = Depends(get_storage),\n    user: AuthenticationResult = Depends(require_write_access)  # Require admin/write access\n):\n    # Only return storage stats, not system info\n    ...\n```\n\n2. **Do not expose `database_path`** - this leaks the filesystem structure:\n\n```python\n# Remove or redact\n# storage_info[\"database_path\"] = storage.db_path  # REMOVE THIS\n```\n\n3. **Add auth to basic `/health`** or limit it to status-only (no version):\n\n```python\n@router.get(\"/health\")\nasync def health_check():\n    return {\"status\": \"healthy\"}  # No version, no uptime\n```\nAlternatively, **Bind to `127.0.0.1` by default** instead of `0.0.0.0`, preventing network-based reconnaissance entirely:\n\n```python\n# In config.py \u2014 change default from \u00270.0.0.0\u0027 to \u0027127.0.0.1\u0027\nHTTP_HOST = os.getenv(\u0027MCP_HTTP_HOST\u0027, \u0027127.0.0.1\u0027)\n```\n\nUsers 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.",
  "id": "PYSEC-2026-2623",
  "modified": "2026-07-13T16:04:48.777953Z",
  "published": "2026-07-13T14:36:41.095636Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/doobidoo/mcp-memory-service/security/advisories/GHSA-73hc-m4hx-79pj"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-29787"
    },
    {
      "type": "WEB",
      "url": "https://github.com/doobidoo/mcp-memory-service/commit/18f4323ca92763196aa2922f691dfbeb6bd84e48"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/doobidoo/mcp-memory-service"
    },
    {
      "type": "PACKAGE",
      "url": "https://pypi.org/project/mcp-memory-service"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/advisories/GHSA-73hc-m4hx-79pj"
    }
  ],
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N",
      "type": "CVSS_V3"
    }
  ],
  "summary": "mcp-memory-service Vulnerable to System Information Disclosure via Health Endpoint"
}



Log in or create an account to share your comment.




Tags
Taxonomy of the tags.





Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.

Sightings

Author Source Type Date Other

Nomenclature

  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
  • Confirmed: The vulnerability has been validated from an analyst's perspective.
  • Published Proof of Concept: A public proof of concept is available for this vulnerability.
  • Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
  • Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
  • Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
  • Not confirmed: The user expressed doubt about the validity of the vulnerability.
  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.



Related by attack behaviour

Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.