A SQL injection vulnerability in `FilterEngine.create_sqla_query()` allows any authenticated Rucio user to execute arbitrary SQL against the backend database through the DID search endpoint (`GET /dids/<scope>/dids/search`). On Oracle deployments attacker-controlled filter keys and values are interpolated directly into `sqlalchemy.text()` via Python `.format()`, completely bypassing parameterization. This enables full database compromise including extraction of authentication tokens, password hashes, and all managed data identifiers. This affects versions 1.27.0 and later before 35.8.5, 38.5.5, 39.4.2, and 40.1.1. The vulnerability exists in `lib/rucio/core/did_meta_plugins/filter_engine.py` within the `create_sqla_query()` method. When the database dialect is Oracle, filter expressions for JSON metadata columns are constructed using `text()` with Python string formatting. Both `key` and `value` are attacker-controlled strings derived from HTTP query parameters. The `text()` function creates a raw SQL fragment — it does **not** escape or parameterize its contents. Any authenticated Rucio user can exploit this through the DID search API to execute arbitrary SQL against the backend database. This can expose all managed data identifiers and sensitive tables such as identities, tokens, accounts, rse_settings, and rules, and may allow modification of database contents. The issue affects Oracle deployments using the default json_meta plugin and does not affect PostgreSQL or MySQL deployments using that plugin. This vulnerability has been fixed in versions 35.8.5, 38.5.5, 39.4.2, and 40.1.1.
This vulnerability carries a HIGH severity rating with a CVSS v3.1 score of 8.8, indicating it can be exploited remotely over the network with relatively low complexity without requiring user interaction requiring only low-level privileges . The vulnerability impacts confidentiality (data exposure), integrity (unauthorized modifications), and availability (service disruption) for affected systems. Impacting 1 product from cern organizations running these solutions should prioritize assessment and patching.
Reported in 2026, this vulnerability emerged during an era marked by increased sophistication in supply chain attacks, cloud infrastructure vulnerabilities, and software-as-a-service (SaaS) security challenges. Security practices during this period emphasized zero-trust architectures, container security, and API protection.
2026-05-06T17:16:22.457
2026-05-11T15:07:20.577
Analyzed
CVSSv3.1: 8.8 (HIGH)
| Type | Vendor | Product | Version/Range | Vulnerable? |
|---|---|---|---|---|
| Application | cern | rucio | < 35.8.5 | Yes |
| Application | cern | rucio | < 38.5.5 | Yes |
| Application | cern | rucio | < 39.4.2 | Yes |
| Application | cern | rucio | < 40.1.1 | Yes |
SecUtils normalizes and enriches National Vulnerability Database (NVD) records by standardizing vendor and product identifiers, aggregating vulnerability metadata from both NVD and MITRE sources, and providing structured context for security teams. For cern's affected products, we extract Common Platform Enumeration (CPE) data, Common Weakness Enumeration (CWE) classifications, CVSS severity metrics, and reference data to enable rapid vulnerability prioritization and asset correlation. This record contains no exploit code, proof-of-concept instructions, or attack methodologies—only defensive intelligence necessary for patch management, risk assessment, and security operations.