Security readout for executives and security teams
Plain-English summary
A malicious GraphQL schema can turn generated model code into a delivery path for attacker-controlled Python. The injected code executes only when someone generates models from the crafted schema and later imports them, but successful exploitation could compromise confidentiality, integrity, and availability.
Executive priority
Prioritize remediation for build systems accepting partner, customer, repository, or internet-sourced GraphQL schemas. Upgrade promptly and examine previously generated artifacts. Lower urgency is reasonable only after confirming affected versions are absent or schema inputs are fully trusted.
Technical view
Versions 0.25.0 through 0.60.0 fail to neutralize carriage returns in GraphQL Union descriptions rendered into Python comments. A carriage return can escape the intended comment context and inject Python into generated models. Importing the generated module executes that code. Version 0.60.1 fixes both affected UnionTypeStatement templates.
Likely exposure
Exposure is most likely in development, CI/CD, or automation workflows using affected versions to process GraphQL schemas from untrusted or externally influenced sources. Systems that neither generate from GraphQL schemas nor import resulting models are unlikely to reach the vulnerable execution path.
Exploitation context
Exploitation requires attacker-controlled GraphQL Union description content, model generation, and subsequent import of the generated Python. User or workflow interaction is therefore required. The supplied record is not in KEV, and the provided sources do not establish active exploitation.
Researcher notes
The affected range is 0.25.0 through 0.60.0. The weakness is template-context code injection involving carriage returns inside Python comment output, mapped to CWE-1336 and CWE-94. Evidence supports arbitrary Python execution upon import, but the bundle provides no evidence of exploitation in the wild.
Mitigation direction
- Upgrade datamodel-code-generator to version 0.60.1 or later.
- Restrict schema inputs to trusted, authenticated sources until upgrading.
- Regenerate affected models with the fixed version before importing or deploying them.
- Review previously generated Python before continued use where schema provenance is uncertain.
Validation and detection
- Inventory installed and CI-pinned datamodel-code-generator versions.
- Identify workflows that generate Python models from GraphQL schemas.
- Verify whether external parties can influence GraphQL Union descriptions.
- Confirm regenerated models use version 0.60.1 or later.
- Review historical generated files and build artifacts from untrusted schemas.
Public sources used
Generated from the cited source records. This long-tail analysis has not been individually reviewed by a named human.
Conservative CVE-to-ATT&CK context
These mappings and lookup hints may be relevant to the vulnerability behavior, CWE, affected product, or exposure path. Glexia-inferred context is not an official MITRE, ATT&CK, CWE, or CVE Program mapping.
ATT&CK lookup starting points
Use these exact CWE pages and searches to review the Glexia ATT&CK library from this CVE's weakness and description context.
CWE-1336: Exact CWE lookup
Use the exact CWE identifier as the starting point before reviewing related ATT&CK behavior. Open the exact CWE lookup page first, then review the ATT&CK searches from that MITRE weakness context. This is a Glexia lookup hint, not an official ATT&CK mapping.
Open ATT&CK lookupCWE-94: Code execution behavior lookup
Code execution and unsafe deserialization weaknesses often justify reviewing execution behavior and process telemetry. Open the exact CWE lookup page first, then review the ATT&CK searches from that MITRE weakness context. This is a Glexia lookup hint, not an official ATT&CK mapping.
Open ATT&CK lookupCVE-2026-54621 mapping review
Open the CVE-to-ATT&CK bridge for reviewed, inferred, or future official mappings tied to this CVE.
Open ATT&CK lookup- Severity
- High
- CVSS
- 7.8 (3.1)
- Known Exploited
- No
- Published
Vector: CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
CNA and ADP enrichment extracted from CVE v5
These fields come from the CVE record and ADP containers, not from Glexia's Take. They preserve time-varying source decisions such as CISA SSVC, KEV status, CVSS metrics, and provider references.
SSVC decision data
CVSS vector scores
1 official scoreWe collect every scored CVSS vector available in the official CNA and ADP containers. When more than one version is present, the table keeps the source vectors side by side instead of collapsing them into the highest score.
CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H1.85.9GitHub_MVulnerability scoring details
Base CVSS 3.1 score
7.8HighVector: CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
Vulnerability timeline
Timeline events are normalized from CVE metadata, CNA source timelines, ADP timelines, and KEV metadata when present.
- CVE reservedCVE Program
The CVE ID was reserved by the assigning CNA.
- CVE publishedCVE Program
The CVE record was published.
- CVE updatedCVE Program
The CVE record metadata indicates this as the latest update time.
ADP provider summaries
Source materials
- CVE List V5 sourceCVE List V5
- https://github.com/koxudaxi/datamodel-code-generator/security/advisories/GHSA-j884-q54q-mmx3CVE reference, GitHub_M · x_refsource_CONFIRM
- https://github.com/koxudaxi/datamodel-code-generator/commit/aec47bc414779f4a9992b3919c8f7663afd6c988CVE reference, GitHub_M · x_refsource_MISC
- https://github.com/koxudaxi/datamodel-code-generator/releases/tag/0.60.1CVE reference, GitHub_M · x_refsource_MISC
Products and packages named in the record
CWE details
CWE links open Glexia weakness intelligence pages with official CWE context, developer remediation guidance, and related CVE mappings.
Improper Neutralization of Special Elements Used in a Template Engine
Improper Neutralization of Special Elements Used in a Template Engine represents a recurring weakness pattern that can create exploitable paths when design, validation, or implementation controls are missing.
Improper Control of Generation of Code ('Code Injection')
Improper Control of Generation of Code ('Code Injection') represents a recurring weakness pattern that can create exploitable paths when design, validation, or implementation controls are missing.