CVE-2026-57170 (GCVE-0-2026-57170)
Vulnerability from cvelistv5 – Published: 2026-08-25 23:18 – Updated: 2026-08-28 22:41
VLAI
EPSS
VEX
Title
Trestle SSTI in Jinja2 include tags allows arbitrary code execution (Incomplete fix of CVE-2026-46439)
Summary
Compliance-trestle (Trestle) is a Python SDK and command-line tool for managing OSCAL compliance documents. In versions prior to 3.12.4 and 4.0.0 through 4.0.3, the custom Jinja2 include tags mdsection_include and md_clean_include re-parse the content of an included Markdown file as Jinja2 template code in a non-sandboxed environment, allowing server-side template injection that can lead to arbitrary code execution. The MDSectionInclude and MDCleanInclude tags in Trestle/core/jinja/tags.py pass included file content to Parser(self.environment, ...).parse(), splicing it into the host template's compilation, and the environment is a plain jinja2.Environment rather than a SandboxedEnvironment, so any expressions in the file are evaluated with full access to the usual SSTI gadget chain. Because Trestle's Markdown writers emit OSCAL prose and component-description fields verbatim, applying delimiter neutralization only to parameter tables, attacker-controlled OSCAL data such as a control statement, part prose, or component description containing Jinja2 syntax flows into an included Markdown file and is executed when the include tag re-parses it. This issue is fixed in version 4.1.0.
Severity
7.8 (High)
SSVC
Exploitation: none
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-08-28 22:41 UTC
CWE
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://github.com/oscal-compass/compliance-trest… | x_refsource_CONFIRM |
| https://github.com/oscal-compass/compliance-trest… | x_refsource_MISC |
| https://github.com/oscal-compass/compliance-trest… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| oscal-compass | compliance-trestle |
Affected:
< 3.12.4
Affected: >= 4.0.0, < 4.1.0 |
guessed |
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
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