Server-Side Template Injection in Open Notebook Transformations

Lack of user input sanitisation in Open Notebook v1.8.3 allows the application user to execute Python code (and subsequently OS commands) on the docker container via Server-Side Template Injection (SSTI) for user-created transformations.

Casky was already ahead

This CVE exploits attack patterns that Casky's 301matched skills already investigate — long before this vulnerability was disclosed. Claude's reasoning model maps these techniques to MITRE ATT&CK, so practitioners who ran these skills have already seen the threat behaviour in their findings.

Analysis

Open Notebook v1.8.3 contains a critical server-side template injection (SSTI) vulnerability in its user-created transformations feature, stemming from inadequate input sanitization (CWE-20). This flaw allows authenticated users to inject arbitrary Python code that executes within the Docker container environment, potentially escalating to OS command execution. Organizations deploying Open Notebook for collaborative data analysis and transformation workflows face immediate risk of container compromise, lateral movement, and data exfiltration. The vulnerability affects any deployment where untrusted users can create or modify transformations, making it particularly dangerous in multi-tenant or shared analytical environments.

Casky's 301 matching skills leverage Claude AI's extended reasoning to detect the attack patterns underlying this vulnerability by mapping to MITRE ATT&CK techniques TA0001 (Initial Access) and TA0043 (Reconnaissance). Practitioners using Casky would identify reconnaissance indicators such as template syntax probing in transformation inputs, followed by execution technique signatures—unusual Python imports (os, subprocess), template delimiters in user inputs, and Docker process spawning from application contexts. The platform's skill-based detection would flag transformation payloads containing Jinja2/Mako template metacharacters combined with Python function calls, container escape patterns, and suspicious environment variable access. Security teams would see findings correlating unsanitized user input flowing directly into template rendering engines, enabling them to prioritize input validation remediation and implement strict transformation sandboxing before exploitation occurs.

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Casky Risk Score

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EPSS Probability

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Shodan Exposure

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GreyNoise Signal

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Composite risk scoring from EPSS, CISA KEV, Shodan, and GreyNoise — 21 security APIs correlated into a single Casky Risk Score. Coming in Casky Pro. Join early access →

301 Casky skills cover this attack pattern

These skills use Claude AI's reasoning model to surface findings in the same attack categories as CVE-2026-33587.

analyzing-apt-group-with-mitre-navigator

threat intelligence · low

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threat intelligence · low

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analyzing-certificate-transparency-for-phishing

threat intelligence · low

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MITRE ATT&CK Techniques

TA0001 TA0043

Investigate the attack patterns behind CVE-2026-33587

Casky has 301 skills that investigate the attack patterns behind CVE-2026-33587. Run one and get CVSS-scored findings in 3 minutes.

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