Full Report
Command Injection vulnerability (CVE-2025-1497) has been found in MLJAR PlotAI software.
Analysis Summary
# Vulnerability: Command Injection in MLJAR PlotAI via Unvalidated LLM Output
## CVE Details
- CVE ID: CVE-2025-1497
- CVSS Score: Not explicitly provided (Severity inferred as High due to arbitrary code execution)
- CWE: CWE-77 (Improper Neutralization of Special Elements used in a Command ('Command Injection'))
## Affected Systems
- Products: MLJAR PlotAI
- Versions: All through 0.0.6
- Configurations: N/A (Applies to the basic functionality relying on LLM output)
## Vulnerability Description
This is a Command Injection vulnerability arising from a lack of validation on output generated by a Large Language Model (LLM) within the PlotAI software. An attacker can leverage this flaw to execute arbitrary Python code on the system processing the malicious output, likely by injecting commands intended for system execution.
## Exploitation
- Status: PoC available (Implied by the nature of the report and the ability to demonstrate the flaw, though explicit public PoC mention is absent, the vendor response suggests high confidence in exploitability.)
- Complexity: Likely Low (If the payload can be passed through the LLM input/output path successfully)
- Attack Vector: Likely Network (If the input is sourced from an untrusted network source processed by the LLM)
## Impact
- Confidentiality: High (Arbitrary code execution can lead to information disclosure)
- Integrity: High (Arbitrary code execution allows data manipulation or system alteration)
- Availability: High (Arbitrary code execution can lead to denial of service or system compromise)
## Remediation
### Patches
- **Vendor Status:** The vendor **does not plan to release a patch** to fix this vulnerability.
- **Vendor Action:** The vendor has commented out the line of code causing the vulnerability. **Reverting this change requires accepting the risk.**
### Workarounds
- **Primary Mitigation:** Ensure the line of code that executes the unvalidated LLM output remains commented out within your installed version of PlotAI.
- **Assumption of Risk:** If functionality requiring LLM output execution is needed, the user must implement custom, robust input validation/sanitization logic before processing any LLM-generated output that could lead to code execution.
## Detection
- **Indicators of Compromise:** Look for unexpected system calls originating from the PlotAI application process, particularly Python process activity attempting to interact with the operating system shell or file system outside of expected application functions.
- **Detection Methods and Tools:** Static analysis of the application source code (version 0.0.6 or below) to identify the vulnerable line and confirm it remains commented out. Runtime monitoring tools tracking process execution could flag unauthorized code execution attempts.
## References
- Vendor advisories: Implicitly discussed in the CERT Polska report which served as coordinated disclosure.
- Relevant links - defanged:
- hXXps://www.cve.org/CVERecord?id=CVE-2025-1497
- hXXps://cert.pl/en/cvd/