CVE-2026-29780
eml_parser serves as a python module for parsing eml files and returning various information found in the e-mail as well as computed information.
Published Mar 7, 2026 · corrected/updated Jun 17, 2026 · govcert.lu eml parser · evidence confidence medium
eml_parser serves as a python module for parsing eml files and returning various information found in the e-mail as well as computed information. Prior to version 2.0.1, the official example script examples/recursively_extract_attachments.py contains a path traversal vulnerability that allows arbitrary file write outside the intended output directory. Attachment filenames extracted from parsed emails are directly used to construct output file paths without any sanitization, allowing an attacker-controlled filename to escape the target directory. This issue has been patched in version 2.0.1.
Grounded briefings
Catalog interpretations for three audiences. Each brief cites ingested metadata and the original advisories below. They are not independent research and they do not invent exploit steps.
Executive
CVE-2026-29780 is a medium public vulnerability record for govcert.lu eml parser. It is not currently listed in the CISA Known Exploited catalog. Check the linked vendor or CERT advisories for patch status. This summary is a catalog interpretation of the ingested metadata and cites the original advisories below.
System administrator
Identify whether govcert.lu eml parser is in your estate, then compare installed versions with the affected ranges. Affected packages or ranges on record: govcert.lu/eml parser. Check the linked vendor or CERT advisories for patch status. Prefer the vendor or distribution advisory linked in Sources before changing production systems. This is a catalog interpretation, not a runbook.
Security analyst
Signals on file: CVSS 5.5. It is not currently listed in the CISA Known Exploited catalog. Weakness classes: CWE-22. Sources contributing to this record: cve_org, nvd. Public exploit references, when present, are outbound links only and are not proof of active exploitation. This is a catalog interpretation of stored metadata.
Exploitation and remediation
Exploitation evidence
Not listed as known exploited in CISA KEV. Not in CISA KEV or VulnCheck KEV.
Patch and remediation
No required-action text is stored yet. Use the vendor or CERT links in Sources for patch availability.
Safe detection guidance
Compare installed versions with the affected ranges below and verify the advisory from the original publisher. This site stores metadata and outbound links only; it does not ship exploit code or proof-of-concept payloads.
Code
The project this record applies to. Exploit listings stay in References.
Timeline
Detection, updates, and resolution for this record.
Mar 7, 2026 · NIST NVD
Detected
eml_parser serves as a python module for parsing eml files and returning various information found in the e-mail as well as computed information. Prior to version 2.0.1, the official example script examples/recursively_extract_attachments.py contains a path traversal vulnerability that allows arbitrary file write outside the intended output directory. Attachment filenames extracted from parsed ema
Jun 17, 2026 · NIST NVD
Updated
eml_parser serves as a python module for parsing eml files and returning various information found in the e-mail as well as computed information. Prior to version 2.0.1, the official example script examples/recursively_extract_attachments.py contains a path traversal vulnerability that allows arbitrary file write outside the intended output directory. Attachment filenames extracted from parsed ema
Affected
- cpe govcert.lu/eml parserversion unspecified
Sources
- CVE.orgVulnerability recordCVE-2026-29780
Official CVE identifier
cve.org - NIST NVDVulnerability recordCVE-2026-29780
eml_parser serves as a python module for parsing eml files and returning various information found in the e-mail as well as computed information. Prior to version 2.0.1, the official example script examples/recursively_extract_attachments.py contains a path traversal vulnerabilit
nvd.nist.gov