CVE-2023-35936
Pandoc 1.13 – 3.1.4
Raw vector
CVSS:3.1/AV:L/AC:H/PR:L/UI:R/S:C/C:N/I:H/A:LCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2023-35936 is a medium-severity Improper Input Validation (CWE-20) vulnerability in Pandoc Pandoc. Its CVSS base score is 6.1 (Medium).
Operationally, ranked at the 29th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-39920
Vulnerability Data
Pandoc is a Haskell library for converting from one markup format to another, and a command-line tool that uses this library. Starting in version 1.13 and prior to version 3.1.4, Pandoc is susceptible to an arbitrary file write vulnerability, which…
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can be triggered by providing a specially crafted image element in the input when generating files using the `--extract-media` option or outputting to PDF format. This vulnerability allows an attacker to create or overwrite arbitrary files on the system ,depending on the privileges of the process running pandoc. It only affects systems that pass untrusted user input to pandoc and allow pandoc to be used to produce a PDF or with the `--extract-media` option. The fix is to unescape the percent-encoding prior to checking that the resource is not above the working directory, and prior to extracting the extension. Some code for checking that the path is below the working directory was flawed in a similar way and has also been fixed. Note that the `--sandbox` option, which only affects IO done by readers and writers themselves, does not block this vulnerability. The vulnerability is patched in pandoc 3.1.4. As a workaround, audit the pandoc command and disallow PDF output and the `--extract-media` option.
- CWE(s)
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Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Security testing and developer training directly verify and enforce proper input validation, reducing exploitability of injection and malformed-data weaknesses.
Security testing and evaluation at multiple SDLC stages directly detects missing or flawed input validation, with the required remediation process ensuring fixes are applied.
Directly implements checks on information inputs to reject invalid data before processing.
Spam protection mechanisms perform filtering and detection on inbound/outbound messages, directly compensating for missing or weak input validation of unsolicited content.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
A.8.25 mandates security requirements, secure coding guidelines, checkpoints, testing (incl. code scans) and developer training in the SDLC, which reaches a slice of input validation defects but leaves the majority (incomplete enforcement, second-order inputs, parser differentials, post-validation canonicalization) unaddressed as in the SA-3 and A.8.28 anchors.
Mandating input controls that include integrity checks and input validation ensures that untrusted data is examined before use, blocking the root cause of many injection and malformed-data weaknesses.
Security-by-design principles explicitly call for data validation and sanitization at every layer, reducing the chance that malformed or malicious input will be processed without scrutiny.
Requiring language-specific secure coding standards, peer review, SAST and documented mitigation of common programming errors forces validation of all inputs before they are trusted.
Testing against a defined set of requirements and using code review plus vulnerability scanning forces validation of inputs and handling of unanticipated conditions, reducing the chance that malformed data will be accepted.
Hardening callouts derived
DISA STIG baselines are authored against specific weaknesses. Where this CVE cites a broad weakness class, the mapping is not asserted at that abstraction (owner ruling, 2026-09-25: grade only at Base and below), so no rule is shown here rather than a rule shown against the wrong grain.
- No fine-grained STIG row for CWE-20, a class-level weakness, and none of its children carries one either.