pypdf: Possible long runtimes/large memory usage for encrypted PDF files
- Published
- Last modified
- Where the record stands: published, rejected by its publisher, or superseded by another id.What do these mean? →
- published
- Whether CISA lists it in its Known Exploited Vulnerabilities catalog: proof that attackers are using it.What do these mean? →
- Not listed in CISA KEV
- Fix
- Fixed in 6.21.3
- Whether working attack code is public (Exploit-DB, Metasploit, Nuclei or GitHub). Public code makes attacks easier.What do these mean? →
- None on Exploit-DB, Metasploit or GitHub
Summary
pypdf, a pure-Python library for working with PDF files, is affected. A specially crafted encrypted PDF can cause an application that reads its page count to use excessive processing time and memory, potentially slowing or crashing the program.
Summarized by anthropic/claude-haiku-5.5. Verify details against the original sources.
Read the original description
pypdf is a free and open-source pure-python PDF library. Prior to 6.21.3, pypdf can consume excessive time and memory when an application accesses the page count of a crafted encrypted PDF whose page tree declares a forged /Count value. Even after successful decryption, page-count retrieval trusts the unvalidated declared count instead of walking the page tree, allowing the attacker-controlled value to drive excessive work and memory use. This issue is fixed in version 6.21.3.
Timeline
- CVE published
- First seen by cve.now
Affected versions
- py-pdf pypdf
fixed in 6.21.3