CVE-2025-62708: py-pdf pypdf · Data Amplification
Affects py-pdf pypdfSource CVE Database V5
Not known to be exploited · CVSS 6.6 Medium : upgrade to 6.1.3 when convenient.
Data as of 26 Oct 2026, 12:55 UTC
- EPSS
- 0.4% chance of exploitation in 30 days – higher than 38% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
- Patch
- Available – fixed in 6.1.3
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N/E:UExploitation evidence
Disclosed: evidence found.
CVE published 22 Oct 2025
Detectable: no evidence on record.
No public nuclei template indexed
Weaponised: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors
A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 26 Oct 2026.
What to do
Upgrade py-pdf pypdf to 6.1.3.
Affected software
| Product | Affected | Fixed in |
|---|---|---|
PyPIpypdfpkg:pypi/pypdfOther threats | Affected
| Fixed in
|
Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.
AI-suggested
The most effective mitigation is to upgrade all instances of pypdf to version 6.1.3 or later, where the vulnerability is fixed. Organizations should audit their software dependencies to identify any use of vulnerable pypdf versions, including indirect dependencies in third-party applications. Implement strict input validation and sandboxing for PDF processing components to limit resource consumption and isolate failures. Employ resource usage monitoring and limits (e.g., memory and CPU quotas) on PDF parsing processes to prevent system-wide impact from malicious files. Where possible, restrict PDF uploads or processing to trusted sources or apply pre-processing filters to detect anomalous compression patterns. Maintain updated threat intelligence feeds to monitor for any emerging exploits targeting this vulnerability. Finally, integrate vulnerability scanning into the software development lifecycle to catch outdated library versions proactively.
Description
### Impact An attacker who uses this vulnerability can craft a PDF which leads to large memory usage. This requires parsing the content stream of a page using the LZWDecode filter. ### Patches This has been fixed in [pypdf==6.1.3](https://github.com/py-pdf/pypdf/releases/tag/6.1.3). ### Workarounds If you cannot upgrade yet, consider applying the changes from PR [#3502](https://github.com/py-pdf/pypdf/pull/3502).