CVE-2026-102997
7.5 HIGHpublic exploit availablePublished 2026-09-30 · Updated 2026-10-05
AI risk analysis
- Summary
- A crafted PDF file can trigger inefficient byte-by-byte decompression in pypdf, leading to excessive CPU usage and application unavailability. This vulnerability allows attackers to perform a denial-of-service attack by submitting malicious PDF files.
- Exploitability
- Exploitation is relatively straightforward as it requires only uploading or processing a specially crafted PDF file with malformed FlateDecode streams, with no additional authentication or complex preconditions needed.
- Blast radius
- The impact could be significant in environments where pypdf is used to process untrusted PDF files, potentially causing widespread service disruption across applications that rely on this library for PDF handling.
- Detection
- No reliable host or network indicator is derivable from the published description.
- Prioritized remediation
- Upgrade to pypdf version 6.18.1 or later to remediate this denial-of-service vulnerability.
Analysis generated locally by garnet-coder (no data left the box). AI-assisted — verify against primary sources before acting.
NVD description
pypdf is a free and open-source pure-python PDF library. Prior to 6.18.1, a crafted PDF containing a partially malformed /FlateDecode stream with padded data can force pypdf/filters.py to use inefficient byte-by-byte decompression while the earlier recovery counter fails to advance for bytes that successfully decode, causing long runtimes and application unavailability. This is a residual issue after the malformed FlateDecode recovery fix. This issue is fixed in version 6.18.1.
CVSS vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Weaknesses
CWE-400, CWE-407
Vendors
pypdf project
Products
pypdf
Public exploit & PoC references
- https://github.com/py-pdf/pypdf/commit/d9d38cf99b115deb562d3b68f36c33027bc04f79[Patch]
- https://github.com/py-pdf/pypdf/pull/4073[Patch, Issue Tracking]
- https://github.com/py-pdf/pypdf/releases/tag/6.18.1[Release Notes]
- https://github.com/py-pdf/pypdf/security/advisories/GHSA-jw7q-gvrg-4vj3[Vendor Advisory]
All references
Source data: NVD (nvd.nist.gov), public domain. Exploit-DB.ai adds local AI analysis for defensive use only.
Related CVEs
- HIGHCVE-2026-102999PoC
- HIGHCVE-2026-102998PoC
- HIGHCVE-2026-102994PoC
- HIGHCVE-2026-102995PoC
- HIGHCVE-2026-102996PoC
- HIGHCVE-2026-103000PoC
- HIGHCVE-2026-104020PoC
- HIGHCVE-2026-107286PoC
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