Processing delays via inefficient PNG predictor decoding
Published Jun 22, 2026 · Updated Jun 22, 2026
Algorithmic complexity in pypdf before 6.12.2 allows attackers to cause long runtimes by processing a crafted PDF stream. The FlateDecode._decode_png_prediction routine repeatedly rebuilds immutable byte sequences while applying PNG predictor filters to attacker-controlled row data. Exposure requires a consuming application to decode the crafted stream; the resulting CPU cost can delay or interrupt that application's PDF-processing work.
Summary
What happened
Algorithmic complexity in pypdf before 6.12.2 allows attackers to cause long runtimes by processing a crafted PDF stream. The FlateDecode._decode_png_prediction routine repeatedly rebuilds immutable byte sequences while applying PNG predictor filters to attacker-controlled row data. Exposure requires a consuming application to decode the crafted stream; the resulting CPU cost can delay or interrupt that application's PDF-processing work.
The record
- CVE
- CVE-2026-49460
- Published
- Jun 22, 2026
- Updated
- Jun 22, 2026
- Vendor
- py-pdf
- Product
- pypdf
- Classifications
- CWE-407, T1499.004
- Attack vector
- local
- Privileges
- unauthenticated
Timeline
How it unfolded
- Jun 22, 2026CVE publishedPublication date reported by the CVE source.
- Jun 22, 2026Record updatedLatest update available in the CVE record.
Exploitability
Present is not the same as exploitable
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Is a vulnerable build present?
Compare these published version ranges with your installed build and any vendor patches.
- Affected versionversion=< 6.12.2
What conditions does exploitation require?
What is affected?
Published CVSS scores
CVSS describes severity. EPSS estimates exploitation probability.
Attacks
What attackers are doing with it
Daily unique IPs observed by Shadowserver honeypots for known exploited vulnerabilities (KEVs). Missing observations do not establish an absence of attacks.
Weakness, pattern, technique
Public exploit references
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Technologies
Your stack
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Your stack
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