https://db.gcve.eu Contains only the most 10 recent entries. http://www.rssboard.org/rss-specification python-feedgen en Thu, 29 Oct 2026 14:30:26 +0000 https://db.gcve.eu/vuln/brew-aider-cve-2026-112894 <p><strong>Affected:</strong> Homebrew: aider</p> <p>``` ============================================================================ Quadratic-time DoS in PDF save_all (PdfParser.next_object_id) Location: src/PIL/PdfParser.py:629 in next_object_id() Commit: a707c6b21c313880d0771e54965d142dd42358b6 ============================================================================ ```</p> <p>Pillow&#39;s PDF writer takes time proportional to the square of the number of frames when it saves a multi-frame image as a multi-page PDF. Anyone who can get an application to convert their uploaded image this way can tie up a worker at full CPU for minutes with a small file. A 240 KB animated image takes about 70 seconds, a 720 KB one an estimated 10 minutes, and a 125-byte animated PNG that merely *declares* a large frame count triggers the same slowdown with no upper bound short of 2³¹ frames. Memory stays under 100 MB and the decompression-bomb limit never applies.</p> <p>The cause is `PdfParser.next_object_id()` in `src/PIL/PdfParser.py`, which finds the next free id by computing `max(self.xref_table.keys())`. `XrefTable.keys()` rebuilds three sets over every id reserved so far on each call. `PdfImagePlugin._save()` calls it three times (four for palette images with transparency) per frame, for `n_frames` frames, before any page is written. That makes the id-reservation loop alone O(N²). Because `n_frames` is taken from the file before any frame is seeked, APNG&#39;s `acTL` count drives the loop even when the frames don&#39;t exist. In that case the save raise…</p> <p><strong>Affected:</strong> Homebrew: aider</p> <p>``` ============================================================================ Quadratic-time DoS in PDF save_all (PdfParser.next_object_id) Location: src/PIL/PdfParser.py:629 in next_object_id() Commit: a707c6b21c313880d0771e54965d142dd42358b6 ============================================================================ ```</p> <p>Pillow&#39;s PDF writer takes time proportional to the square of the number of frames when it saves a multi-frame image as a multi-page PDF. Anyone who can get an application to convert their uploaded image this way can tie up a worker at full CPU for minutes with a small file. A 240 KB animated image takes about 70 seconds, a 720 KB one an estimated 10 minutes, and a 125-byte animated PNG that merely *declares* a large frame count triggers the same slowdown with no upper bound short of 2³¹ frames. Memory stays under 100 MB and the decompression-bomb limit never applies.</p> <p>The cause is `PdfParser.next_object_id()` in `src/PIL/PdfParser.py`, which finds the next free id by computing `max(self.xref_table.keys())`. `XrefTable.keys()` rebuilds three sets over every id reserved so far on each call. `PdfImagePlugin._save()` calls it three times (four for palette images with transparency) per frame, for `n_frames` frames, before any page is written. That makes the id-reservation loop alone O(N²). Because `n_frames` is taken from the file before any frame is seeked, APNG&#39;s `acTL` count drives the loop even when the frames don&#39;t exist. In that case the save raise…</p> https://db.gcve.eu/vuln/brew-aider-cve-2026-112894 https://db.gcve.eu/vuln/cve-2026-112894 <p><strong>Affected:</strong> python-pillow Pillow</p> <p>Pillow is a Python imaging library. From 5.1.0 until 13.0.0, Pillow takes quadratic time to reserve PDF object identifiers when saving many frames with save_all enabled. PdfParser.next_object_id() repeatedly rebuilds and scans all previously reserved identifiers for every object. An attacker can supply a multi-frame image, including a small APNG with a large declared frame count, to an application that converts it to a multipage PDF. This can consume excessive CPU and deny service. This issue is fixed in version 13.0.0.</p> <p><strong>Affected:</strong> python-pillow Pillow</p> <p>Pillow is a Python imaging library. From 5.1.0 until 13.0.0, Pillow takes quadratic time to reserve PDF object identifiers when saving many frames with save_all enabled. PdfParser.next_object_id() repeatedly rebuilds and scans all previously reserved identifiers for every object. An attacker can supply a multi-frame image, including a small APNG with a large declared frame count, to an application that converts it to a multipage PDF. This can consume excessive CPU and deny service. This issue is fixed in version 13.0.0.</p> https://db.gcve.eu/vuln/cve-2026-112894