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Medium github · GHSA-24rc-8hj2-v98c

Pillow: BMP RLE decoder memory-amplification DoS via unbounded delta escape / absolute mode

Published Oct 22, 2026 CVSS 6.5

Summary

BmpRleDecoder can be forced to allocate gigabytes of memory from a kilobyte-sized crafted BMP file via unbounded growth in the delta escape and absolute mode branches.

Affected versions

All versions up to and including current HEAD (v13.0.0.dev0, commit e7a7ea84)

Root cause

BmpRleDecoder.decode() (BmpImagePlugin.py:327-395) builds a Python bytearray data with dest_length = xsize*ysize, looping while len(data) < dest_length. The loop condition is only checked at the TOP; individual branches append attacker-controlled amounts UNBOUNDED by dest_length:

  • delta escape (line 370): data += b"\x00" * (right + up * self.state.xsize) with right,up in 0..255 -> up to ~255*xsize bytes in ONE iteration.
  • absolute mode (line 385): data += bytes_read (up to 255).

Because a single delta can push len(data) to ~256 * (row size), a tiny RLE stream combined with a large-but-legal xsize (xsize*ysize just under MAX_IMAGE_PIXELS, ~89M) yields a multi-GB data bytearray (then copied again by bytes(data) and set_as_raw). No heap OOB (bytearray/set_as_raw are bounds-safe), but a severe memory-amplification DoS: the attacker file stays tiny.

Reproduction

Python 3.13, Pillow HEAD e7a7ea84

Attached: pillow_poc_bmp_rle_dos.py

A 1084-byte BMP (BI_RLE8, width=3,000,000, height=1 -> 3M px, passes bomb check) with one delta escape (00 02 00 150) produces ~429 MB data; measured peak RSS 911 MB. Scaling width toward the bomb limit and up=255 produces tens of GB from a ~1 KB file.

Suggested fix

Cap growth at dest_length in the delta and absolute branches, e.g. clamp the delta fill to (dest_length - len(data)) and stop appending once len(data) >= dest_length; reject deltas that would move the cursor beyond the image, matching the existing per-row clamp at line 341-343.

Credit: Yazan Balawneh - CyStack Security Team (GitHub: sonicnew)

pillow_poc_bmp_rle_dos.py

Affected AI Products

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