GHSA-g82g-j283-hj97 · Severity: critical · Ecosystem: pip — imgaug contains an insecure deserialization vulnerability in BackgroundAugmenter class within multicore.py module
The imgaug library thru 0.4.0 contains an insecure deserialization vulnerability in its BackgroundAugmenter class within the multicore.py module. The class uses Python's pickle module to deserialize data received via a multiprocessing queue in the _augment_images_worker() method without any safety checks. An attacker who can influence the data placed into this queue (e.g., through social engineering, malicious input scripts, or a compromised shared queue) can provide a malicious pickle payload. When deserialized, this payload can execute arbitrary code in the context of the worker process, leading to remote or local code execution depending on the deployment scenario.
Conclusion & alert: CVE-2026-31235 is rated Moderate Risk (52.5/100): CVSS Critical severity, with low exploitation likelihood (EPSS 0.47%). Mandatory action: Review affected assets and schedule remediation.
Risk is dynamic; we continuously reassess and refresh what is shown on this page as upstream context changes.
EPSS lead: Daily EPSS estimates relative likelihood of exploitation; percentile ranks this CVE among scored vulnerabilities (higher = more severe relative rank).
| # | Date | Old EPSS score | New EPSS score | Delta (New - Old) |
|---|---|---|---|---|
| 1 | 2026-06-15 | 0.07% | 0.47% | +0.40% |
| 2 | 2026-05-15 | 0.02% | 0.07% | +0.05% |
| 3 | 2026-05-13 | — | 0.02% | — |
Full EPSS history (3 records total)
CVSS metrics for this CVE.
| Base score | Version | Severity | Vector | Exploitability | Impact | Score source |
|---|---|---|---|---|---|---|
| 9.8 | 3.1 | CRITICAL |
|
3.9 | 5.9 | 134c704f-9b21-4f2e-91b3-4a467353bcc0 |
GHSA-g82g-j283-hj97 · Severity: critical · Ecosystem: pip — imgaug contains an insecure deserialization vulnerability in BackgroundAugmenter class within multicore.py module
| Vendor | Product | Version | Raw CPE |
|---|---|---|---|
| No affected products in dataset. | |||