Attack ChainAIDerived
Hypothetical attack flow derived from CVE metadata – not a confirmed exploit chain
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AccessCraft tiled JPEG2000 file
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DeliverySubmit to image-processing endpoint
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ExploitPillow accumulates tile widths
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ExecutionTrigger oversized memory allocation
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ImpactExhaust host memory (OOM crash)
Vulnerability Assessment
| Weakness |
CWE
ASVS 5.0
V15 - Secure Coding and Architecture Memory allocation limits
|
| Exploitation Conditions | The target application must accept and decode a JPEG2000 (.jp2/.j2k) image supplied by the attacker using an affected Pillow version (8.2.0-12.2.0), and the malicious file must be tiled so that per-tile widths accumulate - a single-tile image does not trigger the bug. No authentication, privileges, or user interaction are required (PR:N/UI:N) once such an input reaches the decoder. Exploitation is limited to deployments that actually process untrusted JPEG2000 input; services that only handle other formats, or that disable the JPEG2000 plugin, are not exposed. Impact is confined to availability (memory exhaustion / OOM) - no data disclosure or code execution. |
| Impact | This is a genuine but narrow-impact availability issue rather than a code-execution threat. The CVSS 4.0 vector (AV:N/AC:L/AT:N/PR:N/UI:N with VC:N/VI:N/VA:H) correctly reflects an unauthenticated, network-reachable, availability-only impact and no confidentiality or integrity effect - consistent with a memory-exhaustion DoS and NOT with the supplied 'Information Disclosure' tag, which appears mislabeled given VC:N. EPSS was not provided and the CVE is not in CISA KEV; with no public exploit identified, real-world exploitation is currently theoretical, though the public patch and diff lower the barrier to weaponization. Practical risk is highest for services that auto-decode user-supplied images (upload pipelines, thumbnailers, image proxies) and is effectively nil for deployments that never process untrusted JPEG2000 input. |
| Exploit ScenarioDerived | An attacker uploads a small, specially crafted tiled JPEG2000 file to a web service that automatically generates thumbnails or previews with Pillow. When Pillow decodes it, the accumulated tile-width miscalculation drives a massive transient allocation, exhausting memory and crashing the worker or host. No public exploit code has been identified, but the low attack complexity and unauthenticated network vector make abuse straightforward once a payload is constructed from the public patch. |
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Alert meAnalysisAIv1 – Jul 14, 2026
Denial of service in Python Pillow (versions 8.2.0 through 12.2.0) allows remote attackers to exhaust memory during JPEG2000 decoding, causing out-of-memory failures in any application that decodes untrusted images. The flaw stems from Pillow's JPEG2000 decoder summing tile widths across the whole image rather than per tile, so a small crafted tiled file forces disproportionately large transient allocations. There is no public exploit identified at time of analysis and it is not listed in CISA KEV, but the upstream fix (12.3.0) and a public PR/commit make the root cause fully transparent.
RemediationAI
Vendor-released patch: upgrade to Pillow 12.3.0 or later (https://github.com/python-pillow/Pillow/releases/tag/12.3.0); the fix is PR #9704 / commit 13ada41172142f2fd9f0906f615a00ea623a11ca. Where an immediate upgrade is not possible, restrict or disable JPEG2000 decoding by not registering/using the Jpeg2K plugin, or reject .jp2/.j2k uploads at the application boundary - this eliminates the attack surface at the cost of losing JPEG2000 support. As a compensating control, decode untrusted images in a resource-capped sandbox or worker process (cgroup/container memory limits, per-request timeouts) so an OOM kills only the isolated worker rather than the host service; the trade-off is added operational complexity and potential latency. Details are in advisory GHSA-vjc4-5qp5-m44j.
Affected VersionsENISA
Affected Packages
Source: OSV (Open Source Vulnerabilities)
Affects your stack
Affects 1 package in pypi
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Technical ContextAI · show details
The affected component is src/libImaging/Jpeg2KDecode.c, Pillow's C-level decoder built on OpenJPEG for the JPEG2000 (.jp2/.j2k) format, which supports tiling of an image into independently coded regions. The bug is a CWE-789 (Memory Allocation with Excessive Size Value) condition: the variable total_component_width was declared and accumulated once outside the per-tile loop, so each tile added its component width to a running total instead of the value being reset per tile. The fix in PR #9704 simply moves the int total_component_width = 0; declaration inside the per-tile processing block so it is recomputed for each tile, bounding the allocation. The affected CPE is cpe:2.3:a:python-pillow:pillow, i.e. the Pillow package itself, independent of OS or Python version.
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Severity by source
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N
Untrusted image reaches the decoder over the network with no auth or interaction (AV:N/AC:L/PR:N/UI:N); impact is pure memory-exhaustion DoS, so C:N/I:N/A:H.
AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Primary rating from Vendor (GitHub_M).
CVSS VectorVendor: GitHub_M
Lifecycle Timeline
2DescriptionCVE.org
Pillow is a Python imaging library. From 8.2.0 through 12.2.0, src/libImaging/Jpeg2KDecode.c accumulates total_component_width across every tile in a JPEG2000 image instead of recomputing it per tile, allowing a crafted tiled JPEG2000 file to force substantially higher transient memory usage and trigger out-of-memory failures during decoding. This issue is fixed in version 12.3.0.
Articles & Coverage 1
Executive ViewAI
Python Pillow, a widely-used image processing library, contains a memory exhaustion vulnerability in JPEG2000 decoding affecting versions 8.2.0 through 12.2.0. Any organization operating applications that process untrusted images-including web services, content platforms, and document processing systems-faces denial-of-service risk when attackers submit specially crafted images. Public disclosure of the root cause creates immediate remediation urgency despite current absence of active exploitation.
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Threat Intelligence Overview
How this decision was reached
The engine reads each signal below and applies a fixed list of rules from top to bottom. The first rule that matches sets the recommended action – like a statement, every line is shown.
What every action level means
SSVC AssessmentENISA
Priority Score
Attack Technique
Information disclosure occurs when an application unintentionally exposes sensitive data that aids attackers in reconnaissance or directly compromises security.
libImaging/TgaRleDecode.c in Pillow 9.1.0 has a heap buffer overflow in the processing of invalid TGA image files. Rated
Out-of-bounds memory disclosure in Python Pillow before 12.3.0 lets an attacker who supplies a crafted McIdas AREA image
Heap out-of-bounds write in Python Pillow prior to 12.3.0 lets an attacker who controls the rank-filter size parameter c
Denial-of-service and controlled heap corruption in Python's Pillow imaging library (all versions prior to 12.3.0) occur
Denial of service in Python Pillow 12.0.0 through 12.2.0 lets a remote attacker hang an application by supplying a craft
Denial of service (and potential memory corruption) in Python Pillow before 12.3.0 arises when public image coordinate A
Uncontrolled memory allocation in Python Pillow before 12.3.0 lets a crafted BDF font file exhaust available memory and
Uncontrolled memory consumption in Python Pillow (PIL) versions 5.1.0 through 12.2.x allows a remote attacker to cause d
Denial-of-service via memory exhaustion in Python Pillow before 12.3.0 allows a crafted GD-format (.gd) image to trigger
Uncontrolled memory allocation in Python Pillow before 12.3.0 allows a maliciously crafted font file to trigger excessiv
Uncontrolled memory allocation in the Python Pillow imaging library (all versions prior to 12.3.0) allows a crafted PCF
Out-of-bounds heap read in Python Pillow's TGA RLE encoder (versions 5.2.0 through 12.2.x) lets adjacent process heap by
Same technique Information Disclosure
View allVendor StatusVendor
SUSE
Severity: Moderate| Product | Status |
|---|---|
| SUSE Linux Enterprise Module for Package Hub 15 SP7 | Fixed |
| openSUSE Tumbleweed | Fixed |
| SUSE Linux Enterprise High Performance Computing 15 SP4-ESPOS | Affected |
| SUSE Linux Enterprise High Performance Computing 15 SP4-LTSS | Affected |
| SUSE Linux Enterprise High Performance Computing 15 SP5-ESPOS | Affected |
| SUSE Linux Enterprise High Performance Computing 15 SP5-LTSS | Affected |
| SUSE Linux Enterprise Module for Python 3 15 SP7 | Affected |
| SUSE Linux Enterprise Server 15 SP7 | Affected |
| SUSE Linux Enterprise Desktop 15 SP7 | Affected |
| SUSE Linux Enterprise Server for SAP Applications 15 SP7 | Affected |
| SUSE Linux Enterprise High Performance Computing 15 SP7 | Affected |
| SUSE Linux Enterprise Server 15 SP4-LTSS | Affected |
| SUSE Linux Enterprise Server 15 SP4-LTSS | Affected |
| SUSE Linux Enterprise Server 15 SP5-LTSS | Affected |
| SUSE Linux Enterprise Server 15 SP5-LTSS | Affected |
| SUSE Linux Enterprise Server 15 SP6-LTSS | Affected |
| SUSE Linux Enterprise Server 15 SP6-LTSS | Affected |
| SUSE Linux Enterprise Server for SAP Applications 15 SP4 | Affected |
| SUSE Linux Enterprise Server for SAP Applications 15 SP5 | Affected |
| SUSE Linux Enterprise Server for SAP Applications 15 SP6 | Affected |
| SUSE Linux Enterprise Desktop 15 SP7 | Affected |
| SUSE Linux Enterprise High Performance Computing 15 SP7 | Affected |
| SUSE Linux Enterprise Module for Package Hub 15 SP7 | Affected |
| SUSE Linux Enterprise Module for Python 3 15 SP7 | Affected |
| SUSE Linux Enterprise Server 15 SP7 | Affected |
| SUSE Linux Enterprise Server 16.0 | Affected |
| SUSE Linux Enterprise Server 16.1 | Affected |
| SUSE Linux Enterprise Server for SAP Applications 15 SP7 | Affected |
| SUSE Linux Enterprise Server for SAP applications 16.0 | Affected |
| SUSE Linux Enterprise Server for SAP applications 16.1 | Affected |
| SUSE Linux Enterprise High Performance Computing 15 SP4 | Affected |
| SUSE Linux Enterprise High Performance Computing 15 SP4-LTSS | Affected |
| SUSE Linux Enterprise High Performance Computing 15 SP5 | Affected |
| SUSE Linux Enterprise High Performance Computing 15 SP5-LTSS | Affected |
| SUSE Linux Enterprise Module for Python 3 15 SP4 | Affected |
| SUSE Linux Enterprise Module for Python 3 15 SP5 | Affected |
| SUSE Linux Enterprise Module for Python 3 15 SP6 | Affected |
| SUSE Linux Enterprise Server 15 SP4 | Affected |
| SUSE Linux Enterprise Server 15 SP4-LTSS | Affected |
| SUSE Linux Enterprise Server 15 SP5 | Affected |
| SUSE Linux Enterprise Server 15 SP5-LTSS | Affected |
| SUSE Linux Enterprise Server 15 SP6 | Affected |
| SUSE Linux Enterprise Server 15 SP6-LTSS | Affected |
| SUSE Linux Enterprise Server for SAP Applications 15 SP6 | Affected |
| SUSE Manager Proxy 4.3 | Affected |
| SUSE Manager Retail Branch Server 4.3 | Affected |
| SUSE Manager Server 4.3 | Affected |
| SUSE Linux Enterprise Desktop 15 SP4 | Affected |
| SUSE Linux Enterprise Desktop 15 SP5 | Affected |
| SUSE Linux Enterprise Desktop 15 SP6 | Affected |
| SUSE Linux Enterprise High Performance Computing 15 SP4-ESPOS | Affected |
| SUSE Linux Enterprise High Performance Computing 15 SP5-ESPOS | Affected |
| SUSE Linux Enterprise High Performance Computing 15 SP6 | Affected |
| SUSE Linux Enterprise Module for Package Hub 15 SP6 | Affected |
| SUSE Linux Enterprise Server for SAP Applications 15 SP4 | Affected |
| SUSE Linux Enterprise Server for SAP Applications 15 SP5 | Affected |
| openSUSE Leap 15.3 | Affected |
| openSUSE Leap 15.4 | Affected |
| openSUSE Leap 15.5 | Affected |
| openSUSE Leap 15.6 | Affected |
EUVD-2026-43730
GHSA-vjc4-5qp5-m44j
NVD
CVE.org
EPSS
VulDB
Exploit-DB