CVE-2026-85715 (GCVE-0-2026-85715)
Vulnerability from cvelistv5 – Published: 2026-09-17 15:33 – Updated: 2026-09-17 15:54
VLAI
EPSS
VEX
Title
ExifReader: DoS via Crafted HEIC/AVIF iloc Box - Memory Exhaustion
Summary
ExifReader is a JavaScript Exif information parser. Prior to 4.41.1, ExifReader parses attacker-controlled HEIC or AVIF ISO-BMFF files in getItems() within src/image-header-iso-bmff-iloc.js and trusts iloc itemCount and extentCount values while allocating an extent object for every nested-loop iteration. When offsetSize, lengthSize, baseOffsetSize, and indexSize are zero, the extent fields consume no input bytes and the buffer offset does not advance, but the parser can still allocate up to itemCount multiplied by extentCount objects without an allocation budget. A small malicious iloc box can therefore cause hundreds of megabytes of heap growth or exhaust system memory, terminating a Node.js process and denying service to web, desktop, or mobile applications that parse untrusted images. The zero field widths are valid ISO-BMFF values indicating absent fields, so the vulnerable parser must bound work rather than relying on offset advancement. The issue is fixed in version 4.41.1.
Severity
7.5 (High)
SSVC
Exploitation: poc
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-17 15:54 UTC
CWE
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://github.com/mattiasw/ExifReader/security/a… | x_refsource_CONFIRM |
| https://github.com/mattiasw/ExifReader/commit/17b… | x_refsource_MISC |
| https://github.com/mattiasw/ExifReader/releases/t… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| mattiasw | ExifReader |
Affected:
< 4.41.1
|
guessed |
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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