CVE-2026-55099 (GCVE-0-2026-55099)
Vulnerability from cvelistv5 – Published: 2026-08-25 19:27 – Updated: 2026-08-26 15:05
VLAI
EPSS
VEX
Title
icalendar: Algorithmic Complexity in Equality
Summary
icalendar is an RFC 5545 compatible parser and generator of iCalendar files for Python. From 7.1.0 until 7.1.3, the Component equality method in src/icalendar/cal/component.py compares nested subcomponents with two membership loops, and each membership test invokes the same method on child components, causing O(2^n) work relative to nesting depth. Component.from_ical accepts arbitrarily nested BEGIN:VEVENT blocks without a depth limit, so an attacker can submit a sub-kilobyte .ics file containing equal nested subtrees and trigger the cost when an application performs equality, inequality, membership, deduplication, test-assertion, round-trip, or normalization comparisons. Parsing alone does not trigger the issue, and comparisons that differ early short-circuit, but a few hundred bytes can pin a CPU core for minutes or indefinitely, causing denial of service in calendar sync or import endpoints, invite processing, and other comparison paths. This issue is fixed in version 7.1.3.
Severity
7.5 (High)
SSVC
Exploitation: poc
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-08-26 15:05 UTC
Assigner
References
5 references
| URL | Tags |
|---|---|
| https://github.com/collective/icalendar/security/… | x_refsource_CONFIRM |
| https://github.com/collective/icalendar/commit/b6… | x_refsource_MISC |
| https://github.com/collective/icalendar/commit/ca… | x_refsource_MISC |
| https://github.com/collective/icalendar/releases/… | x_refsource_MISC |
| http://www.openwall.com/lists/oss-security/2026/06/23/8 |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| collective | icalendar |
Affected:
>= 7.1.0, < 7.1.3
|
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.
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.
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