VAR-201408-0153
Vulnerability from variot - Updated: 2025-04-13 23:29The EnergyWise module in Cisco IOS 12.2, 15.0, 15.1, 15.2, and 15.4 and IOS XE 3.2.xXO, 3.3.xSG, 3.4.xSG, and 3.5.xE before 3.5.3E allows remote attackers to cause a denial of service (device reload) via a crafted IPv4 packet, aka Bug ID CSCup52101. Cisco IOS is the interconnected network operating system used on most Cisco system routers and network switches. This issue is being tracked by Cisco Bug ID CSCup52101. https://tools.cisco.com/bugsearch/bug/CSCup52101
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Drag nodes to arrange them. Double-click a related vulnerability to open it, or a source to visit its link. The Physics button on the left tunes the layout and the simulation; the legend at the bottom left hides or shows nodes by kind and by sighting type.
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.
Vulnerability timeline
Sightings and recorded dates, grouped by day · UTC
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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.
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.