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CVE-2026-24343 (GCVE-0-2026-24343)

Vulnerability from cvelistv5 – Published: 2026-02-10 09:28 – Updated: 2026-02-10 15:37
VLAI
Title
Apache HertzBeat: Uncontrolled Resource Consumption via Crafted XPath Expressions
Summary
Improper Neutralization of Data within XPath Expressions ('XPath Injection') vulnerability in Apache HertzBeat. This issue affects Apache HertzBeat: from 1.7.1 before 1.8.0. Users are recommended to upgrade to version 1.8.0, which fixes the issue.
SSVC
Exploitation: none Automatable: no Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-02-10 15:36 UTC
CWE
  • CWE-643 - Improper Neutralization of Data within XPath Expressions ('XPath Injection')
Impacted products
Vendor Product Version CPE status
Apache Software Foundation Apache HertzBeat Affected: 1.7.1 , < 1.8.0 (semver)
guessed Create a notification for this product.
Show details on NVD website

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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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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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