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CVE-2017-16231 (GCVE-0-2017-16231)

Vulnerability from cvelistv5 – Published: 2019-03-17 16:24 – Updated: 2024-08-05 20:20 Disputed
VLAI
Summary
In PCRE 8.41, after compiling, a pcretest load test PoC produces a crash overflow in the function match() in pcre_exec.c because of a self-recursive call. NOTE: third parties dispute the relevance of this report, noting that there are options that can be used to limit the amount of stack that is used
SSVC
Exploitation: poc Automatable: no Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-06-26 19:41 UTC
CWE
  • n/a
  • CWE-119 - Improper Restriction of Operations within the Bounds of a Memory Buffer
Impacted products
Vendor Product Version CPE status
pcre pcre Affected: 8.41
    cpe:2.3:a:pcre:pcre:8.41:*:*:*:*:*:*:*
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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Detection rules are retrieved from Rulezet.

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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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