CVE-2024-12886 (GCVE-0-2024-12886)

Vulnerability from cvelistv5 – Published: 2025-03-20 10:10 – Updated: 2025-10-15 12:49
VLAI
Title
Out-Of-Memory (OOM) Vulnerability in ollama/ollama
Summary
An Out-Of-Memory (OOM) vulnerability exists in the `ollama` server version 0.3.14. This vulnerability can be triggered when a malicious API server responds with a gzip bomb HTTP response, leading to the `ollama` server crashing. The vulnerability is present in the `makeRequestWithRetry` and `getAuthorizationToken` functions, which use `io.ReadAll` to read the response body. This can result in excessive memory usage and a Denial of Service (DoS) condition.
SSVC
Exploitation: poc Automatable: yes Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-03-20 17:51 UTC
CWE
  • CWE-409 - Improper Handling of Highly Compressed Data (Data Amplification)
Impacted products
Vendor Product Version CPE status
ollama ollama/ollama Affected: unspecified , ≤ latest (custom)
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

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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.
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  • 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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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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