GSD-2022-34917
Vulnerability from gsd - Updated: 2023-12-13 01:19Details
A security vulnerability has been identified in Apache Kafka. It affects all releases since 2.8.0. The vulnerability allows malicious unauthenticated clients to allocate large amounts of memory on brokers. This can lead to brokers hitting OutOfMemoryException and causing denial of service. Example scenarios: - Kafka cluster without authentication: Any clients able to establish a network connection to a broker can trigger the issue. - Kafka cluster with SASL authentication: Any clients able to establish a network connection to a broker, without the need for valid SASL credentials, can trigger the issue. - Kafka cluster with TLS authentication: Only clients able to successfully authenticate via TLS can trigger the issue. We advise the users to upgrade the Kafka installations to one of the 3.2.3, 3.1.2, 3.0.2, 2.8.2 versions.
Aliases
Aliases
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"alias": "CVE-2022-34917",
"description": "A security vulnerability has been identified in Apache Kafka. It affects all releases since 2.8.0. The vulnerability allows malicious unauthenticated clients to allocate large amounts of memory on brokers. This can lead to brokers hitting OutOfMemoryException and causing denial of service. Example scenarios: - Kafka cluster without authentication: Any clients able to establish a network connection to a broker can trigger the issue. - Kafka cluster with SASL authentication: Any clients able to establish a network connection to a broker, without the need for valid SASL credentials, can trigger the issue. - Kafka cluster with TLS authentication: Only clients able to successfully authenticate via TLS can trigger the issue. We advise the users to upgrade the Kafka installations to one of the 3.2.3, 3.1.2, 3.0.2, 2.8.2 versions.",
"id": "GSD-2022-34917",
"references": [
"https://access.redhat.com/errata/RHSA-2022:6819"
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"details": "A security vulnerability has been identified in Apache Kafka. It affects all releases since 2.8.0. The vulnerability allows malicious unauthenticated clients to allocate large amounts of memory on brokers. This can lead to brokers hitting OutOfMemoryException and causing denial of service. Example scenarios: - Kafka cluster without authentication: Any clients able to establish a network connection to a broker can trigger the issue. - Kafka cluster with SASL authentication: Any clients able to establish a network connection to a broker, without the need for valid SASL credentials, can trigger the issue. - Kafka cluster with TLS authentication: Only clients able to successfully authenticate via TLS can trigger the issue. We advise the users to upgrade the Kafka installations to one of the 3.2.3, 3.1.2, 3.0.2, 2.8.2 versions.",
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"pubdate": "2022-09-20",
"solution": "Upgrade to versions 2.8.2, 3.0.2, 3.1.2, 3.2.3 or above.",
"title": "Apache Kafka vulnerability can lead to brokers hitting OutOfMemoryException, causing Denial of Service",
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"title": "Allocation of Resources Without Limits or Throttling",
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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.
Vulnerability timeline
Sightings and recorded dates, grouped by day · UTC
How durations are calculated
Following the VTEM framework (Black Hat USA 2015), time to patch starts when the vendor or a coordinator was informed, total time to patch at discovery, and disclosure to patch at public disclosure; vendor response time runs from the report to its acknowledgement. Time to exploit and time unpatched start at the earliest discovery or report, falling back to public disclosure. Unpatched time ends at the first recorded patch, or the calculation time when no patch is recorded. Exploitation to patch shows the interval between those two events; a published proof of concept is a public exploit, not exploitation.
Each result shows its source dates. A negative interval means the end event came first; when date-only inputs leave the order open, the result says so. Date-only inputs are approximate. The earliest evidence wins: KEV report dates and sightings are labelled as such. Records describing another vulnerability are listed but never calculated from, and a PoC alone does not establish exploitation. Missing patch evidence does not prove that no patch exists. Filters below change the event list only.
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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.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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.
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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.