CVE-2024-24791VulnerabilityPublished 30 Sep 2024Updated 31 Oct 2026

Red Hat Security Advisory: Custom Metrics Autoscaler Operator for Red Hat 2.14.1-467 OpenShift Update

Affects Red HatSource GCVE Database

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Not known to be exploited · fixed in Red Hat package updates : update Red Hat when convenient.

Data as of 31 Oct 2026, 20:20 UTC

Severity

Medium

Rated by Threat Radar · No CVSS score from NVD or the CNA

EPSS: 1.4% chance of exploitation in 30 days – higher than 72% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
Patch: Available – fixed in 2.14.1

Exploitation evidence

Disclosed: evidence found.
CVE published 30 Sep 2024
Detectable: no evidence on record.
No public nuclei template indexed
Weaponized: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 31 Oct 2026.

Disclosed: The CVE record is public on cve.org. Its publication is t = 0.
Detectable: A public nuclei template can find exposed instances, for defenders and attackers alike.
Weaponized: A Metasploit exploit module or Exploit-DB entry exists (Metasploit scanner modules do not count), or CISA SSVC or the CVSS exploit maturity reports a public proof of concept.
Exploited in the wild: CISA KEV lists it, CISA SSVC rates exploitation active, or a source reports attacks.
Observed by OffSeq Mirage: OffSeq Mirage honeypot sensors recorded attack traffic for this CVE, or found exposed hosts without attack traffic.

Moments are spaced evenly, not to scale; a dashed line marks a gap of six months or more. Deltas count from t = 0. Sources that give only a date (CISA KEV, Exploit-DB, or a time of exactly 00:00Z) read “same day” rather than hours. Metasploit modules carry the flaw’s disclosure date, not their release date, and nuclei templates carry no date, so both appear above but not on the timeline.

What to do

AI-suggested

Red Hat has released an official security update (RHSA-2024:7348) that fixes CVE-2024-24791 in the Custom Metrics Autoscaler Operator for Red Hat OpenShift. Users should apply this update to version 2.14.1-467 after ensuring all previously released relevant errata are installed. Detailed update instructions are available from Red Hat's official documentation. No additional mitigation actions are indicated beyond applying the update.

Description

A security update for the Custom Metrics Autoscaler Operator for Red Hat OpenShift addresses CVE-2024-24791, a moderate severity vulnerability related to improper handling of HTTP 100-continue requests that could lead to denial of service. This operator extends Kubernetes Event Driven Autoscaler (KEDA) functionality by enabling scaling based on additional metrics sources. The update improves user experience and fixes the identified vulnerability.

Impact

The vulnerability CVE-2024-24791 could allow denial of service conditions due to improper handling of HTTP 100-continue requests within the Custom Metrics Autoscaler Operator. This could disrupt scaling operations and affect workload availability in Red Hat OpenShift environments using this operator. The severity is rated moderate, indicating a significant but not critical impact on system stability or security.

CWE-20Improper Input Validation (opens in a new tab)
Class weaknessLikelihood of exploit: HighCWE Top 25 (2025): #18OWASP Top 10 A05:2025: Injection (opens in a new tab)
The product receives input or data, but it does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly.
MITRE discourages mapping vulnerabilities to this broad entry; the root cause is usually a more specific weakness.
Architecture and Design · Attack Surface Reduction
Consider using language-theoretic security (LangSec) techniques that characterize inputs using a formal language and build "recognizers" for that language. This effectively requires parsing to be a distinct layer that effectively enforces a boundary between raw input and internal data representations, instead of…
Architecture and Design · Libraries or Frameworks
Use an input validation framework such as Struts or the OWASP ESAPI Validation API. Note that using a framework does not automatically address all input validation problems; be mindful of weaknesses that could arise from misusing the framework itself (CWE-1173).
Architecture and Design · Implementation · Attack Surface Reduction
Understand all the potential areas where untrusted inputs can enter the product, including but not limited to: parameters or arguments, cookies, anything read from the network, environment variables, reverse DNS lookups, query results, request headers, URL components, e-mail, files, filenames, databases, and any…
OWASP Cheat Sheets
XML Security (opens in a new tab)
Mass Assignment (opens in a new tab)
Injection Prevention (opens in a new tab)
SQL Injection Prevention (opens in a new tab)
Injection Prevention in Java (opens in a new tab)
OWASP ASVS 4.0.3
V13.3.1 (opens in a new tab)
V5.1.4 (opens in a new tab)
V5.1.3 (opens in a new tab)
Attack patterns
Buffer Overflow via Environment Variables (opens in a new tab)
Server Side Include (SSI) Injection (opens in a new tab)
Cross Zone Scripting (opens in a new tab)
Command Line Execution through SQL Injection (opens in a new tab)
Object Relational Mapping Injection (opens in a new tab)
From MITRE CWE, MITRE CAPEC and OWASP (Top 10, OpenCRE).

References

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Exploitation evidence

What to do

Description

AI analysisMachine-generated, updated 31 Oct 2026, 18:09 UTC

WeaknessesCWE-20

Technical details

References

Community reviews

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