CVE-2026-9270 (GCVE-0-2026-9270)
Vulnerability from cvelistv5 – Published: 2026-06-05 14:49 – Updated: 2026-06-08 18:17
VLAI
EPSS
VEX
Title
DataDog::DogStatsd versions through 0.07 for Perl allow metric injections
Summary
DataDog::DogStatsd versions through 0.07 for Perl allow metric injections.
DataDog::DogStatsd does not properly sanitise input, allowing metric injections of data from untrusted sources.
The send_stats method does not remove newlines from metric names ($stat variable), allowing attackers to change the metric name prefix.
The send_stats method does not validate the content of the value ($delta variable), allowing attackers to inject metrics, especially from methods that do not restrict the data type for the value, such as set, gauge, count and histogram.
The send_stats method does not validate the content of the tags, which may contain newlines, pipes and colons that allow metric injections.
Note that the SYNOPSIS shows an example of passing a website form "loginName" parameter as a tag, which is unsafe.
Severity
9.1 (Critical)
SSVC
Exploitation: none
Automatable: yes
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-06-08 18:17 UTC
CWE
Assigner
References
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| BINARY | DataDog::DogStatsd |
Affected:
0 , ≤ 0.07
(custom)
|
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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.
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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.
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