CVE-2026-9270
Binary Datadog\ \
Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:NSummary
CVE-2026-9270 is a critical-severity CRLF Injection (CWE-93) vulnerability in Binary Datadog\. Its CVSS base score is 9.1 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Content Injection (T1659); ranked at the 26th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to SI-10 (Information Input Validation) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-34846
Vulnerability Data
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 ($stat variable), allowing attackers to change the…
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metric name prefix. The send_stats method does not validate the content of the value ($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.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.2.10V1.3.12V4.2.4
Mitigating Controls (NIST 800-53 r5) AI
Input validation directly stops untrusted data containing CRLF sequences from reaching the component that treats CRLF as a delimiter.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Secure SDLC practices directly require input neutralization and validation to block CRLF injection.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Security testing can detect CRLF flaws but does not itself implement the neutralization.
Secure development lifecycle mandates input validation and output encoding that directly prevents CRLF injection.
Application security requirements include rules for neutralizing special characters such as CRLF in inputs.
Secure architecture principles encourage safe handling of untrusted data but do not prescribe specific CRLF controls.
Secure coding standards explicitly require neutralization of CRLF sequences, fully addressing this weakness.