HighCVE-2026-116588

    Datadog dd-trace-py: ReDOS in URL query string obfuscation (CVE-2026-116588)

    Published Last modified Sources: CVE.org, OSV, Hersteller

    What is affected, what to do

    Datadog dd-trace-py is the Datadog Python APM client. From 1.5.0 until 3.19.9 and 4.15.6, the default query-string obfuscation regular expression can exhibit excessive backtracking while synchronously processing attacker-controlled URL query strings for HTTP span metadata.

    Update ddtrace to version 3.19.9.

    Affected
    • Datadog Dd-trace-py gte 1.5.0, < 3.19.9..*

    Not sure whether and how you are affected? Ask a question about this vulnerability

    Metrics

    8.7

    Priority

    XIEM Effective CVSS: highest available CVSS rating from NVD and vendor data.

    Source: Vendor (CNA), CVSS v4

    8.7

    CVSS v4

    Severity High on the scale from 0 to 10.

    Source: CVE.org, OSV, Hersteller

    0.5 %

    EPSS score

    Low — model estimates < 1% exploitation likelihood.

    Source: FIRST EPSS, percentile 40.5

    Show all metrics
    Severity
    High
    Priority (0–325)

    The priority score is a consolidated metric that condenses several individual signals into a single, action-guiding ranking: technical severity (CVSS), exploitation likelihood (EPSS), known-exploited status (KEV) and the context of the affected asset. The aim is to answer the only truly important question in vulnerability management: what first?

    Read in glossary
    86.63 Methodology
    Exploit maturity

    An exploit is code or a technique that specifically uses a concrete vulnerability to force unintended behaviour — such as executing code or escalating privileges. It is the tool that turns a theoretical flaw into a practical attack.

    Read in glossary
    no public PoC known
    XIEM Effective CVSS

    XIEM® is the tiered managed-security operating model from NEOSEC and a registered trademark of NEOSEC GmbH. It extends classic SIEM — the central collection, normalisation and correlation of security-relevant events — with endpoint forensics, network visibility and deception technology, and consolidates them into three building tiers: Sentry, Orchestrate and Command.

    Read in glossary
    8.7 Methodology
    CVSS v4

    CVSS is the globally established, open standard for assessing the technical severity of a vulnerability on a scale from 0 to 10. It describes how easily a flaw can be exploited and what damage it can cause — but not how likely its actual exploitation is. CVSS and the complementary EPSS deliberately answer different questions.

    Read in glossary
    8.7
    EPSS score

    The EPSS score is the absolute model output for an individual vulnerability: the estimated probability of real-world exploitation within the next 30 days, expressed as a value between 0 and 1 (i.e. 0 % to 100 %). A score of 0.42 means „the model estimates a 42 % chance of real-world exploitation within 30 days“.

    Read in glossary
    0.5 %
    Low — model estimates < 1% exploitation likelihood.
    EPSS percentile

    The EPSS percentile is the relative position of a vulnerability within all EPSS-scored CVEs, expressed as a value between 0 and 1. A percentile of 0.90 means „this CVE has a higher EPSS score than 90 % of all other scored CVEs“. Unlike the EPSS score, it is not a probability — but a positioning within a ranking.

    Read in glossary
    40.5
    High — this CVE ranks above the median of all CVEs scored today (rank ≥ 36%).
    KEV status

    The KEV catalogue is a list maintained by the US authority CISA of vulnerabilities for which active exploitation in the wild has been confirmed. It answers not the question „how severe?“ but „is it already being attacked?“ — thereby sharply prioritising patching.

    Read in glossary
    —
    Published
    CWE

    CWE is a catalogue of typical weakness types in software and hardware — such as flawed input validation, unsafe memory handling or poor authentication. Where a CVE names a concrete vulnerability in a concrete product, a CWE describes the underlying class of defect.

    Read in glossary
    CWE-1333

    Detection rules

    No NEOSEC detection rule is available for this vulnerability yet.

    Classification under NIS2 and CRA

    Rule-based classification from exploitation status and severity. It does not replace a case-by-case assessment.

    NIS2

    NIS2 is EU Directive (EU) 2022/2555 to raise the level of cybersecurity across the Union. It substantially broadens obligations compared with the first NIS directive: more sectors, mandatory risk management, staged reporting duties and personal accountability of senior management.

    Read in glossary
    High technical severity: assess and remediate the vulnerability in vulnerability handling under Art. 21(2)(e) NIS2 and document the decision.
    CRA

    The CRA is EU Regulation (EU) 2024/2847 setting horizontal cybersecurity requirements for „products with digital elements“ — from industrial controllers and software to connected consumer devices. For the first time manufacturers must ensure security across the entire product lifecycle, handle vulnerabilities and provide security updates.

    Read in glossary
    From 11.12.2027, Annex I Part II CRA requires manufacturers of affected products with digital elements to handle vulnerabilities without delay and provide security updates.
    ISO/IEC 27001

    ISO/IEC 27001 is the internationally leading standard for an information security management system (ISMS). It describes a risk-based, process-oriented framework to systematically plan, implement, review and improve information security.

    Read in glossary
    Control A.8.8, management of technical vulnerabilities: assess relevance to your systems, plan remediation and keep evidence.

    Description

    Datadog dd-trace-py is the Datadog Python APM client. From 1.5.0 until 3.19.9 and 4.15.6, the default query-string obfuscation regular expression can exhibit excessive backtracking while synchronously processing attacker-controlled URL query strings for HTTP span metadata. A remote attacker can cause prolonged CPU consumption, request latency, and service unavailability in affected HTTP tracing integrations that include query strings in URL span tags. The vulnerable processing is enabled by default for those integrations. This issue is fixed in versions 3.19.9 and 4.15.6.

    Source: NVD (NIST), cvelistv5, OSV (Open Source Vulnerabilities), GitHub Security Advisories

    Affected products

    The following versions are affected. Older releases of the same product line are also vulnerable unless stated otherwise.

    Affected products
    Affected versionsFixed in
    DataDogdd-trace-py
    • ≥ 1.5.0, < 3.19.9
    • —
    pipddtrace
    • >= 1.5.0, < 3.19.9
    • >= 4.0.0, < 4.15.6
    • 3.19.9
    • 4.15.6
    pypiddtrace
    • 2.6.0
    • 1.15.0
    • 1.6.0rc2
    • 4.11.5
    • 3.9.0rc1
    • 2.9.0rc7
    • 2.7.0
    • 3.12.0rc3
    • 3.16.0rc2
    • 2.14.7
    • 4.13.0rc2
    • 2.9.4
    • 4.8.13
    • 2.18.2
    • 2.16.3
    • 2.16.0rc1
    • 2.2.2
    • 4.13.3
    • 3.10.0
    • 2.11.7
    • 4.0.3
    • 1.13.6
    • 4.1.0rc2
    • 3.7.2
    • 2.4.2
    • 1.12.5
    • 1.5.4
    • 1.8.0rc3
    • 4.11.0
    • 2.8.6
    • 2.10.1
    • 1.8.0
    • 1.11.1
    • 4.6.0rc1
    • 1.15.2
    • 2.3.1
    • 2.21.7
    • 2.6.4
    • 1.10.1
    • 4.2.1
    • 1.7.0
    • 1.17.0
    • 2.20.0rc1
    • 3.17.3
    • 2.13.1
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    Vendors and products

    Weakness classes (CWE)

    • CWE-1333Inefficient Regular Expression Complexity

      Base

      The product uses a regular expression with a worst-case computational complexity that is inefficient and possibly exponential.

      Entry at MITRE CWE-1333

    References & sources

    • github.comDataDog/dd-trace-py/commit/63ddc3cb07d8813ded7a8b3ab5b8d0f5470e…x_refsource_MISC, web
    • github.comDataDog/dd-trace-py/commit/83ea39845dd95bfb9b8e247c62b3d22fc5dc…x_refsource_MISC, web
    • github.comDataDog/dd-trace-py/commit/a6d73607ea45ecd67152630f64b094555697…x_refsource_MISC, web
    • github.comDataDog/dd-trace-py/pull/20857x_refsource_MISC, web
    • github.comDataDog/dd-trace-py/pull/20862x_refsource_MISC, web
    • github.comDataDog/dd-trace-py/pull/20880x_refsource_MISC, web
    • github.comDataDog/dd-trace-py/releases/tag/v3.19.9x_refsource_MISC, web
    • github.comDataDog/dd-trace-py/releases/tag/v4.15.6x_refsource_MISC, web
    • github.comDataDog/dd-trace-py/security/advisories/GHSA-3633-r77q-h3v3x_refsource_CONFIRM, web
    • NVD (NIST)vuln/detail/CVE-2026-116588advisory
    • github.comDataDog/dd-trace-pypackage

    Changes to this CVE

    Who changed this CVE and when: NVD (analysis, affected products, CVSS), the CVE publisher (CNA) and additional providers such as CISA (ADP).

    1. ReceivedGitHub

      CVSS V4.0: AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N

      Weakness type: CWE-1333

      Description added or changed

      Show 13 original changes
      Individual changes of this event as published by NVD
      TypeActionBeforeAfter
      Descriptionadded
      —
      Datadog dd-trace-py is the Datadog Python APM client. From 1.5.0 until 3.19.9 and 4.15.6, the default query-string obfuscation regular expression can exhibit excessive backtracking while synchronously processing attacker-controlled URL query strings for HTTP span metadata. A remote attacker can cause prolonged CPU consumption, request latency, and service unavailability in affected HTTP tracing integrations that include query strings in URL span tags. The vulnerable processing is enabled by default for those integrations. This issue is fixed in versions 3.19.9 and 4.15.6.
      CVSSadded
      —
      AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X
      Weakness type (CWE)added
      —
      CWE-1333
      Affected versions (publisher)added
      —
      New affected value received. <a href="https://github.com/CVEProject/cvelistV5/blob/main/cves/2026/116xxx/CVE-2026-116588.json">CVE-2026-116588</a>
      Referenceadded
      —
      https://github.com/DataDog/dd-trace-py/commit/63ddc3cb07d8813ded7a8b3ab5b8d0f5470e4bfd
      Referenceadded
      —
      https://github.com/DataDog/dd-trace-py/commit/83ea39845dd95bfb9b8e247c62b3d22fc5dce1ce
      Referenceadded
      —
      https://github.com/DataDog/dd-trace-py/commit/a6d73607ea45ecd67152630f64b0945556972ed8
      Referenceadded
      —
      https://github.com/DataDog/dd-trace-py/pull/20857
      Referenceadded
      —
      https://github.com/DataDog/dd-trace-py/pull/20862
      Referenceadded
      —
      https://github.com/DataDog/dd-trace-py/pull/20880
      Referenceadded
      —
      https://github.com/DataDog/dd-trace-py/releases/tag/v3.19.9
      Referenceadded
      —
      https://github.com/DataDog/dd-trace-py/releases/tag/v4.15.6
      Referenceadded
      —
      https://github.com/DataDog/dd-trace-py/security/advisories/GHSA-3633-r77q-h3v3

      Source identifier: security-advisories@github.com

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