BlackTreeCVE Intelligence
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Full vulnerability report · 2026
CVE-2026-86000High confidence

Soup Sieve: Polynomial-time ReDoS (O(n²)) in the `IDENTIFIER` / `VALUE` selector sub-patterns

facelessuser · soupsieve

Official source article: GitHub GHSA-GJV8-XP57-G29C ↗. Check the applicable product and release in the original source.

5.3MediumCVSS 3.1
Recommended action
Patch only the product branches with a verified fix

Medium technical severity with public exploit material referenced by a structured source; prioritise exposed affected systems while verifying vendor guidance. Verified remediation exists for at least one product or source, but 102 structured product or package states remain unresolved. Apply remediation only to the exact product branch confirmed by its source.

Fix availability varies by product
R
Operational reassessment

Published severity in operational context

Open reassessment dashboard →
Published severityMediumOperational priority:High, raised one band.upgradedsince 17 Sep 2026

Evidence used

  • No CISA KEV confirmation is currently recorded.
  • A structured source references public exploit or proof-of-concept material.
  • The selected CVSS metric records a network-reachable, unauthenticated path with no user interaction.
  • EPSS is 0.61% for the current model date.

Compensating controls

  • Validate the affected product branch and deploy the verified fixed release.
  • Restrict the affected network interface to trusted sources where business-safe.
  • Increase monitoring for the attack path and post-exploitation behaviour described in the report.

Verification

  1. Confirm that the asset runs facelessuser soupsieve and falls inside the recorded affected range.
  2. Verify the installed build against the product-specific fixed version after deployment.
  3. Validate exposure, authentication requirements and compensating controls in the actual environment.
  4. Reopen this reassessment when CVSS, KEV, EPSS, exploit evidence or remediation changes.
Mitigation target: Within 30 daysRemediation target: Within 180 days

This automated reassessment organises public evidence. It does not know asset exposure, business impact or control effectiveness and does not replace CVSS or a human risk decision.

Cross-source reconciliation

Remediation availability differs by product scope

Verified remediation exists for at least one product or source, but 102 structured product or package states remain unresolved. Apply remediation only to the exact product branch confirmed by its source.

Distribution package intelligence

Release-specific package status

Debian, ubuntu findings are scoped to the named distribution, release and source package. An absent finding does not mean a package is unaffected.

5 package states
Package result overrides the generic status

BlackTree has verified remediation for at least one product or source, but the relevant distribution still reports no fixed package for 4 affected package states shown here. Treat those rows as affected with no fix until that distribution publishes a fixed version.

Repository candidate not checked

A published vendor fix does not prove that a matching update is enabled and installable on a particular asset. Confirm the local package candidate before scheduling remediation.

Distribution releaseSource packageVendor stateFixed versionEvidence
Debian trixietrixie · sourcesoupsieveAffected, no fix publishedDebian currently tracks this release as open.Not published in this feedDebian Security Tracker ↗Source updated 8 Oct 2026
Debian bookwormbookworm · sourcesoupsieveAffected, no fix publishedDebian currently tracks this release as open.Not published in this feedDebian Security Tracker ↗Source updated 8 Oct 2026
Debian forkyforky · sourcesoupsieveAffected, no fix publishedDebian currently tracks this release as open.Not published in this feedDebian Security Tracker ↗Source updated 8 Oct 2026
Debian sidsid · sourcesoupsieveAffected, no fix publishedDebian currently tracks this release as open.Not published in this feedDebian Security Tracker ↗Source updated 8 Oct 2026
Ubuntu 24.04 LTSnoble · standard archivesoupsieveUnder evaluationCanonical reports that the package might be affected and still needs evaluation or fixing.Not published in this feedCanonical Ubuntu Security ↗Source updated 7 Oct 2026
Open-source package ranges3 source-attributed ranges

These OSV and GitHub advisory ranges apply only to the named package and ecosystem. A listed fixed version is not a universal product patch or proof that an update is installed.

Ecosystem and packageAffected rangeFirst fixed versionEvidence
PyPIsoupsieveECOSYSTEM: introduced 0; fixed 2.9.02.9.0OSV record ↗aggregator derived · 1 Oct 2026
PyPIsoupsieveECOSYSTEM: introduced 0; fixed 2.9.02.9.0OSV record ↗source linked ecosystem record · 1 Oct 2026
pipsoupsieve< 2.9.02.9.0GitHub advisory ↗upstream repository advisory · 17 Sep 2026
Direct vendor intelligence

Authoritative vendor CSAF and VEX advisories

Structured product status and remediation from the issuing vendor. Product-state explanations are always visible; large lists can be searched or downloaded.

1 current
CVE-2026-86000 · CSAF 2.0 · revision 3 · finalRed Hat Product Securitysoupsieve: Soup Sieve: Denial of Service via crafted CSS selectors
98 known affected

The vendor explicitly identifies these products as affected by this CVE.

  • exploit-intelligence/vulnerability-analysis-rhel9 as a component of Exploit Intelligence
  • lightspeed-core/rag-tool-cpu-rhel9 as a component of Lightspeed Core
  • lightspeed-core/rag-tool-cuda-12.9-rhel9 as a component of Lightspeed Core
  • mta/mta-solution-server-rhel9 as a component of Migration Toolkit for Applications 8
  • openshift-lightspeed-tech-preview/lightspeed-rag-tool-rhel9 as a component of OpenShift Lightspeed
  • openshift-lightspeed/lightspeed-ocp-rag-rhel9 as a component of OpenShift Lightspeed
  • ansible-automation-platform-25/lightspeed-chatbot-rhel8 as a component of Red Hat Ansible Automation Platform 2
  • rhai-early-access/docling-sdk-cuda-rhel9 as a component of Red Hat OpenShift AI (RHOAI)
  • rhai-early-access/docling-serve-cuda-rhel9 as a component of Red Hat OpenShift AI (RHOAI)
  • rhoai/odh-automl-rhel9 as a component of Red Hat OpenShift AI (RHOAI)
  • rhoai/odh-autorag-rhel9 as a component of Red Hat OpenShift AI (RHOAI)
  • rhoai/odh-feature-server-rhel9 as a component of Red Hat OpenShift AI (RHOAI)
Summary
A flaw was found in Soup Sieve, a CSS selector library. An attacker can craft a malicious CSS selector that, when processed by the library, leads to excessive CPU consumption. This occurs due to a polynomial-time regular expression denial of service (ReDoS) vulnerability in the selector parser. Successful exploitation can cause the application to stall, leading to a denial of service.
Remediation
No mitigation is currently available for this vulnerability. Users are advised to apply the security update when available.
Optional official sources

National CERT insights
?CERT means Computer Emergency Response Team; CSIRT is the closely related term Computer Security Incident Response Team.

Choose official national sources for this report. Each advisory shows its original language. Your selection is remembered on this device and included in shared links.

Official European source

ENISA European Vulnerability Database

Official EUVD identifiers, advisory evidence and known-exploited context. Missing fields are not treated as evidence of low risk.

1 current
ENISA EUVD identifier

EUVD-2026-81689

No EUVD known-exploited evidence

Soup Sieve is a CSS selector library designed to be used with Beautiful Soup 4. Prior to 2.9, the selector parser in src/soupsieve/css_parser.py defines IDENTIFIER with adjacent quantified groups over overlapping character classes, and VALUE embeds IDENTIFIER for attribute selectors. When an attacker-controlled selector contains a long identifier or unquoted attribute-value run followed by input that makes the overall match fail, the regular expression engine explores quadratically many splits between the overlapping groups. User-controlled selectors can reach this path through soupsieve.compile(), soupsieve.select(), or BeautifulSoup.select(), while applications using only hard-coded selectors are unaffected. The resulting CPU consumption can hold the Python GIL, exhaust application workers, and stall a service; successful plain identifier matches are linear, and the issue does not cause memory corruption or code execution. The issue is fixed in version 2.9.

EUVD state
Present in the current official mapping
Known exploitation
Not present in the current ENISA EUVD known-exploited dataset. This is not proof of no exploitation.
ENISA score
5.3 · CVSS 3.1
Advisory evidence
No linked advisory details stored yet
Recommended actionPatch only the product branches with a verified fix

Medium technical severity with public exploit material referenced by a structured source; prioritise exposed affected systems while verifying vendor guidance. Verified remediation exists for at least one product or source, but 102 structured product or package states remain unresolved. Apply remediation only to the exact product branch confirmed by its source.

Fix availability varies by product
01

What, why and how

Soup Sieve is a CSS selector library designed to be used with Beautiful Soup 4. Prior to 2.9, the selector parser in src/soupsieve/css_parser.py defines IDENTIFIER with adjacent quantified groups over overlapping character classes, and VALUE embeds IDENTIFIER for attribute selectors. When an attacker-controlled selector contains a long identifier or unquoted attribute-value run followed by input that makes the overall match fail, the regular expression engine explores quadratically many splits between the overlapping groups. User-controlled selectors can reach this path through soupsieve.compile(), soupsieve.select(), or BeautifulSoup.select(), while applications using only hard-coded selectors are unaffected. The resulting CPU consumption can hold the Python GIL, exhaust application workers, and stall a service; successful plain identifier matches are linear, and the issue does not cause memory corruption or code execution. The issue is fixed in version 2.9.

What

Soup Sieve is a CSS selector library designed to be used with Beautiful Soup 4. Prior to 2.9, the selector parser in src/soupsieve/css_parser.py defines IDENTIFIER with adjacent quantified groups over overlapping character classes, and VALUE embeds IDENTIFIER for attribute selectors. When an attacker-controlled selector contains a long identifier or unquoted attribute-value run followed by input that makes the overall match fail, the regular expression engine explores quadratically many splits between the overlapping groups. User-controlled selectors can reach this path through soupsieve.compile(), soupsieve.select(), or BeautifulSoup.select(), while applications using only hard-coded selectors are unaffected. The resulting CPU consumption can hold the Python GIL, exhaust application workers, and stall a service; successful plain identifier matches are linear, and the issue does not cause memory corruption or code execution. The issue is fixed in version 2.9.

Why

The product does not properly control the allocation and maintenance of a limited resource.

How

An attacker operating through a network path may attempt exploitation without authentication or user interaction. If successful, the issue may cause the confidentiality, integrity or availability impact described by the vendor.

What

Soup Sieve is a CSS selector library designed to be used with Beautiful Soup 4. Prior to 2.9, the selector parser in src/soupsieve/css_parser.py defines IDENTIFIER with adjacent quantified groups over overlapping character classes, and VALUE embeds IDENTIFIER for attribute selectors. When an attacker-controlled selector contains a long identifier or unquoted attribute-value run followed by input that makes the overall match fail, the regular expression engine explores quadratically many splits between the overlapping groups. User-controlled selectors can reach this path through soupsieve.compile(), soupsieve.select(), or BeautifulSoup.select(), while applications using only hard-coded selectors are unaffected. The resulting CPU consumption can hold the Python GIL, exhaust application workers, and stall a service; successful plain identifier matches are linear, and the issue does not cause memory corruption or code execution. The issue is fixed in version 2.9.

Why

The product does not properly control the allocation and maintenance of a limited resource.

How

An attacker operating through a network path may attempt exploitation without authentication or user interaction. If successful, the issue may cause the confidentiality, integrity or availability impact described by the vendor.

02

Exploit reality and attack path

CVSS severity, EPSS forecast probability, public exploit material and CISA-confirmed exploitation are separate signals.

Observed exploitation
?Confirmed exploitation and public exploit material are separate signals. Attacks can occur without public proof-of-concept or exploit code.
No confirmed evidence

No CISA KEV match was present at the last successful refresh. This means no confirmation from that source, not proof of no exploitation.

Public PoC / exploit material
?Confirmed exploitation and public exploit material are separate signals. Attacks can occur without public proof-of-concept or exploit code.
Reference recorded

CISA Vulnrichment records proof-of-concept exploitation in its SSVC data. BlackTree has not independently executed or validated exploit material.

Likely attack path
a network path → Uncontrolled Resource Consumption → cause the confidentiality, integrity or availability impact described by the vendor
Attack surface
Network
Privileges required
None: unauthenticated exploitation is possible
User interaction
None
Attack complexity
Low: no specialised conditions are recorded
Security boundary
Unchanged: impact remains within the vulnerable component's security authority
Weakness
?CWE means Common Weakness Enumeration: a standard category for the underlying weakness.
CWE-400 ↗

CWE-400: Uncontrolled Resource Consumption. The product does not properly control the allocation and maintenance of a limited resource.

CVSS vector
?CVSS means Common Vulnerability Scoring System. The vector records the metric values used to calculate technical severity.
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L

Common Vulnerability Scoring System 3.1: the compact vector below is decoded into plain language.

AVNetworkAttack vector: The vulnerable component can be reached over a network.ACLowAttack complexity: No specialised conditions are required beyond attacker-controlled input.PRNonePrivileges required: The attacker does not need an account or existing privileges.UINoneUser interaction: No action by another user is required.SUnchangedScope: The security impact remains within the vulnerable component's authority.CNoneConfidentiality impact: No direct loss is represented by this metric.INoneIntegrity impact: No direct loss is represented by this metric.ALowAvailability impact: A successful attack can cause a limited loss.
Post-exploitation / living off the land
No specific living-off-the-land technique is confirmed in the structured sources. Monitor normal administration tools for activity inconsistent with the affected service's baseline.
NetworkUnauthenticatedCWE-400Public exploit reference
A

Official authority intelligence

Only matched European and national findings are included. Language selectors and unavailable sources are omitted.

ENISA EUVD · EUVD-2026-81689Official EUVD mapping

Soup Sieve is a CSS selector library designed to be used with Beautiful Soup 4. Prior to 2.9, the selector parser in src/soupsieve/css_parser.py defines IDENTIFIER with adjacent quantified groups over overlapping character classes, and VALUE embeds IDENTIFIER for attribute selectors. When an attacker-controlled selector contains a long identifier or unquoted attribute-value run followed by input that makes the overall match fail, the regular expression engine explores quadratically many splits between the overlapping groups. User-controlled selectors can reach this path through soupsieve.compile(), soupsieve.select(), or BeautifulSoup.select(), while applications using only hard-coded selectors are unaffected. The resulting CPU consumption can hold the Python GIL, exhaust application workers, and stall a service; successful plain identifier matches are linear, and the issue does not cause memory corruption or code execution. The issue is fixed in version 2.9.

Official EUVD record ↗
Cyber Security Agency of Singapore · English · CSA-SB-20260923Security Bulletin 23 Sep 2026

The Cyber Security Agency of Singapore included this CVE in its official Security Bulletin 23 Sep 2026, published on 23 September 2026. Open the linked bulletin for the product, severity and reference information published in that issue.

Official advisory ↗
03

Patch and workaround

Operational remediation based on structured source evidence.

Status
?Patch availability is based on structured fixed-version fields and authoritative update references. If no fix is verified, check the vendor advisory before making a change.
Fix availability varies by product
Affected
Fixed
2.9.
Action
Use the product-specific evidence above. Patch only products with a verified fixed release, and keep every affected or under-investigation state without a matching fix in the remediation queue.
Workaround
No mitigation is currently available for this vulnerability. Users are advised to apply the security update when available.
04

Evidence and provenance

Published 17 Sept 2026 · Last source change 17 Sept 2026, 15:45 UTC · CWE-400 · Uncontrolled Resource Consumption

CVE recordCVE.org · 5.2
CVSS sourceCNA
EPSS source
?The date BlackTree first stored a score for this CVE from the daily FIRST EPSS feed.
FIRST · tracked since 2026-09-18
European sourceENISA EUVD · EUVD-2026-81689
Product sourceVendor CSAF · Red Hat Product Security
Remediation sourceVendor CSAF · Red Hat Product Security
CWE sourceCNA
NVD statusNVD awaiting enrichment

Core structured fields are present and their contributing authorities are shown above.

Material change intelligence

What changed after publication

View recent updates ↗
  1. Vendor guidanceAuthoritative vendor guidance changed from remediation: access.redhat.com/CVE-2026-86000 to remediation: access.redhat.com/CVE-2026-86000.
    Before
    remediation: access.redhat.com/CVE-2026-86000
    After
    remediation: access.redhat.com/CVE-2026-86000
    Red Hat Product Security ↗
  2. Remediation statusRemediation status changed from Awaiting fix to Mitigation available.
    Before
    Awaiting fix
    After
    Mitigation available
    Red Hat Product Security ↗
  3. ENISA EUVD mappingEUVD-2026-81689 was added to the official ENISA EUVD mapping for this CVE.
    Before
    not recorded
    After
    {"euvdId":"EUVD-2026-81689"}
    ENISA EUVD ↗
  4. Affected versionsThe structured affected or fixed version information changed.
    Before
    exploit-intelligence/vulnerability-analysis-rhel9 as a component of Exploit Intelligence; lightspeed-core/rag-tool-cpu-rhel9 as a component of Lightspeed Core; lightspeed-core/rag-tool-cuda-12.9-rhel9 as a component of Lightspeed Core; mta/mta-solution-server-rhel9 as a component of Migration Toolkit for Applications 8; openshift-lightspeed-tech-preview/lightspeed-rag-tool-rhel9 as a component of OpenShift Lightspeed; openshift-lightspeed/lightspeed-ocp-rag-rhel9 as a component of OpenShift Lightspeed; ansible-automation-platform-25/lightspeed-chatbot-rhel8 as a component of Red Hat Ansible Automation Platform 2; python-attrs.src as a component of Red Hat Hardened Images; python-rpds-py.src as a component of Red Hat Hardened Images; python-urllib3.src as a component of Red Hat Hardened Images; rhai-early-access/docling-sdk-cuda-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhai-early-access/docling-serve-cuda-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-automl-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-autorag-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-feature-server-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-kserve-autogluon-server-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-kserve-storage-initializer-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-ogx-core-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-minimal-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-llmcompressor-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-th-torch-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-th-torch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-th-torch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-th06-cpu-torch210-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-th06-cpu-torch291-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); and 71 more
    After
    exploit-intelligence/vulnerability-analysis-rhel9 as a component of Exploit Intelligence; lightspeed-core/rag-tool-cpu-rhel9 as a component of Lightspeed Core; lightspeed-core/rag-tool-cuda-12.9-rhel9 as a component of Lightspeed Core; mta/mta-solution-server-rhel9 as a component of Migration Toolkit for Applications 8; openshift-lightspeed-tech-preview/lightspeed-rag-tool-rhel9 as a component of OpenShift Lightspeed; openshift-lightspeed/lightspeed-ocp-rag-rhel9 as a component of OpenShift Lightspeed; ansible-automation-platform-25/lightspeed-chatbot-rhel8 as a component of Red Hat Ansible Automation Platform 2; rhai-early-access/docling-sdk-cuda-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhai-early-access/docling-serve-cuda-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-automl-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-autorag-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-feature-server-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-kserve-autogluon-server-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-kserve-storage-initializer-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-ogx-core-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-minimal-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-llmcompressor-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-th-torch-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-th-torch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-th-torch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-th06-cpu-torch210-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-th06-cpu-torch291-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-th06-cuda130-torch210-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-th06-cuda130-torch291-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-th06-rocm64-torch291-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); and 68 more
    Red Hat Product Security ↗
  5. Catalogue recordCVE added to the BlackTree catalogue.
    CNA ↗
  6. Vendor guidanceAuthoritative vendor guidance changed: added remediation: github.com/GHSA-gjv8-xp57-g29c; removed remediation: github.com/ce44e4996e6632871c18cdd7a7fb641be8ef34ef.
    Before
    remediation: github.com/ce44e4996e6632871c18cdd7a7fb641be8ef34ef
    After
    remediation: github.com/GHSA-gjv8-xp57-g29c
    CNA ↗
Material fields only · duplicate refreshes suppressed · history retained for the configured operational retention period
Technical terms and abbreviations used in this report
CVE
Common Vulnerabilities and Exposures: the public identifier for one disclosed vulnerability.
CVSS
Common Vulnerability Scoring System: a technical severity framework; it is not patching priority by itself.
EPSS
Exploit Prediction Scoring System: FIRST's estimate of the probability that exploitation activity will be observed in the next 30 days; it is a forecast, not confirmation.
CWE
Common Weakness Enumeration: the standard category describing the underlying software or hardware weakness.
CNA
CVE Numbering Authority: an organisation authorised to assign and publish CVE records.
CISA ADP
Cybersecurity and Infrastructure Security Agency Authorized Data Publisher: structured enrichment added to a CVE record.
NVD
National Vulnerability Database: NIST's enrichment service for CVE records.
CERT / CSIRT
A computer security incident response team that publishes warnings or coordinates incident response.
PoC
Proof of concept: public material that demonstrates or helps reproduce exploitation.
CSAF
Common Security Advisory Framework: a machine-readable format for security advisories.
LoTL
Living off the land: abuse of legitimate tools or system functions during an attack.
Free version - for non-commercial use only.CVE-2026-86000 · cve.blacktree.nl