CriticalCVE-2026-53753

    Crawl4AI: AST Sandbox Escape via gi_frame.f_back Chain - Pre-Auth RCE in Docker API (CVE-2026-53753)

    Published Last modified Sources: CVE.org, OSV

    What is affected, what to do

    Crawl4AI is an open-source LLM friendly web crawler & scraper. Prior to 0.8.7, the _safe_eval_expression() function in the computed fields feature uses an AST validator that only blocks attributes starting with underscore.

    An exploit is publicly available. Update Crawl4AI to version 0.8.7.

    Affected
    • Crawl4AI lt *..0.8.7
    Fixed in
    • Crawl4AI 0.8.7

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

    Metrics

    10.0

    Priority

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

    Source: NVD, CVSS v3

    10.0

    CVSS v3

    Severity Critical on the scale from 0 to 10.

    Source: CVE.org, OSV

    2.9 %

    EPSS score

    Moderate — model estimates 1-10% exploitation likelihood.

    Source: FIRST EPSS, percentile 86.9

    Show all metrics
    Severity
    Critical
    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
    129.87 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
    PoC (publicly reported)
    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
    10.0 Methodology
    CVSS v3

    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
    10.0
    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
    2.9 %
    Moderate — model estimates 1-10% 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
    86.9
    Critical — this CVE ranks in the top fifth of all CVEs scored today (rank ≥ 80%).
    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-94, CWE-913

    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

    Crawl4AI is an open-source LLM friendly web crawler & scraper. Prior to 0.8.7, the _safe_eval_expression() function in the computed fields feature uses an AST validator that only blocks attributes starting with underscore. Python generator and frame object attributes (gi_frame, f_back, f_builtins) do NOT start with underscore, enabling a complete sandbox escape to achieve arbitrary code execution. The attack requires no authentication (JWT disabled by default) and is triggered via POST /crawl with a crafted extraction schema. This vulnerability is fixed in 0.8.7.

    Source: NVD (NIST), OSV (Open Source Vulnerabilities), cvelistv5, CVE.org (MITRE)

    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
    unclecodecrawl4ai
    • < 0.8.7
    • 0.8.7
    kidocodecrawl4ai
    • < 0.8.7
    • 0.8.7
    pypicrawl4ai
    • 0.4.246
    • 0.3.742
    • 0.3.745
    • 0.3.71
    • 0.4.24
    • 0.4.3b3
    • 0.4.3b1
    • 0.4.245
    • 0.7.1
    • 0.7.3
    • 0.8.0
    • 0.5.0.post3
    • 0.3.741
    • 0.3.73
    • 0.3.74
    • 0.3.2
    • 0.5.0.post1
    • 0.7.2
    • 0.7.0
    • 0.6.1
    • 0.6.2
    • 0.3.8
    • 0.4.248b3
    • 0.3.743
    • 0.3.746
    • 0.4.3b2
    • 0.4.247
    • 0.4.22
    • 0.5.0.post4
    • 0.3.744
    • 0.3.72
    • 0.7.6
    • 0.3.4
    • 0.3.3
    • 0.4.23
    • 0.5.0.post2
    • 0.4.241
    • 0.6.0rc1
    • 0.4.243
    • 0.6.0
    • 0.8.5
    • 0.7.8
    • 0.4.248
    • 0.5.0
    • 0.3.7
    • 0.3.5
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    Vendors and products

    Weakness classes (CWE)

    • CWE-94Improper Control of Generation of Code ('Code Injection')

      Base

      The product constructs all or part of a code segment using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the syntax or behavior of the intended code segment.

      Entry at MITRE CWE-94

    • CWE-913Improper Control of Dynamically-Managed Code Resources

      Class

      The product does not properly restrict reading from or writing to dynamically-managed code resources such as variables, objects, classes, attributes, functions, or executable instructions or statements.

      Entry at MITRE CWE-913

    Public exploit references

    Publicly reported proof-of-concepts, exploit modules and detection templates for this vulnerability. NEOSEC links to the original sources only and does not provide any exploit code.

    Public exploit references
    PoC-in-GitHub (nomi-sec)Advanced-CVE-2026-53753 (opens in a new tab)github.comPoC (publicly reported)reported, not verified
    PoC-in-GitHub (nomi-sec)CVE-2026-53753 (opens in a new tab)github.comPoC (publicly reported)reported, not verified
    PoC-in-GitHub (nomi-sec)CVE-2026-53753-Crawl4AI-RCE (opens in a new tab)github.comPoC (publicly reported)reported, not verified

    References & sources

    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. Record modifiedCISA ADP

      CISA assessment (SSVC): exploitation: proof of concept, automatable: yes

      Show 2 original changes
      Individual changes of this event as published by NVD
      TypeActionBeforeAfter
      Referenceadded
      —
      https://github.com/unclecode/crawl4ai/security/advisories/GHSA-qxjp-w3pj-48m7
      SSVC assessmentadded
      —
      {"id":"CVE-2026-53753","role":"CISA Coordinator","options":[{"exploitation":"poc"},{"automatable":"yes"},{"technicalImpact":"total"}],"version":"2.0.3","timestamp":"2026-06-23T18:55:14.019870Z"}

      Source identifier: 134c704f-9b21-4f2e-91b3-4a467353bcc0

    2. ReceivedGitHub

      CVSS V3.1: AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

      Weakness type: CWE-94, CWE-913

      Description added or changed

      Show 6 original changes
      Individual changes of this event as published by NVD
      TypeActionBeforeAfter
      Affected versions (publisher)added
      —
      crawl4ai
      Descriptionadded
      —
      Crawl4AI is an open-source LLM friendly web crawler & scraper. Prior to 0.8.7, the _safe_eval_expression() function in the computed fields feature uses an AST validator that only blocks attributes starting with underscore. Python generator and frame object attributes (gi_frame, f_back, f_builtins) do NOT start with underscore, enabling a complete sandbox escape to achieve arbitrary code execution. The attack requires no authentication (JWT disabled by default) and is triggered via POST /crawl with a crafted extraction schema. This vulnerability is fixed in 0.8.7.
      CVSSadded
      —
      AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
      Weakness type (CWE)added
      —
      CWE-94
      Weakness type (CWE)added
      —
      CWE-913
      Referenceadded
      —
      https://github.com/unclecode/crawl4ai/security/advisories/GHSA-qxjp-w3pj-48m7

      Source identifier: security-advisories@github.com

    One NVD translation into another language is hidden.

    Linked advisories

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