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    MedTech Cybersecurity · Since 2022

    Goat Feed · KEV

    CISA KEV: Linux Kernel CVE-2026-46300 (CVSS 3.1 7.8 HIGH) - Kernel Missing Initialization of a Variable Vulnerability

    In the Linux kernel, the following vulnerability has been resolved: net: skbuff: preserve shared-frag marker during coalescing skb_try_coalesce() can attach paged frags from @from to @to. If @from has SKBFL_SHARED_FRAG set, the resulting @to skb can contain the same externally-owned or page-cache-backed frags, but the shared-frag marker is currently lost. That breaks the invariant relied on by later in-place writers. In particular, ESP input checks skb_has_shared_frag() before deciding whether an uncloned nonlinear skb can skip skb_cow_data(). If TCP receive coalescing has moved shared frags into an unmarked skb, ESP can see skb_has_shared_frag() as false and decrypt in place over page-cache backed frags. Propagate SKBFL_SHARED_FRAG when skb_try_coalesce() transfers paged frags. The tailroom copy path does not need the marker because it copies bytes into @to's linear data rather than transferring frag descriptors.

    Back to the daily feed
    KEV
    criticalPublished October 29, 2026 at 1:00 PM UTC
    Blue Goat take· Blue Goat Cyber Research

    This memory corruption flaw in the Linux networking stack allows attackers to bypass write protections during data decryption. Manufacturers of connected imaging systems or patient monitors using Linux-based TCP/IP stacks are most at risk, especially those processing encrypted telemetry. Teams should audit their SBOMs for affected kernel versions and prioritize kernel updates to maintain data integrity across network interfaces.

    Blue Goat Risk Score

    Blue Goat Cyber MedTech rubric v1.0 · methodology

    6.1
    of 10
    notable
    CVSS technical
    40% · +3.1

    3.1 base 7.8 · CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

    Patient safety
    35% · +0.7

    No direct patient impact inferred

    Exploit maturity
    15% · +1.5

    On CISA KEV (in-the-wild)

    MedTech exposure
    10% · +0.8

    8/10 network-reachable signals

    How we got to 6.1

    1. 1
      CVSS technical severity (40%)

      Industry-standard exploitability + impact score. We prefer CVSS 4.0 and fall back to 3.1 per the FDA's Feb 2026 premarket cybersecurity guidance. Missing CVSS scores get a neutral 4.0 so unknown vulns are not over- or under-rated.

      3.1 base 7.8 × 40% = +3.12
    2. 2
      Patient safety impact (35%)

      What happens to a patient if this vuln is exploited on a connected device. Auto-inferred from headline, dek, tags, and device class against a curated MedTech keyword library (pacemaker, infusion pump, EHR, PACS, etc.).

      No direct patient impact inferred → 2 × 35% = +0.70
    3. 3
      Exploit maturity (15%)

      Is anyone actually using this in attacks? KEV listing > weaponized exploit > public PoC > none. KEV alone forces tier=critical regardless of CVSS.

      On CISA KEV (in-the-wild) → 10 × 15% = +1.50
    4. 4
      MedTech exposure (10%)

      How likely this affects clinical operations: presence in our MedTech feed (+4 baseline), network-reachable signals (+3), known device-class tags (+2), identified MedTech vendor (+1).

      Exposure 8/10 × 10% = +0.80

    Tier cutoffs: Critical ≥ 8.5 · High 7.0–8.4 · Notable 4.0–6.9 · Info < 4.0. Full methodology, weights, and changelog at /goatfeed/risk-rubric.

    Related Goat Feed analysis

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    Citations
    • CISA Known Exploited Vulnerabilities
    • Methodology and sources →
    #kev#cve#linux
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