[CVE-2026-74579][LOW] netfilter: nft_payload: fix mask build for partial field offload [ Upstream

[CVE-2026-74579][LOW] netfilter: nft_payload: fix mask build for partial field offload [ Upstream

[AL-KERNEL]

CVE: CVE-2026-74579
Priority: LOW
AL-KERNEL base severity: LOW
KPANIC flag: NO
Patch: netfilter: nft_payload: fix mask build for partial field offload [ Upstream
Commit: b19b5d2e042c294e2cc1c908dc598f9d64015396
Upstream patch: https://git.kernel.org/pub/scm/linux/kernel/git/stable/linux.git/commit/?id=b19b5d2e042c294e2cc1c908dc598f9d64015396
Original CVE announcement: https://lore.kernel.org/linux-cve-announce/?q=CVE-2026-74579
Analysis date: Mon, 17 Aug 2026 01:51:32 -0400
ActionableScore: 2
ActionableScore lower bound: 0
Actionable bucket: Ordinary Moderate / Low-like
Manual review required: NO

Summary:
A local administrator or delegated CAP_NET_ADMIN user can create an nftables payload offload rule whose partial-field mask is built incorrectly, causing a UBSAN shift warning and possible hardware offload policy mismatch, but no concrete memory corruption or privilege escalation primitive is shown.

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ABOUT THIS REPORT
======================================================================

The original Linux kernel CVE announcement for CVE-2026-74579 is available here:
https://lore.kernel.org/linux-cve-announce/?q=CVE-2026-74579

The original announcement does not normally provide a security severity
estimate, CVSS assessment, or enough information to determine whether the
reported kernel bug represents a practically relevant security issue.

This report was generated by AL-KERNEL, an AI-assisted Linux kernel
vulnerability analysis system developed by Alexander Larkin. It combines
an autonomous classifier with LLM-assisted technical analysis and a
separate ActionableScore mechanism.

The purpose of this report is to prioritize Linux kernel CVEs before
manual review, identify cases that require prompt investigation, and
support automatic closure of issues that are unlikely to have meaningful
security impact.

Published priority for this report: LOW
Manual review required: NO

A detailed explanation of the methodology and priority rules is included
at the end of this message.

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AL-KERNEL CLASSIFICATION RESULT
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CVE-2026-74579	LOW	CHECK WITH IMPACT FROM ORIG NN MODERATE	Maybe valid. Check manually. Hints by AL-KERNEL: The best (paranoid) CVSS is 'AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L';CWE-682;CWE-758;CWE-693;Other CVSS 'AV:L/AC:L/PR:H/UI:N/S:U/C:N/I:L/A:L';BEST CVSS score: '4.4';DESCR 'nft_payload_offload_mask can build an incorrect hardware offload mask for partial payload field matches. For example, a partial IPv6 address match can require a shift such as 1 << 120 on a 32 bit int, which is undefined behavior and can trigger a UBSAN shift out of bounds warning. The same logic may leave trailing mask words set to 0xffffffff, so the offloaded match can cover more bytes than the nftables rule actually matches. This is a control plane issue in nftables offload configuration rather than a packet triggered memory corruption bug. For the CVSS the PR:L is used in the paranoid score because some deployments may delegate CAP_NET_ADMIN or nftables control to a container root or service account, even though the base case is administrative PR:H. The issue is not directly network reachable. Impact is mainly a low integrity risk from firewall offload policy mismatch and a low availability risk from warnings or incorrect offload behavior.';NO MANUAL CHECK; ,and ActionableScore result is Ordinary Moderate / Low-like (with actual score 1)	YES	REMOTE WRITE KASAN OOB SIMPLEFIX NETFILTER IPV6  DECREASED_TO_MODERATE_REGULAR_FROM_MODERATE7_BASED_ON_GUESSCVSS DECREASED_TO_LOW_FROM_MODERATE_BASED_ON_ACTIONABLESCORELESSTHAN3	NO	NO	guess

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ACTIONABLESCORE ANALYSIS
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ActionableScore=2
ActionableScoreLower=0

## 1. ActionableScore

* Conservative score: 0
* Paranoid score: 2
* Final recommended bucket: **Ordinary Moderate / Low-like**::

## 2. Signal breakdown

Conservative signals:

* Requires admin/root/CAP_NET_ADMIN in typical deployments: -2. Creating or modifying nftables offload rules normally requires CAP_NET_ADMIN.
* Integrity impact plausible: +1. The generated hardware offload mask can cover more bytes than the nft rule actually matches, creating a possible firewall offload policy mismatch.
* No reliable kernel crash / strong DoS: +0. The commit shows UBSAN shift-out-of-bounds, but not a panic, Oops, UAF, OOB write, or persistent system-wide failure.
* No memory corruption primitive: +0. The patch removes undefined shift logic and fixes mask construction. It does not show UAF, double free, OOB write, type confusion, refcount misuse, or arbitrary write.
* No direct network reachability: +0. Packets may be affected after a bad offload rule exists, but packet traffic does not create the vulnerable rule.

Paranoid added signals:

* Cross-boundary policy mismatch concern: +1. In deployments relying on nftables hardware offload, an incorrect mask can make hardware filtering diverge from intended firewall semantics.
* Availability impact low/plausible: +1. UBSAN warnings or incorrect offload behavior can cause operational disruption, but this is not a strong crash primitive.
* Reduced privilege interpretation: privilege penalty is softened from -2 to 0 in the paranoid score if nftables control is delegated to container root, a service account, or a reduced-capability administrator.

## 3. Reachability analysis

The trigger is local control-plane configuration of nftables payload expressions with hardware offload. In normal deployments this requires CAP_NET_ADMIN, so a fully unprivileged local user cannot trigger it directly. Namespaces or containers can lower practical reachability if CAP_NET_ADMIN or nftables management is delegated, but that is environment-specific. The affected path is not directly network-triggerable because incoming packets do not build the offload mask by themselves. Realistic exploitation requires nftables offload being used and an attacker being able to install or modify relevant nft rules.

Call-site confidence: medium. The patch context clearly identifies nft_payload_offload_mask() and the offload mask construction path, but the full driver offload call chain is not included.

## 4. Severity interpretation

This behaves more like an ordinary Moderate or Low-like issue than an Important-class kernel vulnerability. The demonstrated problem is a logic and undefined-behavior bug in mask generation, not memory corruption. The realistic impact is limited to possible nftables hardware offload policy mismatch and low operational disruption. There is no supported privilege escalation path, no kernel memory lifetime issue, and no direct remote attack surface.

## 5. One-sentence report phrase

A local administrator or delegated CAP_NET_ADMIN user can create an nftables payload offload rule whose partial-field mask is built incorrectly, causing a UBSAN shift warning and possible hardware offload policy mismatch, but no concrete memory corruption or privilege escalation primitive is shown.

## 6. Manual review recommendation

NO MANUAL CHECK NEEDED

This can be auto-closed for urgent triage because the score remains below 3, the bug is CAP_NET_ADMIN-gated in typical deployments, and the patch supports only a low-severity logic or policy-mismatch impact rather than memory corruption, LPE, or direct network reachability.

======================================================================
UPSTREAM PATCH SUMMARY
======================================================================

Patch: netfilter: nft_payload: fix mask build for partial field offload [ Upstream
Commit: b19b5d2e042c294e2cc1c908dc598f9d64015396
Upstream URL: https://git.kernel.org/pub/scm/linux/kernel/git/stable/linux.git/commit/?id=b19b5d2e042c294e2cc1c908dc598f9d64015396

Changed files:
  net/netfilter/nft_payload.c

Diff excerpt:

Not included in this email. See the upstream URL for the full patch.

Full patch:
https://git.kernel.org/pub/scm/linux/kernel/git/stable/linux.git/commit/?id=b19b5d2e042c294e2cc1c908dc598f9d64015396

======================================================================
DETAILED REPORT METHODOLOGY
======================================================================

The original Linux kernel CVE announcement for CVE-2026-74579 can be found here:
https://lore.kernel.org/linux-cve-announce/?q=CVE-2026-74579

The original CVE announcement normally does not include a security-level
estimate. In particular, it may not contain a CVSS assessment, an impact
level, or enough information to determine whether the reported bug is a
practically relevant security issue. One purpose of this parallel CVE list
is to provide that missing technical and prioritization information.

The original goal of the AL-KERNEL project was to prioritize Linux kernel
CVE analysis automatically before manual review. The system can also help
identify non-security issues that may be suitable for automatic closure.

This report was generated by AL-KERNEL, an AI-assisted Linux kernel
vulnerability analysis system developed by Alexander Larkin.

The first analysis stage combines an autonomous classifier with additional
LLM-based analysis. The autonomous classifier runs locally on a CPU and is
based on a backpropagation neural network. Together, these mechanisms
produce a technical vulnerability description, identify likely weakness
types, estimate CVSS severity, and provide input for ActionableScore.

Two CVSS estimates are retained because incomplete kernel vulnerability
information often permits more than one defensible interpretation:

  Conservative CVSS vector: AV:L/AC:L/PR:H/UI:N/S:U/C:N/I:L/A:L
  The Best / paranoid CVSS vector: AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L
  The Best / paranoid CVSS score: 4.4

The conservative vector represents a lower-impact interpretation.
The Best/paranoid vector intentionally represents a plausible upper-bound
interpretation and should not automatically be treated as demonstrated
real-world impact.

CVSS may also need to be adjusted for a particular Linux deployment,
because actual reachability, privileges, enabled kernel configuration,
hardware, namespaces, exposed device nodes, and other environmental
conditions can differ significantly between systems.

A separate ActionableScore mechanism evaluates practical remediation
urgency. Its analysis may include reachability, attack prerequisites,
subsystem exposure, memory-corruption characteristics, denial-of-service
reliability, and possible confidentiality, integrity, or
privilege-escalation impact.

  Conservative ActionableScore: 0
  Paranoid ActionableScore: 2

The final base severity is taken directly from the second tab-separated
field of the AL-KERNEL classification result. ActionableScore does not
replace or independently override that final AL-KERNEL decision, and
if ActionableScore adjusted impact level of ALKERNEL, then you would see
self-readable flags above like INCREASED_TO_HIGH_BASED_ON_ACTIONABLESCOREHIGHEREQTHAN7.

For an AL-KERNEL result of MODERATE, this report uses the following
additional presentation split:

  ActionableScore below 5   -> MODERATE REGULAR
  ActionableScore 5 or more -> MODERATE 7.0

The distinction between MODERATE REGULAR and MODERATE 7.0 makes it
possible to identify Moderate issues that should receive manual analysis
and fixes before lower-priority MODERATE REGULAR issues. In many cases,
MODERATE REGULAR fixes may wait for a later rebase or routine update.

There is one override in which MODERATE REGULAR becomes MODERATE 7.0
even when the ActionableScore is below 5. When the AL-KERNEL result
contains the KPANIC flag, a MODERATE result is always presented as
MODERATE 7.0. The KPANIC flag selected with few regexps without
usage of AI at all, so it helps to detect cases when Kernel Crash happens
and similar (to filter False-Negative results from the LLM usage).

KPANIC indicates that a reliable kernel crash, kernel panic, or similarly
serious kernel availability impact was identified by the classification
workflow.

AL-KERNEL base severity for this report: LOW
KPANIC detected for this report: NO
Published priority for this report (same as in Subject): LOW

These results are intended to support engineering triage. They are
machine-generated estimates, and cases marked for manual review should
be validated by a human security engineer before final disposition.
For more info read docs linked from here: https://kernelcve.org/
(and you can submit you own patch there to generate such a report
for non-existant CVE-id yet).

Note that in many cases this AI tool selects higher severity, than
real is (means you can expect Importants instead of Moderate 7.0 or
Moderates 7.0 instead of regular Moderates). If you see such cases,
please use reply email interface to add additional manual analyses
info to this particular CVE.
And please, please, let me know when you see Lows instead of Importants
or Important instead of Low (because particular for such cases I
need to tune this AI tool to make it better for this one and next similar).
My contact email for such notifications is alexanjelausa@gmail.com (and both
send reply to CVE record itself too and see "reply" button below for howto reply).