From mboxrd@z Thu Jan 1 00:00:00 1970 From: AL-KERNEL To: kernel-cve@kernelcve.org Subject: [CVE-2026-74290][MODERATE 7.0] net/sched: cls_flow: Dont expose folded kernel pointers [ Upstream Date: Sat, 15 Aug 2026 19:24:41 -0400 Message-ID: MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit X-AL-KERNEL-CVE: CVE-2026-74290 X-AL-KERNEL-Priority: MODERATE 7.0 X-AL-KERNEL-Severity: MODERATE 7.0 X-AL-KERNEL-Base-Severity: MODERATE X-AL-KERNEL-KPANIC: NO X-AL-KERNEL-ActionableScore: 5 X-AL-KERNEL-ActionableScore-Lower: 4 X-AL-KERNEL-Commit: 19f2ecf8ea564562c7e7a919cf38068dd9aa1c96 List-Id: CVE: CVE-2026-74290 Priority: MODERATE 7.0 AL-KERNEL base severity: MODERATE KPANIC flag: NO Patch: net/sched: cls_flow: Dont expose folded kernel pointers [ Upstream Commit: 19f2ecf8ea564562c7e7a919cf38068dd9aa1c96 Upstream patch: https://git.kernel.org/pub/scm/linux/kernel/git/stable/linux.git/commit/?id=19f2ecf8ea564562c7e7a919cf38068dd9aa1c96 Original CVE announcement: https://lore.kernel.org/linux-cve-announce/?q=CVE-2026-74290 Analysis date: Sat, 15 Aug 2026 19:24:41 -0400 ActionableScore: 5 ActionableScore lower bound: 4 Actionable bucket: Actionable Moderate at minimum / manual-review candidate Manual review required: YES Summary: A local user able to configure `cls_flow` tc classifiers, including via a user/network namespace on permissive systems, can recover 32-bit folded values derived from kernel pointers through class statistics, weakening kernel pointer hiding but not directly providing memory corruption or privilege escalation. ====================================================================== ABOUT THIS REPORT ====================================================================== The original Linux kernel CVE announcement for CVE-2026-74290 is available here: https://lore.kernel.org/linux-cve-announce/?q=CVE-2026-74290 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: MODERATE 7.0 Manual review required: YES A detailed explanation of the methodology and priority rules is included at the end of this message. ====================================================================== AL-KERNEL CLASSIFICATION RESULT ====================================================================== CVE-2026-74290 MODERATE CHECK WITH IMPACT FROM ORIG NN IMPORTANT Maybe valid. Check manually. Hints by AL-KERNEL: The best (paranoid) CVSS is 'AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N';*CWE-200;CWE-203;CWE-497;Other CVSS 'AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:N';BEST CVSS score: '5.5';DESCR 'The cls_flow classifier can expose folded kernel pointer values when packet header fields are missing and addr_fold is used for fallback keys. In map mode, userspace can control mask, xor, rshift, addend, and divisor, then observe the resulting classid through class statistics. This can allow recovery of a 32-bit folded value derived from skb sk, skb_dst(), or skb_nfct(). For the CVSS the PR:L means a local user or process must be able to configure tc classifiers, commonly through CAP_NET_ADMIN in a user or network namespace. The issue is not directly network reachable because packet traffic alone is not enough without control over the classifier configuration and statistics observation. Impact is information disclosure that may weaken kernel pointer hiding or help another exploit chain, with no direct evidence of memory corruption, denial of service, or privilege escalation by itself.';YES REQUIRES MANUAL CHECK; ,and ActionableScore result is Actionable Moderate at minimum / manual-review candidate (with actual score 5) YES REMOTE SIMPLEFIX NETWORK LINUS PACKET LOWERED_FROM_HIGH_BASED_ON_GUESSCVSS DECREASED_TO_MODERATEREG_BASED_ON_FALSEPOSCHECKOFKP NO NO checked ====================================================================== ACTIONABLESCORE ANALYSIS ====================================================================== ActionableScore=5 ActionableScoreLower=4 ## 1. ActionableScore * Conservative score: 4 * Paranoid score: 5 * Final recommended bucket: **Actionable Moderate at minimum / manual-review candidate**:: ## 2. Signal breakdown Conservative signals: * Local unprivileged trigger: +1. The commit explicitly mentions a tc classifier in a user/network namespace, so practical reachability may exist for a local user when unprivileged user namespaces and network namespace setup are available. * Local high-control netlink/classifier configuration: +1. Userspace controls `mask`, `xor`, `rshift`, `addend`, and `divisor`, and can observe classid-derived results via class statistics. * Confidentiality impact plausible: +1. The issue leaks a 32-bit value derived from kernel pointers such as `skb->sk`, `skb_dst()`, or `skb_nfct()`. * Cross-boundary isolation or hardening bypass concern: +1. A namespace-local classifier can expose host-kernel pointer-derived information, which may weaken kernel pointer hiding or KASLR assumptions. Paranoid additional signal: * Broad/common networking subsystem exposure: +1. Traffic control and net/sched infrastructure are broadly present in Linux kernels, even though this specific `cls_flow` configuration is not necessarily default. Not awarded: * No generic memory corruption. The patch replaces XOR pointer folding with keyed siphash and does not show UAF, OOB write, type confusion, refcount misuse, or arbitrary write. * No privilege escalation bonus. The leak may assist another exploit chain, but the patch does not demonstrate a direct LPE primitive. * No reliable DoS bonus. The issue is information disclosure, not crash or resource exhaustion. * No remote-reachable bonus. Packet traffic alone is insufficient without control over classifier configuration and statistics observation. ## 3. Reachability analysis The likely trigger is a local user or process that can configure `tc` flow classifiers and read class statistics. In typical host deployments this often requires `CAP_NET_ADMIN`, but the commit explicitly calls out user/network namespace use, which can reduce the practical privilege requirement on systems allowing unprivileged user namespaces. The path is not directly reachable from the network. Remote traffic may provide packets for classification, but the attacker must also control the classifier parameters and observe the resulting classid/statistics. The affected code is in net/sched rather than a default packet parser, so exposure depends on whether `cls_flow` is available and configurable by less-trusted users. Call-site confidence: medium-high. The patch and commit describe both the leaking helper `addr_fold()` and the observable classifier behavior, but the full classifier call graph is not included. ## 4. Severity interpretation This behaves more like an actionable Moderate information disclosure than an Important memory-corruption issue. The realistic impact is kernel pointer-derived information leakage that may weaken KASLR or support a separate exploit chain. The theoretical concern is higher in namespace-enabled environments because reduced-privilege users may be able to configure the classifier and recover pointer-derived values. However, there is no evidence in the patch of direct memory corruption, arbitrary read/write, kernel crash, or standalone privilege escalation. ## 5. One-sentence report phrase A local user able to configure `cls_flow` tc classifiers, including via a user/network namespace on permissive systems, can recover 32-bit folded values derived from kernel pointers through class statistics, weakening kernel pointer hiding but not directly providing memory corruption or privilege escalation. ## 6. Manual review recommendation MANUAL CHECK REQUIRED This should not be auto-closed because it is a kernel pointer-derived information leak reachable through namespace-sensitive networking control paths, and its practical severity depends heavily on user namespace policy, `CAP_NET_ADMIN` delegation, and whether the leaked 32-bit folded values are useful for bypassing kernel address randomization in the target environment. ====================================================================== UPSTREAM PATCH SUMMARY ====================================================================== Patch: net/sched: cls_flow: Dont expose folded kernel pointers [ Upstream Commit: 19f2ecf8ea564562c7e7a919cf38068dd9aa1c96 Upstream URL: https://git.kernel.org/pub/scm/linux/kernel/git/stable/linux.git/commit/?id=19f2ecf8ea564562c7e7a919cf38068dd9aa1c96 Changed files: net/sched/cls_flow.c net/inet_sock.h net/pkt_cls.h net/ip.h net/route.h net/flow_dissector.h 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=19f2ecf8ea564562c7e7a919cf38068dd9aa1c96 ====================================================================== DETAILED REPORT METHODOLOGY ====================================================================== The original Linux kernel CVE announcement for CVE-2026-74290 can be found here: https://lore.kernel.org/linux-cve-announce/?q=CVE-2026-74290 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:L/UI:N/S:U/C:L/I:N/A:N The Best / paranoid CVSS vector: AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N The Best / paranoid CVSS score: 5.5 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: 4 Paranoid ActionableScore: 5 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: MODERATE KPANIC detected for this report: NO Published priority for this report (same as in Subject): MODERATE 7.0 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).