From mboxrd@z Thu Jan 1 00:00:00 1970 From: AL-KERNEL To: kernel-cve@kernelcve.org Subject: [CVE-2026-98893][MODERATE REGULAR] firmware: arm_scmi: Validate SENSOR_UPDATE payload size [ Upstream Date: Mon, 26 Oct 2026 15:09:27 -0400 Message-ID: MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit X-AL-KERNEL-CVE: CVE-2026-98893 X-AL-KERNEL-Priority: MODERATE REGULAR X-AL-KERNEL-Severity: MODERATE REGULAR X-AL-KERNEL-Base-Severity: MODERATE X-AL-KERNEL-KPANIC: NO X-AL-KERNEL-ActionableScore: 3 X-AL-KERNEL-ActionableScore-Lower: unknown X-AL-KERNEL-Commit: e543d60f966a5f5c92298720c2fd1810f85a6be3 List-Id: CVE: CVE-2026-98893 Priority: MODERATE REGULAR AL-KERNEL base severity: MODERATE KPANIC flag: NO Patch: firmware: arm_scmi: Validate SENSOR_UPDATE payload size [ Upstream Commit: e543d60f966a5f5c92298720c2fd1810f85a6be3 Upstream patch: https://git.kernel.org/pub/scm/linux/kernel/git/stable/linux.git/commit/?id=e543d60f966a5f5c92298720c2fd1810f85a6be3 Original CVE announcement: https://lore.kernel.org/linux-cve-announce/?q=CVE-2026-98893 Analysis date: Mon, 26 Oct 2026 15:09:27 -0400 ActionableScore: 3 ActionableScore lower bound: unknown Actionable bucket: Borderline / manual review recommended Manual review required: YES Summary: A truncated SCMI SENSOR_UPDATE can cause a firmware-controlled out-of-bounds payload read and possible kernel fault, without a demonstrated write, disclosure, or protected-state impact. ====================================================================== ABOUT THIS REPORT ====================================================================== The original Linux kernel CVE announcement for CVE-2026-98893 is available here: https://lore.kernel.org/linux-cve-announce/?q=CVE-2026-98893 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 REGULAR 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-2026-98893 MODERATE https://www.kernelcve.org/list/?q=CVE-2026-98893 CHECK WITH IMPACT FROM ORIG NN LOW | AEGIS IMPACT MODERATE_KPANIC AEGIS_AS=0 LEGACY=MODERATE RESULT=DIFF (final Legacy and Aegis differ; FINAL: MODERATE, Aegis: MODERATE_KPANIC) Maybe valid. Check manually. Hints by AL-KERNEL: The best (paranoid) CVSS is 'AV:A/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:H';CWE-125;*CWE-20;CWE-130;Other CVSS 'AV:A/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:L';BEST CVSS score: '7.6';DESCR 'A truncated SCMI SENSOR_UPDATE notification can make the sensor event parser read beyond the received payload because the reading count comes from the sensor description while the actual variable array length was not validated. The concrete primitive is an out of bounds read from provider controlled payload memory. It may inject invalid sensor values into kernel consumers and can potentially fault the kernel at a buffer boundary, but the diff does not establish an out of bounds write or use after free. For the CVSS the PR:N paranoid interpretation applies when malicious SCMI firmware or a virtual backend can submit notifications without victim credentials. Practical exploitation still requires control of the trusted SCMI provider and is not directly network reachable. Automated impact decision path. The original SimpleNet classifier selected LOW. The primary LLM estimated paranoid CVSS 7.6 and the production ActionableScore returned 3 with recommendation Borderline / manual review recommended. The production rules then evaluated CVSS thresholds and ActionableScore thresholds. Recorded rule transitions were CVSS and initial triage stage LOW to MODERATE_KPANIC because the manual review requirement was applied. ActionableScore thresholds stage MODERATE_KPANIC to MODERATE because the ActionableScore threshold rule was applied. The legacy KP specialist has no review artifact for this run. The legacy FD or DH downgrade specialist has no review artifact for this run. Exact triggered rule markers were INCREASED_FROM_LOW_BASED_ON_REQUIREMANUALCHECK and DECREASED_TO_MODERATEREG_BASED_ON_ACTIONABLESCORELESSTHAN4 and V41_INHERITED_KPANIC_PROMOTION_BLOCKED and MANUAL_REVIEW_REQUIRED. The independent weaker Aegis shadow evaluated CVSS 0.0 and ActionableScore 0 with primitive class CLASS_C and manual review REQUIRED. Its independently reconciled impact was MODERATE_KPANIC. The models disagreed but the aggregation rules retained the production result. The final reported impact is MODERATE.';YES REQUIRES MANUAL CHECK; ,and ActionableScore result is Borderline / manual review recommended (with actual score 3) MAYBE SIMPLEFIX LINUS INCREASED_FROM_LOW_BASED_ON_REQUIREMANUALCHECK DECREASED_TO_MODERATEREG_BASED_ON_ACTIONABLESCORELESSTHAN4 V41_INHERITED_KPANIC_PROMOTION_BLOCKED MANUAL_REVIEW_REQUIRED - - checked ====================================================================== ACTIONABLESCORE ANALYSIS ====================================================================== ActionableScore=3 PrimitiveClass=CLASS_C RealUAF=NO HostAdminRequired=UNKNOWN NamespaceScopedPrivilege=UNKNOWN ImportantCandidate=NO ManualReview=RECOMMENDED AutoDowngradeAllowed=YES RequiresHostUID0=UNKNOWN AuthorizationDecisionBypass=NO ProtectedResourceImpact=NONE B4PendingReview=NO B4PendingConfirmed=NO 1. ActionableScore * Raw base score: 3. * Conservative score: 3; no floor or cap applied. * Raw paranoid score: 3. * Paranoid score: 3; unsupported downstream effects add no points. * Final recommended bucket: **Borderline / manual review recommended**:: 2. Signal breakdown * +1 weak/indirect corruption concern: the parser reads `p->readings[i]` beyond a truncated provider-supplied payload. This is a confirmed out-of-bounds read, not a write. * +1 firmware-mediated external influence: an SCMI firmware or virtual backend controls notification payload length and contents. * +1 plausible kernel crash/DoS: crossing the payload allocation boundary can fault the kernel, although no guaranteed panic is shown. * No confidentiality point: no out-of-bounds bytes are shown escaping to an attacker. * No integrity point: invalid readings can enter the report, but no protected downstream state-changing consumer is identified. * No B5-R: there is no retry-accumulated index and no heap out-of-bounds write. * No UAF, arbitrary write, controlled reclaim, authorization bypass, or remote-network reachability is shown. 3. Reachability analysis The direct input actor is the SCMI provider, such as platform firmware or a virtual backend—not an ordinary network peer. The evidence does not establish whether a local user, guest, host administrator, or only compromised firmware can control that provider. Consequently, complete-trigger privilege, UID 0 requirements, namespace capability scope, and prior provisioning requirements remain unknown. No race or retry sequence is required. 4. Primitive and severity reading The exact primitive is a variable-array out-of-bounds read caused by trusting the sensor description’s reading count without validating `payld_sz`. Parsed garbage may populate a sensor report, and a boundary crossing may fault. The patch does not identify a later consumer that turns the invalid reading into protected-state corruption, disclosure, or a security-boundary crossing. This is therefore CLASS_C rather than a write-capable or lifetime CLASS_B primitive. ImportantCandidate is NO, and auto-downgrade remains allowed, while manual review is recommended to inspect downstream sensor-event consumers. 5. One-sentence report phrase A truncated SCMI SENSOR_UPDATE can cause a firmware-controlled out-of-bounds payload read and possible kernel fault, without a demonstrated write, disclosure, or protected-state impact. 6. Manual review advice MANUAL CHECK RECOMMENDED Review downstream consumers of parsed sensor reports and the deployed SCMI provider trust boundary. 7. Call-site confidence Call-site confidence: medium ====================================================================== UPSTREAM PATCH SUMMARY ====================================================================== Patch: firmware: arm_scmi: Validate SENSOR_UPDATE payload size [ Upstream Commit: e543d60f966a5f5c92298720c2fd1810f85a6be3 Upstream URL: https://git.kernel.org/pub/scm/linux/kernel/git/stable/linux.git/commit/?id=e543d60f966a5f5c92298720c2fd1810f85a6be3 Changed files: drivers/firmware/arm_scmi/sensors.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=e543d60f966a5f5c92298720c2fd1810f85a6be3 ====================================================================== DETAILED REPORT METHODOLOGY ====================================================================== The original Linux kernel CVE announcement for CVE-2026-98893 can be found here: https://lore.kernel.org/linux-cve-announce/?q=CVE-2026-98893 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:A/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:L The Best / paranoid CVSS vector: AV:A/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:H The Best / paranoid CVSS score: 7.6 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: unknown Paranoid ActionableScore: 3 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 REGULAR 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).