From mboxrd@z Thu Jan 1 00:00:00 1970 From: AL-KERNEL To: kernel-cve@kernelcve.org Subject: [CVE-2026-68272][MODERATE REGULAR] drm/amdgpu: validate CP_GFX_SHADOW chunk size in CS pass1 Date: Mon, 10 Aug 2026 15:34:55 -0400 Message-ID: MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit X-AL-KERNEL-CVE: CVE-2026-68272 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: 3f190956404da55560056ce20606010e18bc059c List-Id: CVE: CVE-2026-68272 Priority: MODERATE REGULAR AL-KERNEL base severity: MODERATE KPANIC flag: NO Patch: drm/amdgpu: validate CP_GFX_SHADOW chunk size in CS pass1 Commit: 3f190956404da55560056ce20606010e18bc059c Upstream patch: https://git.kernel.org/pub/scm/linux/kernel/git/stable/linux.git/commit/?id=3f190956404da55560056ce20606010e18bc059c Original CVE announcement: https://lore.kernel.org/linux-cve-announce/?q=CVE-2026-68272 Analysis date: Mon, 10 Aug 2026 15:34:55 -0400 ActionableScore: 3 ActionableScore lower bound: unknown Actionable bucket: Borderline, manual review recommended Manual review required: YES Summary: A local user with AMDGPU render-node access can submit an undersized CP_GFX_SHADOW CS chunk that reaches `amdgpu_cs_p2_shadow()` with `ZERO_SIZE_PTR` command data, causing a NULL-pointer style kernel fault and denial of service. ====================================================================== ABOUT THIS REPORT ====================================================================== The original Linux kernel CVE announcement for CVE-2026-68272 is available here: https://lore.kernel.org/linux-cve-announce/?q=CVE-2026-68272 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-2026-68272 MODERATE CHECK WITH IMPACT FROM ORIG NN LOW 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:N/A:H';*CWE-20;**CWE-476;CWE-754;BEST CVSS score: '5.5';DESCR 'An undersized AMDGPU_CHUNK_ID_CP_GFX_SHADOW chunk can reach amdgpu_cs_p2_shadow after vmemdup_array_user returns ZERO_SIZE_PTR for a zero length allocation. The pass2 code then treats chunk kdata as struct drm_amdgpu_cs_chunk_cp_gfx_shadow and reads the flags field, causing a kernel fault and local denial of service. For the CVSS the PR:L is used because a local process needs access to the amdgpu render node or the render group, but full administrative privileges are not required. The issue is not network reachable and is triggered through the local DRM CS ioctl path. Impact is kernel crash only. The patch context supports a NULL pointer style dereference rather than UAF, OOB write, or a controlled memory corruption primitive.';YES REQUIRES MANUAL CHECK; ,and ActionableScore result is Borderline, manual review recommended (with actual score 3) SKIP CVE-2026-68272 UNKNOWN SKIP No affected files built, so skip this CVE NO - - unknown MAYBE SIMPLEFIX HARDWARE INCREASED_FROM_LOW_BASED_ON_REQUIREMANUALCHECK DECREASED_TO_MODERATEREG_BASED_ON_ACTIONABLESCORELESSTHAN5 - - checked ====================================================================== ACTIONABLESCORE ANALYSIS ====================================================================== ActionableScore=3 ## 1. ActionableScore * Conservative score: 3 * Paranoid score: 3 * Final recommended bucket: **Borderline, manual review recommended**:: ## 2. Signal breakdown Triggered signals: * Local unprivileged trigger: +1 The commit explicitly says the issue is reachable by an unprivileged process in the render group through the local AMDGPU CS ioctl path. * Reliable kernel crash / strong DoS: +1 A zero-length CP_GFX_SHADOW chunk can make `vmemdup_array_user()` return `ZERO_SIZE_PTR`, which is later dereferenced as `struct drm_amdgpu_cs_chunk_cp_gfx_shadow`, causing a kernel fault. * Broad/default/common subsystem or broadly deployed exposure: +1 AMDGPU render nodes are commonly exposed to local desktop or compute users on systems with AMD GPUs, although this is still hardware and device-access dependent. Not triggered: * Generic memory corruption: +0 The demonstrated primitive is a NULL/ZERO_SIZE_PTR dereference, not UAF, double free, OOB write, type confusion, or controlled overwrite. * Privilege escalation plausible: +0 No reclaim, object replacement, callback control, write primitive, or type confusion is shown. * Confidentiality impact plausible: +0 No read-back or information disclosure path is indicated. * Integrity impact plausible: +0 No attacker-controlled write or policy bypass is indicated. * Remote reachable: +0 The affected path is a local DRM ioctl, not a network path. ## 3. Reachability analysis A local process with access to the AMDGPU render node, typically through membership in the render group or equivalent device ACLs, can submit the malformed CS chunk. Full root privileges are not required, so this is not a PR:H style issue in practical triage terms. Namespaces and containers may matter if the DRM render node is passed into a container. In that case, a containerized or reduced-privilege workload with GPU access could potentially trigger the same host kernel bug. The path is not network reachable and requires an AMDGPU device with the affected CS ioctl support exposed. Call-site confidence: high. The commit describes the exact path from `amdgpu_cs_pass1()` to `amdgpu_cs_p2_shadow()` and identifies the dereference of `chunk->kdata`. ## 4. Severity interpretation This behaves like an actionable local Moderate issue, not an Important-class vulnerability. The realistic impact is local denial of service through a kernel fault from a malformed GPU command submission. The theoretical memory-corruption potential is low because the patch context supports a deterministic invalid pointer dereference of `ZERO_SIZE_PTR`. It does not show UAF, stale object reuse, writable corruption, object confusion, or a path toward privilege escalation. ## 5. One-sentence report phrase A local user with AMDGPU render-node access can submit an undersized CP_GFX_SHADOW CS chunk that reaches `amdgpu_cs_p2_shadow()` with `ZERO_SIZE_PTR` command data, causing a NULL-pointer style kernel fault and denial of service. ## 6. Manual review recommendation MANUAL CHECK RECOMMENDED This should not be auto-closed purely as low-risk because it is a local unprivileged kernel crash through a commonly exposed GPU ioctl. However, no evidence supports memory corruption beyond invalid dereference or privilege escalation, so it does not look like a Strong Important candidate. ====================================================================== UPSTREAM PATCH SUMMARY ====================================================================== Patch: drm/amdgpu: validate CP_GFX_SHADOW chunk size in CS pass1 Commit: 3f190956404da55560056ce20606010e18bc059c Upstream URL: https://git.kernel.org/pub/scm/linux/kernel/git/stable/linux.git/commit/?id=3f190956404da55560056ce20606010e18bc059c Commit description: Add a minimum-length check for the AMDGPU_CHUNK_ID_CP_GFX_SHADOW chunk in amdgpu_cs_pass1(), matching the gate already present for the IB, FENCE and BO_HANDLES chunk types. The CP_GFX_SHADOW case previously shared a bare break with the dependency and syncobj chunk types, which do not dereference a fixed-size struct. When userspace submits this chunk with length_dw == 0, vmemdup_array_user() is called with size 0 and returns ZERO_SIZE_PTR, which passes the IS_ERR() check. amdgpu_cs_p2_shadow() then dereferences chunk->kdata as a struct drm_amdgpu_cs_chunk_cp_gfx_shadow (reading shadow->flags), faulting on the ZERO_SIZE_PTR and causing a NULL-pointer dereference. This is reachable by an unprivileged process in the render group. Reject undersized chunks with -EINVAL during pass1 so the bad submission is rejected before pass2 ever dereferences the data. Fixes: ac92870 ("drm/amdgpu: add gfx shadow CS IOCTL support") Reviewed-by: Alex Deucher Signed-off-by: Mario Limonciello Signed-off-by: Alex Deucher (cherry picked from commit 7f61b2e ) Cc: stable@vger.kernel.org Signed-off-by: Greg Kroah-Hartman Changed files: drivers/gpu/drm/amd/amdgpu/amdgpu_cs.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=3f190956404da55560056ce20606010e18bc059c ====================================================================== DETAILED REPORT METHODOLOGY ====================================================================== The original Linux kernel CVE announcement for CVE-2026-68272 can be found here: https://lore.kernel.org/linux-cve-announce/?q=CVE-2026-68272 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: Not available The Best / paranoid CVSS vector: AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H 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: 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).