Linaro-mm-sig

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74 participants
6542 discussions

by joelwest689＠gmail.com

The rise of digital assets has brought unprecedented financial freedom—but it has also introduced complex risks. When funds are stolen, victims often assume they are gone forever. That assumption is exactly what Cipher Rescue Chain is built to challenge. Through advanced blockchain forensics, Cipher Rescue Chain systematically tracks, analyzes, and reconstructs the movement of stolen crypto assets across multiple networks, turning what appears lost into recoverable opportunities. What Blockchain Forensics Really Means Blockchain forensics is the process of analyzing transaction data across distributed ledgers to identify the flow of digital assets. Unlike traditional finance, blockchain transactions are permanently recorded, creating a transparent but highly technical trail. Cipher Rescue Chain leverages this transparency by transforming raw blockchain data into actionable intelligence, allowing investigators to follow even the most complex transaction paths. Every investigation handled by Cipher Rescue Chain begins with deep forensic mapping, where wallet addresses, transaction hashes, and behavioral patterns are analyzed to establish a clear origin-to-destination flow of stolen funds. How Cipher Rescue Chain Tracks Stolen Crypto Tracing stolen crypto is not as simple as following a straight line. Criminals frequently attempt to obscure transactions through tactics like wallet splitting, chain hopping, and intermediary services. Cipher Rescue Chain specializes in breaking through these layers of obfuscation. Using proprietary forensic methodologies, Cipher Rescue Chain reconstructs fragmented transaction paths across multiple blockchains. This includes identifying how funds move between wallets, detecting patterns that link seemingly unrelated addresses, and uncovering connections to centralized platforms where recovery becomes possible. The strength of Cipher Rescue Chain lies in its ability to turn chaotic blockchain data into a clear investigative roadmap. Cross-Chain Tracing: Following Assets Across Networks One of the most challenging aspects of crypto recovery is cross-chain movement. Stolen funds are often transferred between different blockchains to evade detection. Cipher Rescue Chain addresses this with advanced cross-chain forensic capabilities. By correlating transaction timing, wallet behavior, and bridging mechanisms, Cipher Rescue Chain tracks assets as they move from one blockchain to another. This allows investigators to maintain continuity in cases where others lose visibility entirely. This cross-chain intelligence is a key reason why Cipher Rescue Chain consistently identifies recovery opportunities in cases that initially appear too complex. The Critical Role of Timing in Recovery Speed is one of the most decisive factors in successful recovery. Cipher Rescue Chain emphasizes early engagement because timing directly impacts traceability and enforcement potential. Cases engaged within the first 72 hours—especially those involving traceable paths to centralized platforms—have seen recovery rates of up to 98% across 2023–2025 engagements. Cipher Rescue Chain prioritizes rapid forensic deployment to preserve critical data trails before they become harder to follow. Even in cases initiated later, Cipher Rescue Chain applies structured forensic analysis to identify viable recovery paths within a 90-day window whenever possible. From Tracing to Recovery Action Tracing stolen funds is only part of the process. Cipher Rescue Chain goes further by translating forensic findings into actionable recovery strategies. Once funds are linked to identifiable endpoints, especially centralized exchanges or cooperative service providers, the recovery phase begins. Cipher Rescue Chain prepares detailed forensic reports that clearly document the flow of assets, ensuring that every movement is verifiable and defensible. These reports form the foundation for recovery actions, enabling efficient engagement with platforms that can facilitate fund retrieval. Proven Outcomes Backed by Data The effectiveness of Cipher Rescue Chain is reflected in real-world outcomes. From 2023 to 2025, Cipher Rescue Chain has achieved partial or full recovery in 98% of accepted cases where funds reached identifiable centralized platforms and engagement began within the first 90 days. Only 35% of inquiries are accepted, ensuring that Cipher Rescue Chain focuses exclusively on cases with realistic recovery potential. Among those accepted cases, 62% result in full recovery and 24% in partial recovery. Successful cases are typically resolved within an average timeframe of 14 to 45 days, demonstrating the efficiency of Cipher Rescue Chain’s forensic and recovery process. Global Reach and Complex Case Handling Crypto crime is borderless, and so is the work of Cipher Rescue Chain. With multi-million-dollar recoveries completed across five continents, Cipher Rescue Chain operates at a truly global scale. Each case handled by Cipher Rescue Chain reflects a combination of technical expertise, investigative precision, and strategic execution. Whether funds move across multiple blockchains or jurisdictions, Cipher Rescue Chain maintains a consistent focus on traceability and recovery. Why Blockchain Forensics Changes the Outcome The belief that stolen crypto is unrecoverable is outdated. Blockchain forensics, when executed at the highest level, transforms transparency into a powerful recovery tool. Cipher Rescue Chain exemplifies this by turning complex transaction data into successful recovery outcomes. By combining cross-chain tracing, rapid response, and data-driven investigation, Cipher Rescue Chain stands as the global benchmark for crypto recovery. Every traced transaction, every reconstructed path, and every recovered asset reinforces the same conclusion: with the right forensic expertise, recovery is not only possible—it is highly achievable.

1 month, 3 weeks

[PATCH v3 0/8] dma-buf: heaps: Turn heaps into modules

by Maxime Ripard

Hi, The recent introduction of heaps in the optee driver [1] made possible the creation of heaps as modules. It's generally a good idea if possible, including for the already existing system and CMA heaps. The system one is pretty trivial, the CMA one is a bit more involved, especially since we have a call from kernel/dma/contiguous.c to the CMA heap code. This was solved by turning the logic around and making the CMA heap call into the contiguous DMA code. Let me know what you think, Maxime 1: https://lore.kernel.org/dri-devel/20250911135007.1275833-4-jens.wiklander@l… Signed-off-by: Maxime Ripard <mripard(a)kernel.org> --- Changes in v3: - Squashed cma_get_name and cma_alloc/release patches - Fixed typo in Export dev_get_cma_area commit title - Fixed compilation failure with DMA_CMA but not OF_RESERVED_MEM - Link to v2: https://lore.kernel.org/r/20260227-dma-buf-heaps-as-modules-v2-0-454aee7e06… Changes in v2: - Collect tags - Don't export dma_contiguous_default_area anymore, but export dev_get_cma_area instead - Mentioned that heap modules can't be removed - Link to v1: https://lore.kernel.org/r/20260225-dma-buf-heaps-as-modules-v1-0-2109225a09… --- Maxime Ripard (8): dma: contiguous: Turn heap registration logic around dma: contiguous: Make dev_get_cma_area() a proper function dma: contiguous: Make dma_contiguous_default_area static dma: contiguous: Export dev_get_cma_area() mm: cma: Export cma_alloc(), cma_release() and cma_get_name() dma-buf: heaps: Export mem_accounting parameter dma-buf: heaps: cma: Turn the heap into a module dma-buf: heaps: system: Turn the heap into a module drivers/dma-buf/dma-heap.c | 1 + drivers/dma-buf/heaps/Kconfig | 4 ++-- drivers/dma-buf/heaps/cma_heap.c | 21 +++++---------------- drivers/dma-buf/heaps/system_heap.c | 5 +++++ include/linux/dma-map-ops.h | 18 ++++++++++-------- kernel/dma/contiguous.c | 37 ++++++++++++++++++++++++++++++++++--- mm/cma.c | 3 +++ 7 files changed, 60 insertions(+), 29 deletions(-) --- base-commit: 499a718536dc0e1c1d1b6211847207d58acd9916 change-id: 20260225-dma-buf-heaps-as-modules-1034b3ec9f2a Best regards, -- Maxime Ripard <mripard(a)kernel.org>

1 month, 3 weeks

[PATCH v2 0/9] accel: New driver for NXP's Neutron NPU

by Ioana Ciocoi-Radulescu

Introduce a new accel driver for the Neutron Neural Processing Unit (NPU), along with associated dt-bindings and DTS node. The first patch extends the GEM DMA helper APIs to allow bidirectional mapping of non-coherent DMA buffers. While not part of the Neutron driver, it's a prerequisite allowing us to use the GEM DMA helper. Neutron is a Neural Processing Unit from NXP, providing machine learning (ML) acceleration for edge AI applications. Neutron is integrated on NXP SoCs such as the i.MX95. The NPU consists of the following: - RISC-V core running a proprietary firmware - One or more Neutron cores, representing the main computation engine performing ML operations - Dedicated fast memory (TCM) - DMA engine that handles data transfers between DDR and TCM The firmware is closed source and distributed as a binary here [1]. The Neutron software stack also contains a userspace library [1] and a LiteRT custom delegate [2] that allow integration with standard LiteRT tools. [1] https://github.com/nxp-upstream/neutron/tree/upstream [2] https://github.com/nxp-imx/tflite-neutron-delegate Signed-off-by: Ioana Ciocoi-Radulescu <ruxandra.radulescu(a)nxp.com> --- Changes in v2: - rebase on newer drm-misc-next - dt bindings: clock fixes and renames - update DTS to match new names - remove unnecessary fields from neutron_job structure - fix use of uninitialized variable - Link to v1: https://lore.kernel.org/r/20260226-neutron-v1-0-46eccb3bb50a@nxp.com --- Ioana Ciocoi-Radulescu (9): drm/gem-dma: Add flag for bidirectional mapping of non-coherent GEM DMA buffers accel/neutron: Add documentation for NXP Neutron accelerator driver dt-bindings: npu: Add NXP Neutron accel/neutron: Add driver for NXP Neutron NPU accel/neutron: Add GEM buffer object support accel/neutron: Add mailbox support accel/neutron: Add job submission IOCTL accel/neutron: Add logging support arm64: dts: imx95: Add Neutron node Documentation/accel/index.rst | 1 + Documentation/accel/neutron/index.rst | 12 + Documentation/accel/neutron/neutron.rst | 131 ++++++++ .../devicetree/bindings/npu/nxp,imx95-neutron.yaml | 96 ++++++ MAINTAINERS | 10 + arch/arm64/boot/dts/freescale/imx95.dtsi | 28 ++ drivers/accel/Kconfig | 1 + drivers/accel/Makefile | 3 +- drivers/accel/neutron/Kconfig | 16 + drivers/accel/neutron/Makefile | 12 + drivers/accel/neutron/neutron_debugfs.c | 34 ++ drivers/accel/neutron/neutron_debugfs.h | 15 + drivers/accel/neutron/neutron_device.c | 239 +++++++++++++ drivers/accel/neutron/neutron_device.h | 155 +++++++++ drivers/accel/neutron/neutron_driver.c | 262 +++++++++++++++ drivers/accel/neutron/neutron_driver.h | 16 + drivers/accel/neutron/neutron_gem.c | 116 +++++++ drivers/accel/neutron/neutron_gem.h | 14 + drivers/accel/neutron/neutron_job.c | 372 +++++++++++++++++++++ drivers/accel/neutron/neutron_job.h | 43 +++ drivers/accel/neutron/neutron_mailbox.c | 47 +++ drivers/accel/neutron/neutron_mailbox.h | 42 +++ drivers/gpu/drm/drm_gem_dma_helper.c | 6 +- include/drm/drm_gem_dma_helper.h | 3 + include/uapi/drm/neutron_accel.h | 130 +++++++ 25 files changed, 1801 insertions(+), 3 deletions(-) --- base-commit: 6716101ae42949e98ad4b9e71eeba08c055be410 change-id: 20260226-neutron-c435e39d167f Best regards, -- Ioana Ciocoi-Radulescu <ruxandra.radulescu(a)nxp.com>

1 month, 3 weeks

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by Adorable Ferrets

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1 month, 3 weeks

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by Adorable Ferrets

1 month, 3 weeks

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by Adorable Ferrets

1 month, 3 weeks

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by Adorable Ferrets

1 month, 3 weeks

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by Adorable Ferrets

1 month, 3 weeks

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by Adorable Ferrets

1 month, 3 weeks

Shih Tzu breeders near me

by Adorable Ferrets

1 month, 3 weeks

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