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An Open-Source End-to-End FHE Implementation for Privacy-Preserving Llama 3 8B Inference
Odin runs Llama-3-8B fully homomorphic encrypted inference on a single H100 in 366 seconds, a 4.51x speedup over THOR.
Odin is an open-source end-to-end GPU CKKS implementation for privacy-preserving Llama-3-8B inference that co-designs ciphertext packing with model execution. A feature-major cross-layer layout unifies residual connections and layer interfaces, while transient intra-operator layouts serve linear projections and attention, avoiding intermediate repacking of QK^T softmax outputs. Minimax polynomial approximation with input-range control reduces polynomial degree and multiplicative depth for nonlinear ops. With 128-token input, Odin evaluates all 32 Transformer layers on one NVIDIA H100 80 GB in 366.4 s using 58.9 GiB peak memory, versus 1651.9 s for the THOR baseline, a 4.51x speedup.
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MacOS 27 - First Boot, (Tue, Sep 15th)
SANS ISC documents the expected network traffic macOS 27 'Golden Gate' generates on first boot to help defenders baseline their networks.
Johannes Ullrich of SANS Internet Storm Center captured roughly 300 packets from a macOS 27 'Golden Gate' system before user login, covering DHCP, IPv6 duplicate address discovery, DNS, and TCP behavior. macOS 27 resolves hostnames like albert.apple.com (device activation, certificate-pinned), push messaging hosts, and ipv4only.arpa for NAT64 networks. The OS still uses a TCP window scale of 6, ECN, and random timestamps, with only four TCP connections observed during boot. The analysis provides a reference baseline for security teams monitoring Apple endpoints.
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OptiPrime: Optimizing Private Inference through Protocol-Hardware Co-design
OptiPrime co-designs HE-MPC protocols with hardware acceleration to remove network communication bottlenecks in private DNN inference, beating Cheetah by up to 5.7x.
OptiPrime is a protocol-hardware co-optimization framework for private deep neural network inference based on hybrid homomorphic encryption (HE) and multi-party computation (MPC). It introduces a novel HE protocol for convolutions that reduces the number of transmitted output ciphertexts, addressing the network bottleneck that limits gains from commercial HE accelerators. A lightweight compression system reduces weight plaintext memory traffic by 10x, while a specialized dataflow maximizes on-chip reuse of intermediate ciphertexts. Experiments show up to 5.7x speedup over the Cheetah baseline on CPUs and 4.2x with an accelerator.
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Risks in IoT Supply Chain
Unit 42 analyzes multilayer IoT supply chain risks across hardware, firmware, and software, citing counterfeit Cisco switches and OpenWrt attacks.
Unit 42 examines weaknesses in the IoT supply chain ecosystem across hardware, firmware, operation, and vulnerability layers, noting that 89% of IT decision-makers reported IoT device growth and IDC forecast 41.6 billion connected IoT devices by 2025. Examples include counterfeit Cisco Catalyst 2960-X switches with possible backdoor access (F-Secure, July 2020), a March 2020 OpenWrt flaw enabling malicious update impersonation, and threat actor interest in TeamViewer remote support software. The report stresses that untracked third-party components and missing device inventories make it hard to assess vulnerability impact across vendors.
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The Gopher in the Room: Analysis of GoLang Malware in the Wild
Unit 42 analysis of 10,700 Go-compiled malware samples shows steady growth in the wild, with 92% targeting Windows and top families including Veil, GoBot2, and HERCULES.
Unit 42 collected roughly 10,700 unique Go-compiled malware samples and found that Go usage by malware developers has steadily risen in recent months. About 92% of samples targeted Windows and 75% were attributed to known families, led by Veil, GoBot2, and HERCULES. The most prevalent groupings were penetration testing tools, remote access Trojans, and backdoors. Statically linked Go binaries average 4.65MB, which can complicate phishing delivery but sometimes causes antivirus products to skip or fail scanning.
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Rare Not Random Using Token Efficiency for Secrets Scanning
Researcher proposes token efficiency (string length divided by BPE token count) as a better post-regex filter than entropy for secrets scanning, validated on CredData.
The post explores whether Byte-Pair Encoding tokenization can replace Shannon entropy as the primary filter for candidate secrets captured by regex in tools like Gitleaks. It defines 'token efficiency' as string length divided by token count under the cl100k_base tokenizer; secret-like strings such as GitHub tokens tokenize into many small tokens and score low, while natural text scores high. Evaluating labeled secrets from the CredData dataset shows a usable separation, with roughly 2.5 suggested as a minimum cutoff versus Gitleaks' 3.5 entropy threshold. The technique is positioned as a post-regex filtering step rather than a standalone detector.
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Building a Linux GPU Driver for the M4 Mac Mini in One Month
Two developers built a fully OpenGL ES 3.0 compliant Linux GPU driver for the M4 Mac Mini in one month via clean-room reverse engineering.
Niklas and the author reverse engineered Apple's AGX GPU firmware ABI and user-space components in about a month, a process that normally takes years, producing an OpenGL ES 3.0 conformant driver fast enough to run Minecraft at 200fps on an M4 Mac Mini. The work was done transparently using hypervisor traces without examining Apple binaries, following clean-room practices, and included a custom shader compiler, command stream builder, and a full Linux kernel driver for the firmware ABI. The A18 Pro firmware ABI proved significantly more complex than the M1's, with 1.5x as many structs and twice as many pointers. All experiments and provenance evidence were published in public agx-re repositories.
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Testing race conditions with memory access tracing and stack-based delay injection
Google Project Zero released MAccConc, Linux kernel tooling that traces memory accesses to explore and test race condition interleavings.
A Google Project Zero researcher published MAccConc (Memory Access Concurrency), tooling for exploring possible interleavings of multithreaded test cases in the Linux kernel, available on GitHub. The tools use KCOV with ASAN outline-mode instrumentation to record per-access memory traces, enabling automatic testing of all A-B-A interleavings plus terminal and GUI explorers for manual analysis. The work targets confirming race condition candidates, building reliable regression tests, and enabling concurrency fuzzing, drawing on ideas from SKI and Ned Williamson's sockfuzzer.
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