CVE-2026-3580

In wolfSSL 5.8.4, GCC optimizes constant-time masking logic in sp_256_get_entry_256_9 into conditional branches (bnez) when targeting RISC-V RV32I with -O3, breaking the expected side-channel resistance of ECC scalar multiplication. This may enable a local attacker to recover secret keys via timi...

CVE-2026-3580

In wolfSSL 5.8.4, constant-time masking logic in sp256getentry2569 is optimized into conditional branches bnez by GCC when targeting RISC-V RV32I with -O3. This transformation breaks the side-channel resistance of ECC scalar multiplication, potentially allowing a local attacker to recover secret...

CVE-2026-3580 Compiler-induced timing leak in sp_256_get_entry_256_9 on RISC-V

In wolfSSL 5.8.4, constant-time masking logic in sp256getentry2569 is optimized into conditional branches bnez by GCC when targeting RISC-V RV32I with -O3. This transformation breaks the side-channel resistance of ECC scalar multiplication, potentially allowing a local attacker to recover secret...

CVE-2026-27980

An unbounded disk usage flaw has been discovered in Next.js. The default Next.js image optimization disk cache /next/image did not have a configurable upper bound, allowing unbounded cache growth. An attacker could generate many unique image-optimization variants and exhaust disk space, causing...

CVE-2026-27980

Next.js is a React framework for building full-stack web applications. Starting in version 10.0.0 and prior to version 16.1.7, the default Next.js image optimization disk cache /next/image did not have a configurable upper bound, allowing unbounded cache growth. An attacker could generate many...

CVE-2026-27980

Next.js versions 10.0.0 through 16.1.6 expose an unbounded disk cache in the image optimization feature at /_next/image, allowing denial of service via cache growth. The root cause is a lack of an upper bound on the disk cache; the fix in v16.1.7 adds an LRU-backed disk cache and an eviction poli...

CVE-2026-27980 Next.js: Unbounded next/image disk cache growth can exhaust storage

Next.js is a React framework for building full-stack web applications. Starting in version 10.0.0 and prior to version 16.1.7, the default Next.js image optimization disk cache /next/image did not have a configurable upper bound, allowing unbounded cache growth. An attacker could generate many...

CVE-2026-27980 Next.js: Unbounded next/image disk cache growth can exhaust storage

Next.js is a React framework for building full-stack web applications. Starting in version 10.0.0 and prior to version 16.1.7, the default Next.js image optimization disk cache /next/image did not have a configurable upper bound, allowing unbounded cache growth. An attacker could generate many...

CVE-2026-27980: Uncontrolled Resource Consumption

Next.js is a React framework for building full-stack web applications. Starting in version 10.0.0 and prior to version 16.1.7, the default Next.js image optimization disk cache /next/image did not have a configurable upper bound, allowing unbounded cache growth. An attacker could generate many...

Defending the Power Grid by Segmenting the EV Charging Cyber Infrastructure

This paper examines defending the power grid against load-altering attacks using electric vehicle charging. It proposes to preventively segment the cyber infrastructure that charging station operators CSOs use to communicate with and control their charging stations, thereby limiting the impact of...

Allocation of Resources Without Limits or Throttling

Overview next is a react framework. Affected versions of this package are vulnerable to Allocation of Resources Without Limits or Throttling due to the lack of an upper bound on the disk cache used by the image optimization. An attacker can exhaust disk storage by generating a large number of...

Next.js: Unbounded next/image disk cache growth can exhaust storage

Summary The default Next.js image optimization disk cache /next/image did not have a configurable upper bound, allowing unbounded cache growth. Impact An attacker could generate many unique image-optimization variants and exhaust disk space, causing denial of service. Note that this does not impa...

DeepStage: Learning Autonomous Defense Policies against Multi-Stage APT Campaigns

This paper presents DeepStage, a deep reinforcement learning DRL framework for adaptive, stage-aware defense against Advanced Persistent Threats APTs. The enterprise environment is modeled as a partially observable Markov decision process POMDP, where host provenance and network telemetry are fus...

CLSA-2026-1773314343 git-lfs: Fix of CVE-2025-61729

Rebuild with golang 1.25.7-1.el96.tuxcare.els1 to fix CVE-2025-61729 - CVE-2025-61729: limit number of hosts printed in HostnameError.Error and optimize error string construction to prevent quadratic runtime...

EUVD-2026-11160

Calling NSS-backed functions that support caching via nscd may call the nscd client side code and in the GNU C Library version 2.36 under high load on x8664 systems, the client may call memcmp on inputs that are concurrently modified by other processes or threads and crash. The nscd client in the...

CVE-2026-3904

The GNU C Library (glibc) versions 2.35 and 2.36 are vulnerable to a crash in the nscd client when running on x86_64 systems under high load. The root cause is an optimized memcmp implementation that fails when invoked with inputs concurrently modified by other threads or processes, leading to un...

Systematic Scaling Analysis of Jailbreak Attacks in Large Language Models

Large language models remain vulnerable to jailbreak attacks, yet we still lack a systematic understanding of how jailbreak success scales with attacker effort across methods, model families, and harm types. We initiate a scaling-law framework for jailbreaks by treating each attack as a...

Robust Provably Secure Image Steganography Via Latent Iterative Optimization

We propose a robust and provably secure image steganography framework based on latent-space iterative optimization. Within this framework, the receiver treats the transmitted image as a fixed reference and iteratively refines a latent variable to minimize the reconstruction error, thereby improvi...

PRoADS: Provably Secure and Robust Audio Diffusion Steganography with Latent Optimization and Backward Euler Inversion

This paper proposes PRoADS, a provably secure and robust audio steganographic framework based on audio diffusion models. As a generative steganography scheme, PRoADS embeds secret messages into the initial noise of diffusion models via orthogonal matrix projection. To address the reconstruction...

Important: Red Hat Security Advisory: Red Hat AI Inference Server Model Optimization Tools 3.2.2 (CUDA)

Red Hat AI Inference Server Model Optimization Tools 3.2.2 CUDA is now available. Red Hat® AI Inference Server Model Optimization Tools...