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SecureClaw: Clawing Back Control of LLM Agents
arXiv:2606.09549v1 Announce Type: new Abstract: Tool-using large language model (LLM) agents face two distinct security failures: unauthorized external actions and exposure of sensitive plaintext inside the runtime before any final output check can intervene. Existing defenses usually protect one boundary, either the planner/runtime or the action sink, and therefore do not by themselves secure both surfaces. We present SecureClaw, a dual-boundary architecture that places authorization at the...
PS-UIE: Privilege-Separated Integrity Enforcement for User-Space Executable Objects in Confidential VMs
arXiv:2606.04549v1 Announce Type: new Abstract: Confidential Virtual Machines (CVMs), such as AMD SEV-SNP, enable cloud tenants to run security-sensitive workloads, but tenants can rely on the execution of these workloads only when they can trust the CVM. This trust requires continuous integrity assurance from CVM launch to the current runtime state, including initial trust establishment at launch and subsequent runtime integrity assurance. Existing works help establish launch-time trust and...
Security-First Approach to API Pipeline Development with Zero-Trust Architecture
arXiv:2606.09062v1 Announce Type: new Abstract: Modern enterprises face an accelerating onslaught of API-targeted threats amid a rapidly expanding attack surface. Record volumes of software vulnerabilities continue to accelerate dramatically, with 28,818 CVEs disclosed in 2023 (a 38% jump from 2022) and 40,009 CVEs in 2024 (another 38% increase), while the average time-to-exploit (TTE) of new flaws shrank to mere days (approximately 5 days in 2023, down from 32 days in 2021). At the same...
AgileOS: A GPU Operating System Layer for Protected CUDA Services
Announce Type: new Abstract: Modern GPU applications increasingly interact with storage systems, network devices, vendor libraries, and GPU-resident services rather than executing only isolated compute kernels. This shift creates a need for operating-system-like protection around GPU services, where service metadata, device queues, memory-mapped I/O regions, and library-internal state should not be directly exposed to untrusted application kernels. However, today's CUDA programming model, by...
Generalizing Fair Top-$k$ Selection: An Integrative Approach
arXiv:2603.04689v3 Announce Type: replace Abstract: Fair top-$k$ selection, which ensures appropriate proportional representation of members from minority or historically disadvantaged groups among the top-$k$ selected candidates, has drawn significant attention. We study the problem of finding a fair (linear) scoring function with multiple protected groups while also minimizing the disparity from a reference scoring function. This generalizes the prior setup, which was restricted to the...
Proof-Carrying Agent Actions: Model-Agnostic Runtime Governance for Heterogeneous Agent Systems
Announce Type: new Abstract: Agent systems execute through runtimes with very different control points: local coding tools, framework SDKs, managed agent platforms, API gateways, and observer-only integrations. A high-risk action such as publishing data externally may therefore appear as a shell command in one runtime, a tool call in another, and a hosted session transition in a third. This makes it difficult to answer a basic governance question consistently: what action was authorized,...
SkillGuard: A Permission Framework for Agent Skills
arXiv:2606.03024v1 Announce Type: new Abstract: Agent skills extend LLM agents with reusable instructions, scripts, tool bindings, and contextual dependencies. However, current skill ecosystems largely rely on trust-based loading and static inspection, leaving a gap between what a skill can inject into an agent's context and what it can cause the agent to do at runtime. This gap introduces new security and privacy risks, and existing defenses primarily inspect skill files statically or...
Verifiable and Confidential DNN Inference on Low-End Edge Devices
Announce Type: new Abstract: Deploying deep neural network (DNN) inference on low-end edge devices raises two key challenges: protecting model confidentiality against a potentially compromised edge system and enabling verifiable inference without incurring prohibitive overhead. Existing approaches either house partial models and inference software within trusted execution environments (TEEs), resulting in high cost and an application-dependent trusted computing base (TCB), or execute in...
GovAI-Pipe: A Layered AI Governance Pipeline for Citizen-Facing AI in Turkey's e-Government Gateway
arXiv:2606.01417v1 Announce Type: new Abstract: Turkey's e-Government Gateway (e-Devlet) serves over 68 million registered users with more than 9,200 government services, and is increasingly integrating artificial intelligence into citizen-facing applications such as chatbot assistants and eligibility assessments. However, no structured technical governance infrastructure currently connects high-level AI policy frameworks, such as the EU AI Act, OECD AI Principles, and Turkey's own National...
Relocate and Emulate: Re-Hosting Android's Application Layer
Announce Type: new Abstract: Dynamic analysis of Android's application layer typically relies on physical devices, limiting scalability and reproducibility. To compensate, we introduce a systematic re-hosting method that relocates the Android framework and pre-installed software from real device firmware into a fully emulated environment. Our approach integrates vendor-specific components into the Android Open Source Project (AOSP) build system using tailored extraction and injection...