Search: “Drupal core”

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Drupal core - Moderately critical - Third-party libraries - SA-CORE-2026-013

Drupal issues moderately critical advisory for XSS in bundled CKEditor affecting content editors; fixed versions released, exploitation theoretical.

Drupal published SA-CORE-2026-013, rated moderately critical (13/25), covering an XSS vulnerability in the CKEditor library used for WYSIWYG editing. An attacker able to create or edit content, even without direct CKEditor access, could exploit it to target users with WYSIWYG permissions. Affected versions include Drupal core 10.5.x, 11.0.x and 11.4.x below 11.4.7, and updated releases are available. Exploitation is rated theoretical.

Drupal Security Advisories·Sep 16, 16:21 UTC · 8h agoAdvisory

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Can Foundation Models Moderate Online Content? Evaluating Instruction- vs. Example-Driven Policy Operationalization

ModerationBench shows foundation models can nearly triple Bluesky's moderation F1 (0.60 vs 0.22), with instruction- and example-driven guidance performing comparably.

Researchers built ModerationBench, a new benchmark of 4,000 manually annotated in-the-wild posts from Bluesky, to test whether foundation models can reliably operationalize content moderation policies. They systematically compare instruction-driven guidance (reasoning from policy precepts) with example-driven guidance (generalizing from precedents) for Vision-Language Models. Both paradigms achieve comparable peak effectiveness, and foundation models nearly triple the F1 of Bluesky's deployed moderation system on Random Posts (0.60 vs 0.22).

arXiv cs.AI / cs.LG / cs.CL·Sep 9, 16:30 UTC · 7d agoAI research1

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τ^τ-Bench: An Environment for End-To-End, Realistic Agent Construction

New τ^τ-bench tasks coding agents with building deployable customer-service agents; best config, Claude Opus 5, passes only 23.9% of simulations.

Researchers introduce τ^τ-bench, an end-to-end benchmark where a developer agent must build a complete customer-service agent from real business records, a client with requirements, a production API, an inherited codebase, and cost/model limits, then is scored by deploying it against held-out simulated users. Across 53 tasks in four domains, the strongest configuration, Claude Opus 5 under Claude Code, passes just 23.9% of evaluation simulations versus an 82.2% expert-authored reference ceiling. Failure modes mirror those of human developers: shallow queries instead of deep record comprehension, almost no client communication, and shipping the first architecture that runs rather than experimenting.

Hugging Face daily papers·Sep 3, 20:00 UTC · 13d agoAI research

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Agent Harness vs Agent Framework vs MCP: Which Layer Owns the Loop, State, Tools, Permissions, and Recovery

Architecture explainer separates agent harnesses, frameworks, and MCP by which layer owns the loop, state, permissions, and recovery.

The article distinguishes agent harnesses (OpenAI Codex, Claude Agent SDK), which own the execution loop, sandbox, permission model, and recovery; frameworks (LangGraph, OpenAI Agents SDK, Microsoft Agent Framework), which supply composable primitives; and MCP, a stateless JSON-RPC wire protocol governed by the Linux Foundation's Agentic AI Foundation since December 2025. An ownership matrix maps the execution loop, state, tool transport, permissions, recovery, sandboxing, and multi-agent orchestration to each layer. The 2026-07-28 MCP specification made the protocol fully stateless, retiring the initialize handshake and session headers.

MarkTechPost·Sep 14, 21:54 UTC · 2d agoAI research1

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Dr. Claw: An AI Scientist Workspace for Vibe Research

Researchers release Dr. Claw, an open-source auditable workspace that wraps coding agents like Claude Code for end-to-end AI-assisted research workflows.

Paper 2609.00365 presents Dr. Claw, an open-source workspace that wraps existing coding-agent executors such as Claude Code and Gemini CLI in a controllable, human-in-the-loop research workflow. It uses persistent state objects, a reusable skill library, and multi-executor coordination to make research decisions auditable and recoverable, rather than adding another autonomous agent. Holding the executor fixed, Dr. Claw scores higher on research completeness than a bare command-line agent while preserving an auditable process trail. The code is released under AGPL-3.0 on GitHub (OpenLAIR/dr-claw).

Hugging Face daily papers·Aug 30, 20:00 UTC · 17d agoAI research1

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[0day-rubbish] core-admin 1.0.164 (build 16468) Systemic shell command injection via ineffective quote escaping (8.8)

0day Rubbish discloses a CVSS 8.8 shell command injection in core-admin 1.0.164 via ineffective quote escaping, enabling authenticated remote code execution.

0day Rubbish Research Team publicly disclosed a systemic shell command injection (CWE-78) in core-admin 1.0.164 (build 16468). The flaw stems from ineffective quote escaping and scores 8.8 (AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H). The disclosure does not mention a CVE identifier or observed exploitation in the wild.

Full Disclosure·Sep 8, 17:31 UTC · 8d agoVulnerability1

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Context Engineering Inside the Harness: 4 Mechanisms That Beat Context Overflow and Goal Loss on Long-Horizon Tasks

Survey of four harness mechanisms—context budgeting, compaction, todo-state, and memory—that keep long-horizon LLM agents on task across 200+ tool calls.

The article details how agent harnesses, not larger context windows, solve context overflow and goal loss on long-horizon tasks, citing Chroma's Context Rot report showing 18 LLMs (GPT-4.1, Claude 4, Gemini 2.5, Qwen3) degrade on long inputs. Concrete implementations include LangChain Deep Agents offloading tool responses over 20,000 tokens to the filesystem and truncating old tool calls at 85% window usage, and Claude Code capping auto memory at 25KB while re-reading the 5 most recently modified files after compaction. OpenAI's Responses API now offers server-side compaction via context_management with a standalone /responses/compact endpoint, which Codex uses for long-running coding tasks. Manus reports a roughly 100:1 input-to-output token ratio per ~50-tool-call task, motivating todo.md state recitation to prevent goal drift.

MarkTechPost·Sep 13, 05:56 UTC · 3d agoAI research1

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Putting models to the secure coding test: Plan vs default mode

Datadog Security Labs tested Sonnet 5, Composer 2.5, and GPT 5.5 to see if plan mode yields more secure code than default mode.

Datadog Security Labs evaluated whether plan mode produces measurably more secure code than default mode. The test covered three frontier coding models: Sonnet 5, Composer 2.5, and GPT 5.5. The results inform how engineering teams should configure AI coding assistants to reduce insecure code. This is an AI security evaluation, not an incident report.

Datadog Security Labs·Aug 19, 00:00 UTC · 29d agoAI safety & security

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What Is a Website Attack Surface? A Beginner’s Guide to Reducing Risk

Sucuri's beginner guide explains how logins, plugins, APIs, and forgotten backups expand a website's attack surface and how to reduce that risk.

Sucuri published educational guidance explaining that login pages, contact forms, plugins, APIs, staging sites, and forgotten backups each add exposed components that constitute a website's attack surface. The article frames continuous attack surface reduction as a risk management practice for website owners. It is evergreen educational content rather than breaking incident news.

Sucuri Blog·Aug 19, 20:06 UTC · 28d agoIndustry

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PIA-Bench: Towards Automated Privacy Impact Assessment with Large Language Models

Researchers release PIA-Bench, the first open benchmark evaluating how accurately LLMs can automate privacy impact assessments using 73 curated federal PIAs.

PIA-Bench is the first open benchmark for evaluating large language models on real-world privacy impact assessments (PIAs). The authors audited 499 expert-authored PIAs published by US federal agencies and curated 73 structured PIAs comprising 451 privacy risk items and 831 mitigation items. Off-the-shelf LLMs were found to produce meaningful assessments while identifying clear avenues for improvement. The paper calls for domain-specific LLM agent workflows, accountable LLM infrastructure, and new quality standards for PIAs.

arXiv cs.CR·Sep 11, 08:16 UTC · 5d agoResearch1

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Survey of filesystem MCP servers: how the "sandboxed filesystem" boundary is enforced (one breach, four defended-by-design)

Survey finds one filesystem MCP server vulnerable to a symlink-based sandbox escape while four others are defended by design.

A survey of five filesystem MCP servers assessed how each enforces its path-confinement boundary against symlink escapes in recursive directory walkers. The iceener/files-stdio-mcp-server is vulnerable to a read-side sandbox escape. The other four are defended by design or make no confinement claim. The author describes the vulnerability class as small but real.

oss-security·Sep 10, 01:14 UTC · 6d agoVulnerability

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Benchmark Radar: A Living Database and Search Engine for AI Benchmarks and Evaluation

Benchmark Radar provides a living searchable database of 1,283 AI benchmark records and 12,916 score observations drawn from 37 daily discovery sources.

Benchmark Radar combines daily discovery of benchmark papers, repositories, datasets, and releases from 13 direct connectors and 24 first-party feeds into a searchable catalog with model card mentions and score histories. The catalog contains 1,283 source records drawn from 4 benchmark catalogs plus 12,916 numeric observations on 790 records. The release includes a web dashboard with leaderboard, Pareto frontier of score versus usage, saturation and trend views, daily feeds, a CLI, and reproducible analysis. The paper audits the full catalog and examines benchmark saturation and limits of score comparisons.

Hugging Face daily papers·Sep 9, 20:00 UTC · 7d agoAI research

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ModularRSI: Modular and Generalizable Recursive Harness Self-Improvement

Researchers propose ModularRSI, a modular benchmark-disjoint recursive self-improvement framework that evolves agent harnesses across five modules, improving TB2.0 and SWE-Bench Verified results.

ModularRSI targets generalizable recursive self-improvement (RSI) for agent harnesses by contrasting successful and failed trajectories for the same task and aggregating evidence across tasks to find recurring behavioral deficiencies. It decomposes the evolvable harness into five modules—Agent Loop, Tool Use, Observation Management, Context Management, and Task Completion Detection—each evolved independently within a restricted scope, then integrated with conflict resolution. Using 2,000 executable evolution tasks disjoint from evaluation benchmarks, it shows consistent gains on TB2.0 and SWE-Bench Verified and transfers across different foundation models.

Hugging Face daily papers·Sep 13, 20:00 UTC · 3d agoAI research

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automatic module_metadata_base.json update

Metasploit Framework's automated pipeline refreshed its module metadata file, a routine repository maintenance commit introducing no new modules or exploits.

An automated Metasploit Framework commit updated module_metadata_base.json, the metadata database consumed by module tooling. The change is routine maintenance and contains no new exploit modules or vulnerability content.

Metasploit Framework commits·Sep 3, 13:45 UTC · 13d agoTools1

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iceener/files-stdio-mcp-server: sandbox escape in fs_search via a symlinked directory (recursive walker validates only the top level)

iceener/files-stdio-mcp-server allows a read-side sandbox escape: fs_search follows symlinked directories while the recursive walker validates confinement only at the top level.

A vulnerability report describes a read-side sandbox escape in iceener/files-stdio-mcp-server, an MCP server for text-based file access that explicitly promises 'Sandboxed filesystem access. Only these paths are available'. The fs_search tool can follow symlinked directories outside the allowed paths, and the recursive directory-listing walker used by fs_search (and by fs_read) validates confinement only at the top level. The same flaw affects fs_read's directory-listing walker. No CVE identifier was assigned in the provided report text.

oss-security·Sep 10, 01:17 UTC · 6d agoVulnerability

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Everything in Moderation: Per-Domain Coverage Optima and Alignment-Resistant Domain Gaps in Multi-Domain Mid-Training

Controlled mid-training experiments on Qwen3-8B-Base find each domain has a 10-40% coverage optimum and domain gaps survive alignment SFT.

Using Qwen3-8B-Base (with a 4B replication) across five semantically rule-disjoint KOR-Bench domains, the authors train 30 data allocations spanning the five-domain simplex at five seeds each. All five domains show interior optima in the moderate 10-40% coverage band, and domain gaps persist after a fixed-budget compensatory SFT pass, which raises 116/120 cells yet bridges 0/240 pairs at a 5% threshold. Zero coverage collapses mid-training-only accuracy, though a FineWeb-Edu-only control shows the collapse is partly generic drift. The results argue mid-training data composition requires principled design rather than reliance on later alignment.

arXiv cs.AI / cs.LG / cs.CL·Sep 8, 17:31 UTC · 8d agoAI research1

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Miles v0.1: Production-Level Post-Training

Radix Ark open-sources Miles v0.1, a full-stack RL post-training framework demonstrated with asynchronous agentic RL on GLM-5.2 744B-A40B across 64 GB300 GPUs.

Miles v0.1 is a full-stack, open-source system for frontier-scale reinforcement-learning post-training, built on slime with rollout engines on SGLang and trainers supporting NVIDIA Megatron-LM and PyTorch FSDP backends plus three weight-synchronization transports. It supports full-parameter RL, LoRA RL, on-policy distillation, supervised fine-tuning, true-on-policy rollout-training alignment, and extends to diffusion models. The end-to-end case study ran fully asynchronous agentic RL on GLM-5.2 744B-A40B for terminal-use coding tasks on 64 NVIDIA GB300 GPUs with a median step time of 263 seconds over the first 30 measured steps. The code is open-sourced on GitHub.

Hugging Face daily papers·Sep 7, 20:00 UTC · 9d agoAI tools & infra

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CUA-Universe: A Scalable and Dynamic Environment for Hybrid GUI+CLI Agents

Researchers introduce CUA-Universe, a pipeline turning real desktop software into hybrid GUI+CLI agent environments, lifting a 9B model's OSWorld success rate.

CUA-Universe is an environment-to-data pipeline that converts real desktop applications into hybrid GUI+CLI environments, scaling to 16 applications via App-Forge, Task-Weave, and Path-Steer. Training on its harvested trajectories shifted a 9B model toward effective GUI+CLI orchestration, yielding +39.3 points on CUA-Verse, +16.8 points success rate on OSWorld, and +7.84 points on OSWorld-MCP while cutting steps and tokens by up to 57% and 60%. The work addresses the scarcity of scalable hybrid environments for computer-use agents.

arXiv cs.AI / cs.LG / cs.CL·Sep 4, 17:26 UTC · 12d agoAI research1

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NeoHorse-1: Towards Recursive Self-Improvement via Agentic Post-Training with Routing Harness

NeoHorse-1 introduces agentic post-training with intelligent routing that lifts agent benchmark scores at 4B and 9B scales, prototyping recursive self-improvement.

NeoHorse-1 is a family of agent-native models trained through agentic post-training: routing-harness logs (predicted capability demand, service tier, interaction) become structurally validated training data organized into a three-stage SFT curriculum plus routing-guided on-policy distillation. Capability-guided allocation converts evaluation feedback into the next training mixture, closing an evaluation-selection-update loop. Post-training raises the macro-average from 58.94 to 64.87 at 4B and from 65.60 to 69.04 at 9B across eleven agent, tool-use, coding, and instruction-following benchmarks. The authors position it as a prototype of harness-mediated recursive self-improvement.

Hugging Face daily papers·Sep 7, 20:00 UTC · 9d agoAI research1

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ToolHive: The open-source way to run any MCP server securely

Stacklok's open-source ToolHive runs Model Context Protocol servers in isolated containers with per-request identity enforcement, audit logging and a signed registry.

ToolHive, shipped under Apache 2.0, containersizes MCP servers locally via Docker or Podman or in clusters through a Kubernetes operator, applying permissions, network filtering, and secrets management. The platform includes a Registry Server implementing the official MCP Registry API with signing and provenance verification, a Virtual MCP Server gateway with OIDC/OAuth single sign-on and OpenTelemetry traces, and a desktop Portal for one-click installs. The browser-based cloud UI is retired, so the desktop app and CLI are the supported rollout paths.

Help Net Security·Sep 7, 00:00 UTC · 10d agoAI tools & infra1

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ActReview: Rebuttal-Guided Training Data and Rubric Rewards for Actionable Peer Review Generation

ActReview post-trains Qwen3-8B-Base on OpenReview rebuttals to generate actionable peer-review feedback with grounded revision suggestions, benchmarked on 1,000 curated instances.

The paper defines Actionable Peer-review Generation as diagnostic claim generation plus revision suggestion generation and introduces ActReview, a rebuttal-guided post-training framework. From OpenReview review-rebuttal threads the authors build ActReview-40K, aligning reviewer weaknesses with author responses grounded in localized paper evidence, and post-train Qwen3-8B-Base with multi-task SFT followed by GRPO using weakness-specific rubric rewards. They also release ActReview-Bench, a human-curated 1,000-instance benchmark, on which ActReview outperforms prior specialized review-generation models on actionability and grounding while remaining competitive with strong prompt-based LLMs. Human evaluation confirms improved revision usefulness but identifies a remaining gap in technical accuracy.

Hugging Face daily papers·Sep 7, 20:00 UTC · 9d agoAI research

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MicroHasTEE: Bare-Metal Haskell for Type-Level Peripheral Ownership on Armv8-M

MicroHasTEE expresses TrustZone secure and non-secure firmware as one typed Haskell program, catching peripheral-ownership inconsistencies at compile time.

MicroHasTEE is a multiparty Haskell framework that models both TrustZone firmware images as participants in a single typed program, using type-level capability ledgers to track peripheral acquisition, configuration, transfer, and finalization. MicroHs compiles the shared program twice to produce separate bare-metal Secure and Non-secure firmware images. The framework rejects inconsistent resource use, post-configuration attribution changes, wrong-domain callbacks, and calls to unregistered Secure services. A door-lock case study on an STM32U5 Nucleo board produced images of 232.7 KiB and 228.4 KiB of flash with roughly 220 KiB of SRAM per domain.

arXiv cs.CR·Sep 11, 08:34 UTC · 5d agoResearch1

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automatic module_metadata_base.json update

Metasploit Framework automatically updates its module metadata JSON in routine maintenance commit.

The Metasploit Framework repository received an automatic update to module_metadata_base.json, the metadata file that tracks module information. No specific new vulnerability, exploit module, or feature is described in the commit message. This is routine repository maintenance rather than a notable security event.

Metasploit Framework commits·Sep 3, 16:19 UTC · 13d agoTools

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The Frontier AEO Tracker: What Astra Chooses (and every other frontier model, and what you can do about it)

Latent Space launches an AEO tracker scoring 7 frontier models' product recommendations across 161 categories, revealing generational bias flips.

Latent Space built a tracker measuring Answer Engine Optimization by running 6 prompt variations across 7 frontier models with search enabled over 161 product categories, scoring first choices, alternatives, mentions, and anti-recommendations. It found 28 categories with a universally dominant primary choice and observed soft biases, such as models favoring their own lab's coding agents. Analysis of Anthropic's Sol→Astra and Opus→Fable generations showed newer models consulting fewer sources and being less likely to change answers when questions are paraphrased.

Latent Space·Sep 7, 21:32 UTC · 9d agoAI research

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Best Practices for Good Endpoint Hardening | Huntress

Huntress outlines endpoint hardening best practices, citing exposed RDP, RMM tool abuse, and ClickFix social engineering as common SMB intrusion paths.

Huntress published defensive guidance on endpoint hardening for small and mid-sized businesses, drawing on observations from its SOC. The post describes common intrusion vectors: internet-exposed RDP brute-forced by automated scanners, phishing emails delivering attacker-controlled remote monitoring and management (RMM) tools, with Huntress reporting a 277% spike in RMM abuse in 2025, and ClickFix attacks using fake CAPTCHA pages that trick users into running malicious commands. Recommended controls include scanning for exposed RDP, SSH, and VPN interfaces, removing unneeded local admin rights, enabling Windows Defender tamper protection, disabling SMBv1, and standardizing on one approved remote access tool, guided by CIS and NIST frameworks.

Huntress·Sep 10, 15:00 UTC · 6d agoAdvisory

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AWS limits AI agents’ data access, even when manipulated

AWS detailed propagating user authorization context through Bedrock AgentCore so downstream services enforce access controls even if the agent is manipulated via prompt injection.

AWS described an architecture for Amazon Bedrock AgentCore where user tokens and department claims are validated at runtime and propagated to DynamoDB, Bedrock Knowledge Bases, and Salesforce. Downstream services enforce authorization themselves, so a prompt-injected or buggy agent cannot retrieve data the user is not entitled to see. AWS demonstrated the pattern with a CRM use case separating Sales and Finance access and recommends IAM-backed knowledge bases for stricter isolation.

Help Net Security·Aug 20, 00:00 UTC · 28d agoAI safety & security

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IDORacle: Template-Guided SQL-Sink Mediation for Object-Level Authorization in Java Applications

IDORacle intercepts MyBatis/JDBC SQL sinks to block horizontal privilege escalation in legacy Java apps with sub-millisecond guard latency.

IDORacle is a template-guided SQL-sink interception and rewriting framework that prevents IDOR/BOLA horizontal privilege escalation at runtime in Java database applications. It propagates authenticated identity context across HTTP requests, asynchronous tasks, and data-access boundaries via a server-side trace identifier, and computes dual SQL fingerprints at the MyBatis/JDBC boundary to generate reusable mediation plans. On a Java-SQL benchmark grounded in real-world CVE reports, it blocks tested violations with worst-case guard latency of 0.17 ms, reduced to 0.017 ms average for hot templates via redundancy-aware optimization.

arXiv cs.CR·Sep 11, 04:20 UTC · 5d agoResearch1

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Occamy-1.0: Open Pareto-frontier 35B Intelligence for Co-work

Occamy-1.0 releases open 35B weights post-trained from Qwen3.6-35B-A3B, targeting cost-efficient co-work agents at Pareto-frontier pricing.

Occamy-1.0 is a cost-efficient co-work agent model built by further training the post-trained Qwen3.6-35B-A3B checkpoint, using execution-grounded data, replayable long-horizon trajectories across multiple harnesses, and staged post-training. It consistently ranks among the strongest comparably sized models across co-work benchmarks and remains competitive with substantially larger frontier systems on several tasks. Its aggregate performance across four representative benchmarks places it at the low-cost knee of the observed cost-performance Pareto frontier, while preserving tool calling, coding, and instruction following capability. The model weights and a subset of training data are publicly released.

Hugging Face daily papers·Sep 3, 20:00 UTC · 13d agoModel release

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automatic module_metadata_base.json update

Routine automated Metasploit Framework commit updating module metadata, with no disclosed vulnerability or exploitation activity.

The Metasploit Framework repository received an automatic update to its module_metadata_base.json file. The commit text contains no vulnerability details, CVE references, or new exploit modules. This is routine maintenance activity on the open-source penetration testing framework.

Metasploit Framework commits·Sep 1, 21:40 UTC · 15d agoTools

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Advanced URL Filtering Archives

Palo Alto Networks markets Advanced URL Filtering as combining a malicious URL database with real-time ML and DL web protection.

The Unit 42 blog page is a product category archive for Advanced URL Filtering. The product description states it combines a malicious URL database with a real-time web protection engine powered by machine learning and deep learning models. No research findings, incidents, or vulnerabilities are discussed.

Palo Alto Unit 42·Sep 8, 14:27 UTC · 8d agoIndustry 6 sources

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PACE: Perceived-Latency-Aware Cascading Service Routing and Filler Control for QoE-Efficient Retrieval-Augmented Dialogue Serving

PACE cuts perceived latency in retrieval-augmented dialogue serving via cascading routing and filler control, reaching 0.41s P95 under load.

PACE is a serving framework for retrieval-augmented dialogue that optimizes Perceived Time-to-First-Response (PTFR) under quality and cost constraints. It combines a load-adaptive cascading router, a joint path-filler controller, and volatility-aware cache admission, deployed on a humanoid-robot sales service. On 75k CarQA requests, the cascade halved pure-LLM P95 PTFR (0.29s vs 0.53s) and the adaptive controller reached 0.41s P95, 2.4x better than RAG at high load; filler calls dropped 94% and stale answers fell from 86% to 0%.

arXiv cs.AI / cs.LG / cs.CL·Sep 9, 16:02 UTC · 7d agoAI tools & infra

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