Search: “still-toolkit”

Technical Manual for a Toolkit for Measuring Contextual Individuation in Transformer Language Models

An open methodology toolkit measures whether transformer language models contextualize fixed word forms across domains using bridge forms and layer-wise silhouette analysis.

The manual documents an open toolkit built around 'bridge forms' - identical written words recurring across two or more subject domains with a different sense in each - to test whether transformer language models individuate word occurrences by context beyond the embedding layer. It covers declarative specification of bridge forms, Wikipedia corpus acquisition, occurrence localization, layer-wise representation extraction, domain-pairwise silhouette measurement, and visualization, justifying each choice against failure modes such as sense contamination and subword-tokenization misalignment. It is a methodological and implementation reference and reports no empirical results.

arXiv cs.AI / cs.LG / cs.CL·Sep 4, 16:38 UTC · 12d agoAI research

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

RMM Tools for MSPs: Features, Risks & How to Stay Secure

Threat actors continue abusing MSP remote monitoring and management tools to reach downstream customers, four years after the Kaseya supply chain attack.

Huntress examines how RMM platforms remain a favored gateway for attackers targeting managed service providers and their clients. A recent incident demonstrates that adversaries still successfully pivot from MSP RMM tooling into downstream customer environments. The piece also covers RMM features, associated risks, and hardening guidance for providers.

Huntress·Sep 1, 04:00 UTC · 15d agoThreat actor in the wild

Multi-Step Tool-Calling over Korean Open Public APIs: A Benchmark and a Data-Synthesis Recipe

Researchers introduce KOPA-Bench, a 145-task Korean public API tool-calling benchmark, and EDGE, an execution-grounded data synthesis method.

An arXiv paper presents KOPA-Bench, a benchmark of 145 real-world tasks chaining multiple tool-calls across live Korean government APIs, motivated by data-sovereignty requirements for on-premise open-source LLM agents. It also introduces EDGE, an execution-grounded dynamic graph that keeps only tool-output-to-input links verified by live API calls before synthesizing executable multi-step trajectories. A 9B model fine-tuned with GRPO on the resulting dataset nearly matches its untuned 27B family sibling on KOPA-Bench and improves on the BFCL benchmark.

arXiv cs.AI / cs.LG / cs.CL·Sep 4, 17:44 UTC · 12d agoAI research1

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

Update modules/auxiliary/scanner/http/elasticsearch_tika_xfa_xxe.rb

Rapid7 updated a Metasploit auxiliary scanner module that detects XML external entity injection in Elasticsearch via Apache Tika.

A commit in the Metasploit Framework updated modules/auxiliary/scanner/http/elasticsearch_tika_xfa_xxe.rb, an auxiliary scanner module. The module targets XML external entity (XXE) injection in Elasticsearch through Apache Tika, and was co-authored by jheysel-r7. The terse commit message contains no additional details, CVE references, or exploitation notes.

Metasploit Framework commits·Sep 8, 19:22 UTC · 8d agoTools

Honeypot-Omaha and batch.py [Guest Diary], (Wed, Sep 2nd)

A SANS ISC guest diary describes batch.py, a Python tool that consolidates honeypot logs and enriches IOCs with threat intelligence data.

Written by a SANS.edu BACS intern, the diary explains analysis of the DShield Honeypot-Omaha sensor, which uses Cowrie to emulate SSH and Telnet and log attacker activity. The author's batch.py script implements a four-phase pipeline with SHA-256-generated master and guest authentication to consolidate JSON and log files, correlate data via external APIs, and produce MITRE, CVE, geolocation, threat-score and fingerprint enrichment for investigated indicators.

SANS Internet Storm Center·Sep 3, 02:02 UTC · 13d agoTools1

Learning never stops: How AI makes learning continuous

OpenAI report describes how students and educators use ChatGPT to extend learning continuously beyond the classroom.

OpenAI published a report examining how students and educators use ChatGPT to make learning more continuous. The report describes support that extends beyond the classroom, positioning ChatGPT as an ongoing learning companion. The release is part of OpenAI's education-focused communications rather than a technical or safety research paper.

OpenAI News·Aug 26, 10:00 UTC · 21d agoAI industry

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

ToolLoop: Closed-Loop Tool-Use Data Synthesis via Decomposed Generation and Dynamic Self-Feedback

ToolLoop introduces a closed-loop synthetic data framework whose 11K examples lift a 4B model to 86.40% on BFCL tool-use evaluation.

ToolLoop decomposes tool-use data synthesis into function-name sampling, backward derivation of user queries, and forward derivation of tool calls, with dynamic self-feedback at each stage. This shifts the paradigm from generate-then-filter to generate-verify-refine, reducing inefficient and imbalanced synthetic data. A 4B model trained on 11K synthetic examples reaches 86.40% accuracy on BFCL non-reasoning mode (86.07% in an Isolate variant excluding BFCL-overlapping functions) and 72.1% on ACEBench using only 18.3% of baseline training data.

arXiv cs.AI / cs.LG / cs.CL·Sep 8, 17:26 UTC · 8d agoAI research1

Ask HN: Anyone still coding like 2021? Where do you work?

Hacker News users debate coding without LLMs, with one developer fired for refusing AI tools and others describing daily hand-coding practice to counter skill atrophy.

An Ask HN thread collects experiences of developers who still write code without LLM assistance. One contributor says he was fired for political reasons after refusing to use LLMs despite adequate stated performance, and observes fewer job ads now require LLM use. Others describe starting each day with a LeetCode problem or 30-60 minutes of hand-coding to stay sharp, contractual bans on AI-generated code for a government-adjacent embedded product over unresolved copyright issues, and inconsistent corporate policies where ChatGPT or Codex use flip-flops between allowed and blocked while a CIO mandates 70-80% AI-generated code next year.

Hacker News · AI·Sep 9, 13:41 UTC · 7d agoAI industryHN 47↑ · 54 comments2

Google Open-Sources Mantis: A Modular Skills Toolkit That Lets Coding Agents Find, Reproduce and Patch Vulnerabilities

Google open-sourced Mantis, an Apache-2.0 modular skills toolkit that lets AI coding agents find, reproduce, and patch vulnerabilities with sandboxed verification.

Google released Mantis on GitHub under Apache 2.0 as a stack-agnostic set of slash-command skills that chain through the full vulnerability lifecycle: mining version history, building threat models, filtering findings, reproducing bugs in gVisor or network-disabled VMs, assembling exploit chains, patching, and scoring residual risk from 1 to 10. It runs with Gemini CLI, Antigravity CLI, the Google ADK, or comparable agent frameworks, and a supervisor skill (/mantis-meta-agent) can drive the whole loop. Google says the design targets the sub-7 percent true-positive rate of naive AI code scanning, and that its hierarchical summary tree cuts token overhead by over 85 percent. The toolkit is deployable for local and internal evaluation but not yet recommended for production.

MarkTechPost·Sep 9, 22:58 UTC · 7d agoAI tools & infra

How to implement a continuous offensive security testing program

Help Net Security·Aug 10, 12:13 UTC · Aug 10, 2026Exploit / PoC1

Continual Learning Mechanisms Compose for Long-Horizon Memorization

Composing data, function, and weight anchors with merged LoRA raises 100-task long-horizon retention from 1.2% to 34.9% in continual fine-tuning.

The paper introduces long-horizon memorization: a model learns 100 query-answer tasks through continual supervised fine-tuning without retaining earlier examples or receiving task identifiers at inference. No single continual learning mechanism maintains strong retention at this horizon, so the authors compose complementary mechanisms along data/function/weight anchors and low-rank allocation rules. The best method combining all three anchors with merged LoRA ranks among the top 3 methods on all three datasets and raises average final retention from 1.2% to 34.9%, a 28-fold improvement.

Hugging Face daily papers·Sep 6, 20:00 UTC · 10d agoAI research

Intezer adds native response automation without separate SOAR

Intezer launched Workflows, native response automation inside its AI SOC, letting teams automate remediation without a separate SOAR platform.

Intezer announced Workflows, a native automation and response builder inside its AI SOC platform that lets security teams run post-investigation actions such as closing alerts, isolating hosts, and updating tickets without a separate SOAR. Workflows are created through natural language via MCP, inherit full investigation context, and are logged for audit, with per-tenant routing and customer communications aimed at MSSPs. The announcement cites Intezer's AI SOC Report 2026 finding that nearly 1% of real incidents trace back to lowest-severity alerts.

Help Net Security·Aug 19, 00:00 UTC · 29d agoTools

llm 0.34

Version 0.34 of Simon Willison's llm CLI adds response-duration metrics to log output, plus bug fixes and faster log querying.

The open-source llm command-line tool for interacting with large language models released version 0.34. The headline change adds response duration in milliseconds and human-readable form to llm logs --usage Markdown output, plus a new duration_ms field in llm logs --short. The release includes several contributed bug fixes and a significant performance improvement to llm logs, alongside the related llm-openrouter 0.7.1 release.

Simon Willison·Sep 2, 19:23 UTC · 14d agoAI tools & infra1

Hottest cybersecurity open-source tools of the month: August 2026

August's open-source security roundup highlights NVIDIA SkillSpector for AI agent skill scanning, Future AGI, Chainloop, PentestGPT, and Hazmat agent containment.

Help Net Security's August 2026 roundup covers five open-source tools: NVIDIA's SkillSpector, a scanner that assesses AI agent skills from directories, zips, SKILL.md files, or Git URLs and returns findings and risk scores; Future AGI, an Apache 2.0 platform for tracing, evaluating, simulating, and guardrailing LLM agents; Chainloop, a software supply chain evidence store that produces signed in-toto attestations in CI pipelines; PentestGPT, an agentic penetration testing framework running recon, exploit, and reporting stages; and Hazmat, which runs AI coding agents like Claude Code and Codex inside a separate machine account for containment.

Help Net Security·Aug 26, 00:00 UTC · 22d agoTools

4 groups caught using the same Chrome and Windows exploit kit

Proofpoint says at least four groups, some China-linked, actively share the BlueMoon kit chaining two Chromium and one Windows kernel exploit.

Proofpoint researchers report that at least four hacking groups, some with ties to the Chinese government, are actively using a nearly identical exploit kit named BlueMoon. The kit chains two Chromium browser vulnerabilities and one Windows kernel flaw affecting Windows 10, Windows 11 initial release, and a later Windows version to install malware of the attacker's choice. All three vulnerabilities received patches within the past 24 hours. Proofpoint attributes the kit's rapid, widely shared deployment to a Chromium patch-gap window and AI agents accelerating exploit development against publicly accessible upstream patches.

Ars Technica · Security·Sep 9, 20:55 UTC · 7d agoExploit / PoC in the wild3

The Vulnerability Gap: Why Discovery Is Outrunning Repair

Dark Reading argues AI-accelerated vulnerability discovery and tightening regulation are widening the gap between flaw discovery and repair capacity.

The article argues that AI tooling is increasing the pace at which vulnerabilities are discovered while remediation capacity has not kept up, creating a growing backlog. It frames this widening 'vulnerability gap', combined with a tightening regulatory environment, as an all-hands-on-deck moment for security teams. The piece is analysis and opinion rather than disclosure of a specific flaw.

Dark Reading·Aug 24, 14:00 UTC · 23d agoIndustry

What vulnerability prioritization looks like when KEV, EPSS, and CVSS disagree

Cohesity field CISO Joye Purser ranks KEV over EPSS over CVSS and urges 24-72 hour patching of exploited internet-facing systems.

In a Help Net Security interview, Cohesity Global Field CISO Joye Purser lays out a vulnerability prioritization framework that puts active exploitation (KEV) first, then exploit likelihood (EPSS), then technical severity (CVSS), adjusted for asset exposure, business criticality, and compensating controls. She endorses 24-72 hour remediation targets for critical exploited internet-facing vulnerabilities and describes the organizational tradeoffs and emergency procedures needed to hit them. The interview also covers honeypot failure modes when deception systems are over-connected or over-trusted, and budget guidance recommending OT/IT segmentation, phishing-resistant MFA, and tested recovery for a 400-person manufacturer.

Help Net Security·Aug 31, 00:00 UTC · 17d agoIndustry

Google Research Releases ToolGrad: Answer-First Framework Hits 99.8% Pass Rate for Tool-Use Data Generation

Google Research and partners introduce ToolGrad, a verified tool-chain-first data generation framework reaching 99.8% pass rate and boosting Gemma-3-12B to 83.1 on BFCL.

Researchers from Google, the University of Tokyo, RIKEN AIP, and Tohoku University released ToolGrad, which inverts query-first tool-use data generation by executing and verifying API chains before annotating them with user queries. On the ToolBench database of 16,000+ APIs, ToolGrad raised generation pass rate from 63.8% to 99.8% while increasing tool uses per sample from 2.1 to 3.4 and cutting tool-use steps from 34.3 to 20.0. Fine-tuning Gemma-3 at 1B, 4B, and 12B parameters on the 500-sample ToolGrad-500 dataset lifted ToolGrad-12B to 83.1 on the Berkeley Function Calling Leaderboard, near Gemini 2.5 Pro at 83.2 and ahead of GPT-5 at 74.4. Code is Apache-2.0, with the dataset, PyPI package, and models available on Hugging Face.

MarkTechPost·Sep 11, 06:01 UTC · 5d agoAI research1

Patch Tuesday to Pentest Wednesday: How an Equipment Rental Company Is Turning Continuous Testing Into Continuous Exposure Management

An equipment rental company uses Horizon3 NodeZero for continuous exposure management, surfacing an SSH key exposure in eight hours versus annual pentesting.

The company moved from periodic penetration testing to continuous exposure management using the NodeZero Proactive Security Platform, feeding telemetry into a Splunk-based CTEM pipeline via Horizon3 APIs. NodeZero exposed SSH RSA key pairs from a PHP web server change about eight hours after introduction and found more findings in 12 hours than a third-party engagement found in roughly 30 days. An Active Directory password audit of 15,000 passwords found about 300 identical or similar compromised passwords, driving a banned-password list, 12-character minimums, service desk changes, and self-service reset rollout; users with similar passwords later dropped from 880 to 209. NodeZero also validated a suspected Cisco vulnerability as exploitable.

Horizon3.ai·Sep 9, 15:58 UTC · 7d agoIndustry

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

What Breaks Under Pruning in Smart Homes, and When? Evaluating LLM Degradation Across Architectures and Task Complexity

Pruning study across four LLM architectures finds dense models degrade sharply on smart-home tool calling while MoE models tolerate far more.

Researchers systematically study pruning-induced degradation in smart-home tool calling across four LLMs spanning dense Transformer, dense hybrid, and mixture-of-experts architectures, combining depth, width, hybrid, and expert pruning methods, and evaluate over 19,500 instances from three datasets after post-pruning supervised fine-tuning. Dense models show narrow safe pruning regions followed by sharp degradation, while MoE models tolerate substantially more pruning. Pruning degrades grounded specificity (operation, device, argument, value) before schema-level intent, and aggressive dense pruning can induce systematic over-refusal.

arXiv cs.AI / cs.LG / cs.CL·Sep 15, 17:51 UTC · 1d agoAI research

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

Knowing What Not to Answer: Selective Non-Compliance in Vision-Language Models

Researchers introduce KoNA, a benchmark exposing vision-language models' failures at selective non-compliance, plus fine-tuning that improves refusal and abstention accuracy.

KoNA is a benchmark for evaluating selective non-compliance in vision-language models across five categories: False Premise, Visual Inaccessibility, Universal Unknown, Task Feasibility and Safety. It tests both query-level and component-level non-compliance using paired single and compound queries, and evaluations across diverse VLMs show models often fail to refuse, correct or abstain appropriately, with failures worsening on compound queries. Fine-tuning VLMs on KoNA examples substantially improves non-compliance accuracy while largely maintaining performance on fully answerable tasks.

Hugging Face daily papers·Sep 3, 20:00 UTC · 13d agoAI research1

Four groups caught using the same Chrome and Windows exploit kit

Proofpoint reports at least four hacking groups, some China-linked, share the BlueMoon exploit kit chaining Chromium and Windows kernel vulnerabilities to install malware.

Proofpoint named the nearly identical kit BlueMoon; it chains two Chromium vulnerabilities with one Windows kernel privilege-escalation flaw affecting Windows 10 (October 2018 Update and 2004), Windows Server 2019 and 2022, and the initial Windows 11 release. All three vulnerabilities received patches within 24 hours of the activity. The kit is being actively used by at least four hacking groups, some with Chinese government ties. Proofpoint links the rapid, visible sharing of a historically rare full browser exploit chain to the Chromium supply-chain patch gap and AI-assisted exploit development.

Proofpoint Threat Insight·Sep 9, 21:19 UTC · 7d agoExploit / PoC in the wild 3 sources1

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

12 Best Patch Management Software Compared (2026): Features & Pricing

GBHackers ranks NinjaOne, ManageEngine, and Automox atop twelve patch management tools for 2026, emphasizing third-party application coverage.

GBHackers scored twelve patch management platforms on coverage, automation, visibility, deployment, and value, with NinjaOne ranked highest at 4.55. Action1 is highlighted for its genuinely usable free tier, ManageEngine for third-party catalog breadth, and Automox for cloud-native cross-OS automation. The piece notes that unpatched known vulnerabilities remain a top initial-access vector, citing CISA's Known Exploited Vulnerabilities catalog.

GBHackers·Sep 10, 08:19 UTC · 6d agoIndustry 4 sources