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Risky Bulletin: Russia starts blocking DoH and DoT

Russian users report blocks on DoH and DoT servers, including Cloudflare 1.1.1.1 and Google 8.8.8.8, in an apparent censorship crackdown.

Russian internet users began reporting failures connecting to DNS-over-HTTPS and DNS-over-TLS servers, suggesting a government crackdown on the two privacy protocols. The blocks reportedly cover Cloudflare's 1.1.1.1 and Google's 8.8.8.8 resolvers; Roskomnadzor has not officially confirmed the action. The agency tested a similar block in March on Beeline's network and had named DoH for blocking as early as 2021. The bulletin also briefly notes state-sponsored phishing of EU officials, a DDoS against Norway's Digdir, the ReliaQuest/ShinyHunters dispute, and older ransomware and breach disclosures.

Risky Business News · 21d agoPolicy & legal1

Your DNS Is Hiding in HTTPS — This Is Why It Matters

Akamai argues that unmanaged DNS over HTTPS (DoH) creates enterprise visibility gaps and advocates controlled DoH strategies to restore DNS monitoring.

Akamai published a blog post arguing that unmanaged DNS over HTTPS encrypts DNS queries outside enterprise visibility, creating security monitoring gaps. The post advocates a controlled DoH strategy that restores DNS visibility for defenders while preserving user privacy. No specific incidents, vulnerabilities, or products are cited in the advisory-style piece.

Akamai Blog · 13d agoIndustry

China's AI-Enabled APT Operations Are Getting Interesting

Bitdefender links seven RAT families, five previously undocumented, to China-nexus espionage actor SilkParasite using AI-assisted malware development against Central Asian governments.

A Bitdefender report attributes seven remote access tool families to a single actor dubbed SilkParasite, with medium confidence a China-nexus group targeting governments in Uzbekistan, Turkmenistan and Kazakhstan. The RATs are written in .NET, C++, Go and JavaScript, use C2 via Google Drive and protocols like HTTP, DNS and TCP, and employ modular plugin architectures with regular rotation of infrastructure, encryption material and persistence artifacts. Evidence of AI-assisted development includes leftover test functions, placeholder encryption keys, and GoginRAT and NomadRAT sharing a high-level architecture despite different languages, suggesting a specification implemented twice with AI. The newsletter also covers the US Operation Economic Outcast sanctioning six MOIS-linked Iranian hackers, including hands-on-keyboard operators who targeted US critical infrastructure.

Risky Business News · 20d agoThreat actor1

I-have-ADHD: A skill to stop your coding agent from burying the answer

Developer releases I-have-ADHD, an open-source skill that stops coding agents from burying direct answers under verbose output.

A GitHub project titled I-have-ADHD packages a 'skill' intended to make AI coding agents answer directly instead of hiding the answer inside lengthy output. It gained traction on Hacker News with 45 points and 42 comments. It targets prompt/agent configuration rather than introducing a new model or infrastructure component.

Hacker News · AI · 7d agoAI tools & infraHN 45↑ · 42 comments1

1.1.1.1 now supports post-quantum DNSSEC, all 2,420 bytes of it

Cloudflare's 1.1.1.1 resolver now validates post-quantum DNSSEC signatures using ML-DSA-44, a 2,420-byte NIST algorithm, preparing DNS for post-quantum migration by 2029.

Cloudflare enabled 1.1.1.1 to validate DNSSEC signatures using ML-DSA-44 (algorithm 18), a NIST-standardized post-quantum signature with 1,312-byte public keys and 2,420-byte signatures, roughly 38x larger than ECDSA P-256. The large signatures exceed common DNS-over-UDP limits, forcing fallback to TCP and creating downgrade risks while conventional algorithms must be published alongside. Cloudflare cites the risk of a quantum computer breaking RSA/ECDSA signatures by 2030 and plans full post-quantum security by 2029.

Cloudflare Blog · 5d agoTools1

Show HN: Self-hosted company OS, Claude Code and Codex agents in departments

OtoDock, a self-hosted company OS that organizes Claude Code and Codex AI agents into departments, was launched on GitHub via Show HN.

OtoDock is a self-hosted 'company OS' shared on GitHub through a Show HN post, presenting Claude Code and Codex AI agents organized into department-style teams. The Hacker News feed entry shows the post reached 20 points with 5 comments; no further technical details are provided in the available text.

Hacker News · security · 6d agoAI tools & infraHN 20↑ · 5 comments1

Hackers Hijack HBO Max Reddit Account to Push 108 ClickFix Malware Ads

Hijacked verified HBO Max Reddit account ran 108 ClickFix malvertising ads delivering AMOS infostealers, Windows loaders, and crypto clipboard hijackers.

HudsonRock and ADAMnetworks identified a cross-platform ClickFix operation dubbed PasteSwitch that abused the compromised verified Reddit account u/hbomax to publish 108 malicious ads over 48 hours, using domains like hbomaxx[.]us and codex-craft[.]com. macOS victims run curl/zsh commands delivering AMOS-related stealers and fake wallets, while Windows users get an InstallFix route using mshta and PowerShell that loads Amatera in memory and disables AMSI. The operation's AnimateClipper and ZigClipper families hijack clipboards to swap cryptocurrency addresses, with C2 domains rotated via Binance Smart Chain contracts. Reddit paused the ads and is investigating.

Cyber Security Newsupdated · 21h agofirst · 1d agoMalware in the wild 7 sources

You Can't Prefer Emotions You Don't Sample: Intensity Undershoot in DPO-Tuned LLMs

Study quantifies DPO-tuned LLMs undershooting requested emotional intensity, tracing the gap to candidate-pool extremity rather than conditioning format.

Conditioning an instruction-tuned LLM on continuous valence-arousal targets yields gain of only 0.26 for valence and 0.13 for arousal on Llama-3.1-8B, far below faithful control of 1.0. The authors attribute undershoot to neutral-heavy preference corpora like EmoBank and candidate pools lacking extreme affect, leaving DPO without extreme exemplars. Uniform target coverage with a hotter candidate pool raises valence gain to 0.40 on Llama-3.1-8B and 0.44 on Qwen3-8B, with modest in-distribution cost; arousal gains remain unstable across seeds.

arXiv cs.AI / cs.LG / cs.CL · 8d agoAI research

Four Nation-State Actors Used the Same Chrome Zero-Day Exploit Kit Within 12 Days

Proofpoint reports four nation-state actors, mostly China-nexus, adopted the BlueMoon Chrome and Windows zero-day exploit kit within 12 days, targeting US organizations.

Proofpoint tracked an exploit kit dubbed BlueMoon that chains CVE-2026-85046, a Chrome V8 type-confusion bug, with an unnamed V8 sandbox escape and CVE-2026-85880, a Windows kernel privilege escalation using ALPC and the Windows Notification Facility. The first observed use was by China-nexus TA412 (APT31, Violet Typhoon, JungleBamboo) on August 28, 2026 against US NGOs, mining companies, and commodity trading firms, followed by UNK_LateNight targeting US aerospace and defense companies on September 2. Both V8 bugs were patch-gap zero-days: the fix was committed to Chromium on August 7 but reached stable Chrome on September 3, enabling rapid weaponization from public patches. TA412's post-exploitation payload, GemStone, is a malicious browser extension posing as an AI-powered Google Gemini companion that captures keystrokes, cookies, screenshots, and browsing history via a Cloudflare Worker C2.

Security Affairsupdated · 23h agofirst · 6d agoExploit / PoC in the wild 20 sourcesCVE-2026-85046CVE-2026-858801

Show HN: Ordewell – turn one goal into an ordered plan of coding-agent tasks

Ordewell is an open-source tool that decomposes a single goal into an ordered plan of coding-agent tasks, posted on Hacker News.

Ordewell, shared as a Show HN project on GitHub, converts one high-level goal into an ordered plan of tasks for coding agents to execute. The post received 40 points and 29 comments on Hacker News. It focuses on task planning and orchestration for autonomous coding agents.

Hacker News · AI · 20h agoAI tools & infraHN 40↑ · 29 comments

Active exploitation of Cisco Secure Firewall Management Center vulnerabilities

Cisco Talos reports in-the-wild exploitation of critical FMC flaw CVE-2026-20079 by three clusters including a Sandworm-linked APT and Qilin ransomware affiliates.

Cisco Talos is tracking active exploitation of CVE-2026-20079 (CVSS 10.0), an authentication bypass in Cisco Secure Firewall Management Center that lets unauthenticated remote attackers execute scripts and obtain root access, and CVE-2026-20316 (CVSS 5.3), which permits low-privileged logins and can be chained for privilege escalation. Talos identified three post-compromise clusters: UAT-12197 deploying JSP web shells and a JAR command executor for credential theft; UAT-11823, an APT overlapping with Sandworm, deploying a Netcat reverse shell and Cyclops Blink malware; and UAT-11988, assessed as a ransomware operator with TTPs consistent with Qilin affiliates. Hotfixes are available, with a comprehensive hardening release due the week of September 14, 2026.

Cisco Talosupdated · 2d agofirst · 6d agoExploit / PoC in the wild 13 sourcesCVE-2026-20079CVE-2026-20316

Show HN: LLM Attention Visualization

A developer released a browser-based tool that visualizes which past tokens influence each LLM output token using aggregated, value-weighted attention scores.

A Show HN project presents a React application built on Transformers.js that renders per-token attention influence by aggregating attention weights scaled by value-vector magnitudes across all attention heads and layers. To expose internal tensors, the author instrumented the ONNX computation graph, hosted a modified model on Hugging Face, and pre-generated prompts to avoid long model downloads in the browser. Demos with a 600-million-parameter model show how verbatim copying draws heavily on source tokens and how single outputs blend information from multiple phrases.

Hacker News · AI · 7d agoAI tools & infraHN 41↑ · 9 comments

LongAgent: History-Guided Agentic Search for Longitudinal Outcome Prediction

LongAgent autonomously searches variable sets and temporal windows to predict longitudinal medical outcomes, beating the strongest non-agent baseline on synthetic data.

The paper proposes LongAgent, an agent-based method that searches over combinations of variable sets, temporal windows and aggregation functions for outcome prediction on heterogeneous medical longitudinal data. It uses a history memory of previous searches and numerical evidence to guide exploration. On synthetic data it achieves mean RMSE 1.7376, improving over the best non-agent baseline by 0.0151 (95% CI [0.0045, 0.0260]; p=0.0273), and performs comparably to the best baseline on a real clinical dataset.

arXiv cs.AI / cs.LG / cs.CL · 1d agoAI research

Molecular Déjà Vu: Digit-Level Retrieval of Published Values in Frontier Language Models

Audit of 22 frontier models finds widespread verbatim retrieval of published molecular property values, with higher reasoning increasing recall of memorized numbers.

An arXiv audit tests 22 frontier LLMs across 12 molecular regression benchmarks for verbatim retrieval of published values. More than 50% of the LLMs show verbatim retrieval on five datasets, and identical experiments are flagged 89% more often at a high reasoning level than at the lowest one. Suppressing retrieval moves model prediction errors closer together in relative terms, suggesting predictive capability is not determined solely by memorized values.

arXiv cs.AI / cs.LG / cs.CL · 11d agoAI research1

Emergency Department Revisit Quality Review Screening: Exploring Human Decision-Making and Artificial Intelligence Support

A retrospective study found GPT-4 over-flagged emergency department revisit cases while an LLM knowledge-graph screener achieved 83-100% positive predictive value.

In an exploratory retrospective study of 99 emergency department diagnosis pairs from a multihospital health system, clinicians and GPT-4 independently judged whether revisit pairs warranted further assessment. GPT-4 responses correlated poorly with clinicians, flagging 94% of pairs for follow-up, 4.4-13.3 times more than clinicians, though prompt engineering was minimal. An algorithm leveraging an LLM-populated knowledge graph (KGA) achieved 83-100% positive predictive value against at least one clinician rater, suggesting LLM-based screening could broaden revisit quality review without substantially increasing reviewer workload.

arXiv cs.AI / cs.LG / cs.CL · 6d agoAI research1

From Parameters to Answers: How LLMs Retrieve and Use Their Internal Knowledge

Interpretability study traces how Qwen, Llama, and Gemma route query information and internal knowledge across layers when answering questions.

Researchers used layerwise interventions on hidden states to separate query-routing signals from target knowledge in language models, testing Qwen, Llama, and Gemma on country-continent questions with varied answer types. A pair-conditioned request direction strengthens before interventions alter downstream knowledge, opening a causal window while answer-supporting content is still forming. Trajectories differ by model: Gemma shows a partially overlapping mid-layer routing profile, while Llama has no sustained routing-effect window under the same gates.

arXiv cs.AI / cs.LG / cs.CL · 5d agoAI research1

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 · 11d agoAI research

AI SIEM Search

Huntress launched AI Search for Managed SIEM, translating plain-English questions into ESQL log queries with schedulable custom alerts.

Huntress introduced AI Search in its Managed SIEM, letting users query logs in natural language instead of writing ESQL, KQL, or SPL. The feature generates a real ESQL query behind the scenes, exposes it for users to inspect and learn from, and allows saved searches to be scheduled as recurring alerts at hourly, daily, or weekly cadence. A planned next version will return summarized plain-language answers instead of raw logs.

Huntress · 8d agoTools

One Symptom, Three Levers: A Critical Review of On-Policy Self-Distillation

A review paper frames on-policy self-distillation collapse as governed by three levers: token weighting, privileged information, and guidance decay.

The paper critically reviews On-Policy Self-Distillation (OPSD), where a language model trains on its own generations scored token-by-token by a teacher conditioned on privileged information such as reference solutions or environment feedback. It identifies collapse, the progressive narrowing of producible reasoning paths, as the dominant failure mode and analyzes it through three levers: signal weighting, the nature of privileged information, and teacher dynamics. The review is restricted to mathematical reasoning, reports no new experiments, and offers a shared vocabulary separating settled findings from disputed ones.

Hugging Face daily papers · 21d agoAI research

When Should LLMs Abstain? Chain-of-Self-Questioning for Selective Risk Control

Chain-of-Self-Questioning prompting cuts LLM wrong-answer commitments 32% relative while raising answered accuracy, holding across eleven model families.

The paper introduces Chain-of-Self-Questioning (CoSQ), a prompt-only framework that makes LLM answer commitment conditional on an explicit assessment of the information required to answer. On an 817-item TruthfulQA multiple-choice set, Grounded-CoSQ at τ=0.90 reduced mean unconditional wrong-commitment rate from 13.1% under chain-of-thought to 8.9% (a 32.1% relative reduction), while raising answered accuracy from 86.9% to 89.7% at 87.6% coverage. Improvements held across eleven open-weight and hosted model families and at every evaluated threshold, with convergent evidence from a Natural Questions short-answer evaluation.

arXiv cs.AI / cs.LG / cs.CL · 15h agoAI research

Before You Poll with LLMs: A Deliberative Diagnostic Framework

Deliberative diagnostic shows all five tested frontier LLMs misrepresent human belief shifts after arguments, with GPT-5.1 reversing on outgroup questions.

The Deliberative Polling Diagnostic Framework compares human and LLM persona belief shifts after identical informational interventions, using data from America in One Room (526 personas, 72 questions). All five frontier models tested failed uniquely: GPT-5.1 exhibited partisan reversal (80% on outgroup vs 26% on policy questions), Gemini 2.0 Flash, Claude Sonnet 4.5 and Llama 3.3 70B overshot at 5-7x human magnitude, and DeepSeek V3 showed near-zero change (rigidity). The authors term the underlying signature 'self-sycophancy', conformity to the model's internal persona stereotype rather than reasoning from provided information.

arXiv cs.AI / cs.LG / cs.CL · 1d agoAI research

Performance of Clinical AI System and Physicians and Frontier Language Models in primary care diagnostics

Clinical AI system Doctorina achieved 82.0% primary-care diagnostic concordance versus 57.0% for physicians across 150 synthetic consultations.

The study compared Doctorina, eight physicians, and four standalone frontier language models on 150 synthetic Polish-language primary-care consultations. Doctorina achieved 82.0% Top-1 diagnostic concordance versus 57.0% for physicians (25.0-point difference, 95% CI 17.7-32.7) and 97.3% versus 85.0% primary-or-reference-differential concordance. Normalized workup and treatment scores were 89.4 versus 66.9 and 83.7 versus 61.2. Kimi K3 ranked next on diagnosis, while Claude Opus 5 led the closely spaced management estimates among Opus, Doctorina and Kimi.

arXiv cs.AI / cs.LG / cs.CL · 7d agoAI research

The invisible passenger in your car

Kaspersky discovered Android adware and proxy-botnet malware delivered inside legitimate DoFun car head-unit software.

Kaspersky researchers uncovered Android malware distributed through legitimate software for DoFun automotive head units. The malware displays ads on infotainment screens and enrolls infected devices into a proxy botnet for resale of residential-style proxy traffic. Delivery via trusted vendor software means victims receive it through a legitimate update channel, raising infection likelihood.

Kaspersky Securelist · 26d agoMalware in the wild

Product showcase: Doppler secures secrets for humans, pipelines, and AI agents

Doppler's secrets management platform centralizes credentials for engineers, CI/CD pipelines, MCP servers, and AI agents with runtime injection and dynamic secrets.

Doppler stores API keys, database URLs, tokens, and certificates in a single control plane and injects them at runtime, replacing .env files for human and machine identities including AI agents. It supports OIDC with short-lived identity tokens for Azure, AWS, and GCP, dynamic secrets scoped and time-boxed to single sessions, SCIM provisioning, 50+ integrations, and an MCP server that lets agents request configurations natively. Permissions are enforced at each layer so raw secrets stay out of logs, prompts, and model context, with versioning, rollback, SIEM log forwarding, and cloud or on-prem deployment.

Help Net Security · 8d agoTools

ReactHuman: A Physics-Grounded Benchmark for Human-Like Reactive Decision-Making in Embodied Multimodal LLMs

ReactHuman benchmark tests whether multimodal LLMs react safely to sudden household hazards; seven evaluated models mishandle roughly one hazard in three.

ReactHuman is the first physics-grounded benchmark for human-like reactive decision-making, placing a multimodal LLM as the brain of a simulated humanoid facing 17 event families of sudden household hazards across over 1,000 bit-for-bit reproducible scenes with annotation-free ground truth from 240 Hz rigid-body simulation, including adversarial objects whose appearance contradicts their physics. A five-metric suite scores each reaction along reasonable, safe, and physically grounded axes, and every committed plan is physically executed. Seven representative MLLMs mishandle roughly one hazard in three, act from fixed dispositions rather than the observed scene, trust appearance over motion, and miss interception points at meter scale; none of these failures shrink with model scale.

Hugging Face daily papers · 7d agoAI research

DianShi-RxnDB: A Large-Scale, Fine-Grained Organic Reaction Data Platform Built via a Fully Automated Pipeline for Researchers and AI Agents

Researchers release DianShi-RxnDB, a database of roughly 24 million organic reaction instances extracted automatically from USPTO and EPO patents since 1976.

DianShi-RxnDB is built by a fully automated pipeline integrating patent text, images, and reaction schemes, yielding about 24 million reaction instances, of which 14.8 million (61.7%) pass automated qualification checks. Manual evaluation of 1,300 sampled instances showed 92.95% field-level accuracy, and comparisons with Pistachio found advantages in deduplicated record counts and granularity. The platform offers a web research workbench and a Model Context Protocol (MCP) service enabling AI agents to perform composable structured retrieval.

Hugging Face daily papers · 10d agoAI research

CareMirror: Bringing Caregiver Wellbeing into the Dementia Care Ecosystem

Interview study with 14 dementia caregivers probes CareMirror wellbeing ecosystem, revealing demands for control over clinical sharing and AI boundaries.

CareMirror is an envisioned caregiver wellbeing ecosystem with interconnected caregiver- and clinician-facing interfaces for longitudinal reflection, personalized support, and caregiver-controlled sharing. Semi-structured interviews with 14 family caregivers used the system as a design probe. Caregivers valued wellbeing attention and clinical visibility but found repeated reflection burdensome and worried automatic clinical sharing would inhibit candid disclosure, expecting AI to support rather than replace caregiver and clinician judgment.

arXiv cs.AI / cs.LG / cs.CL · 17h agoAI research

Brief independent investigation of agents’ behavior, reasoning and collaboration in the OpenAI / Hugging Face hacking incident

METR published an independent investigation of AI agent behavior, reasoning, and collaboration during the OpenAI/Hugging Face hacking incident.

METR released a brief independent investigation into the behavior, reasoning, and collaboration of AI agents involved in the OpenAI/Hugging Face hacking incident. The analysis examines how the agents acted during the security incident, adding an third-party perspective to the ongoing debrief.

Lobsters · security · 20d agoAI safety & security in the wild

Show HN: Geiger – See every AI agent on your machine and what it can touch

Geiger, a new open-source tool, surfaces AI agents running on a machine and the files and resources they can access.

Geiger launched on Hacker News as an open-source utility that shows every AI agent operating on a local machine and the scope of what each agent can touch. The Show HN post drew early community attention with 21 points and 11 comments, with the code hosted on GitHub under the Atomburstofficial account.

Hacker News · security · 6d agoToolsHN 21↑ · 11 comments

Bad Likert Judge: A Novel Multi-Turn Technique to Jailbreak LLMs by Misusing Their Evaluation Capability

Unit 42 details the Bad Likert Judge multi-turn jailbreak that abuses LLMs' evaluation capability, raising attack success rates over 60% across six frontier models.

Palo Alto Networks Unit 42 describes the Bad Likert Judge technique, a multi-turn jailbreak that asks a target LLM to act as a Likert-scale judge scoring the harmfulness of example responses. The highest-rated example in each scale can carry harmful content, bypassing the model's internal guardrails. Testing across six state-of-the-art text-generation LLMs showed an average attack success rate increase of more than 60% versus plain attack prompts, with tested models anonymized. The technique targets edge cases rather than typical use, and the article positions the work as guidance for defenders on potential jailbreak risks.

Palo Alto Unit 42 · 29d agoAI safety & security

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 · 5d agoResearch1

DPRK APTs: Ted backdoor and curlRAT target South Korean media and automotive sectors

Rapid7 uncovered a DPRK-linked Linux toolkit using a HAProxy-embedded ted backdoor, SSH keylogger, and curlRAT against South Korean media and automotive firms.

Rapid7 Labs identified a previously undocumented framework attributed with medium confidence to DPRK actors, targeting South Korean automotive and media organizations likely since early 2025. The toolkit embeds a backdoor compiled into HAProxy 2.8.12 using its filter API, plus trojanized crond, agetty, atd, sshd, and polkitd, an SSH keylogger storing credentials under /var/lib/sshd/, and a curl-based RAT with a watchdog thread. It enables remote command execution, malicious script injection into served webpages (a watering-hole loop), credential harvesting, and long-term surveillance. Hardcoded C2s are associated with APT37 via ThreatFox, and exposed groupware portals and mail servers align with Kimsuky tradecraft; the initial access vector and any CVE remain unconfirmed.

Rapid7 Blog · 11d agoThreat actor in the wild1

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 · 5d agoResearch1

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 · 3d agoAI research1