Search: “ece”

A Ranking Approach for Measuring Calibration

Researchers propose rankECE, a ranking-based calibration error measure with theoretical guarantees that outperforms binned ECE approximations.

The paper introduces rankECE, an alternative to Expected Calibration Error (ECE) that measures miscalibration by comparing points with neighboring predicted-probability values. It addresses the impossibility of estimating ECE with guaranteed accuracy in assumption-free settings. Theoretical guarantees and empirical results establish rankECE as a better proxy for ECE than the binned approximations most commonly used in practice.

arXiv cs.AI / cs.LG / cs.CL·Sep 11, 17:34 UTC · 4d agoAI research1

Evaluating the NIST Bugs Framework Against CWE as a Successor for Automated Vulnerability Classification

NIST Bugs Framework evaluation shows it is more structured and automation-friendly than CWE for automated vulnerability classification, with gaps in attribute guidance.

The paper evaluates NIST SP 800-231's Bugs Framework (BF) against CWE as a target for automated CVE classification using a systematically screened corpus of CVE-to-CWE research. An inter-rater study with 2 subject-matter experts mapping 13 CVEs showed strong agreement on BF's cause and operation axes but only fair agreement on the attribute axis. Automated classification was tested across two LLM deployments under different budgets, and findings support BF as more structured and automation-friendly than CWE, though gaps include under-specified attribute guidance and missing fix commits for closed-source software.

arXiv cs.CR·Sep 14, 23:18 UTC · 1d agoResearch1

Drowning in CVEs and thirsty for answers? Try CTEM

Sponsored Register piece argues traditional vulnerability management cannot scale with CVE volume and promotes Continuous Threat Exposure Management via Horizon3's NodeZero.

The sponsored article cites surging CVE volumes, CVSS triage shortcomings, NVD backlog, and AI-driven discovery accelerating an asymmetric vulnerability cycle. It outlines Gartner's five CTEM steps - scoping, discovery, prioritization, validation, and mobilization - and describes how Horizon3's NodeZero automated pentesting validates exploitable attack paths with evidence. Horizon3 says NodeZero uses a deterministic machine learning expert system rather than general LLMs, limiting generative AI to scoped tasks via AWS Bedrock.

The Register · Security·Sep 3, 15:00 UTC · 13d agoIndustry

The History Is the Detector: Executing CVE Patch History, End-to-End

BUGSTONE-E2E converts CVE patch history into executable LLM-guided detection rules, yielding 1,033 rules and 644 runtime-verified findings across 14 programs.

The BUGSTONE-E2E framework mines reusable detection rules from verified fixing commits, organized by CWE and language, and applies them through a funnel pipeline that escalates from Tree-sitter anchors and lightweight heuristics to LLM-based agent inspection, runtime verification, and scope-checked patch generation. Built from 19,325 high-severity CVEs published 2022-2026, it produced 1,033 detection rules spanning 56 CWE families, packaged into 172 skills. Applied across 14 programs, it generated runtime evidence for 644 findings, demonstrating that vulnerability history can drive reproducible detection and repair.

arXiv cs.CR·Sep 4, 16:40 UTC · 11d agoResearch

Toward an Empirical Probabilistic Risk Manifestation Model of Organizational Cybersecurity in SMEs

Empirical study of 22 SME security assessments builds a probabilistic risk model and shows assessments can be cut 24-45% while retaining most critical findings.

Researchers analyzed 281 validated security findings from 22 real-world SME cybersecurity assessments conducted over two years via a pro bono university clinic. They derived an empirical Risk Manifestation Model linking eight organizational security functions to two exposure conditions, five attack mechanisms, and six outcome categories, using probability propagation to identify dominant risk pathways. The dominant pathway runs from asset exposure to credential compromise to unauthorized access, stable under leave-one-organization-out analysis. Retaining six functions reduces assessment burden by 24% while preserving 97% of critical findings; five functions cut burden 45% while preserving 89% of critical findings.

arXiv cs.CR·Sep 14, 01:15 UTC · 2d agoResearch

UltraViolet Cyber Equinox measures detection coverage against MITRE frameworks

UltraViolet Cyber launches Equinox, an AI-automated platform mapping SIEM and EDR detection coverage against MITRE ATT&CK and ATLAS frameworks.

UltraViolet Cyber announced Equinox, a detection engineering platform from its TIDE team that maps existing detections and log sources against MITRE ATT&CK and MITRE ATLAS. It performs coverage analysis in under 30 minutes and recommends vendor or custom detections to fill gaps, with engineers reviewing and backtesting each recommendation. In one customer trial, mapped technique coverage rose from 59 of 222 techniques (26.6%) to 136 of 222 (61.3%) without increasing alert volume.

Help Net Security·Sep 15, 13:33 UTC · 1d agoTools2

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 · 8d agoAI research

Batten the Hatches: Cybersecurity with Military Mariners

Interviews with 20 U.S. Navy and Coast Guard mariners reveal informal, safety-oriented shipboard cyber risk models that may delay attribution and containment.

The study conducts semi-structured interviews with 20 military mariners from U.S. Navy and Coast Guard vessels to understand how service members recognize and respond to cyber risk aboard ships. Unique consequences of compromising military systems identified include weapon takeover and purposeful geopolitical escalation. Cybersecurity is organizationally abstract on ships, so mariners build cyber risk models from informal experience rather than formal instruction. A safety-oriented incident-response model creates resilience but may delay cyber attribution and containment.

arXiv cs.CR·Sep 11, 13:04 UTC · 5d agoResearch

The EU CRA's Real Question: What Shipped, and When Did You Know?

ActiveState argues the EU CRA's 24-hour ENISA exploit-notification duty, effective September 11, 2026, makes current SBOMs and provenance visibility a legal necessity.

An ActiveState essay warns that the EU Cyber Resilience Act's reporting obligations take effect on September 11, 2026, requiring manufacturers of products with digital elements sold into the EU to notify ENISA within 24 hours of learning a vulnerability is actively exploited, with a fuller report within 72 hours. The law's engineering requirements only apply from December 11, 2027, leaving a visibility-first runway, and Article 13 requires the SBOM to stay current unlike one-time artifacts generated under US Executive Order 14028. The author contrasts the 24-hour notification clock with an industry-average 55 days to remediate high or critical vulnerabilities and recommends automated SBOM regeneration or consuming pre-vetted, attested open source components.

BleepingComputer·Sep 8, 20:24 UTC · 7d agoPolicy & legal

Curriculum Learning as Transport: Understanding Curricula with Wasserstein Geodesics

Researchers model curriculum learning as Wasserstein transport over difficulty distributions, finding curriculum benefits are strongly task- and budget-dependent with no dominant strategy.

The framework represents curricula as trajectories of training distributions over discrete difficulty levels, decoupling ordering, matched exposure, endpoint smoothness, and pacing. Across a calibrated suite of 12 tasks and 33 difficulty axes under fixed training budgets, no single strategy dominates, though easy-to-hard ordering improves hard-level performance relative to exposure-matched static sampling. Endpoint smoothness and pacing substantially affect where along the difficulty spectrum a curriculum is effective, and the transport view supports extensions to learned pacing and structured difficulty spaces.

arXiv cs.AI / cs.LG / cs.CL·Sep 8, 17:39 UTC · 7d agoAI research1

Anthropic Adds Plugin Evals to Claude Code: 6 Grader Types, a No-Plugin Baseline, and a CI Gate for Skills

Anthropic ships a plugin evals workflow for Claude Code with six grader types, a no-plugin baseline arm, and a CI gate via threshold and cost flags.

Anthropic published a plugin evals workflow for Claude Code, exposed via the "claude plugin eval" command on v2.1.269+. Six grader types exist: regex, tool_used, tool_order, and file_exists are free transcript checks, while llm and baseline invoke a billed judge model. Every case runs with and without the plugin, and the delta (Δ) isolates the plugin's contribution; a Δ near zero with a failing tool_used:Skill grader indicates the skill never triggers. CI gating uses --threshold 0.8, --max-cost-usd, --trust-plugin, and --no-publish flags, with results written to a report.html under evals/results/.

MarkTechPost·Sep 11, 21:05 UTC · 4d agoAI tools & infra2

NATO and an AI startup can now name and track software vulnerabilities

CyberScoop·Aug 10, 19:50 UTC · Aug 10, 2026Vulnerability in the wild

[AINews] AEF-1 standard emerges for Third Party Evaluators, as Xai, OpenAI, and Anthropic all cosign

xAI, OpenAI, and Anthropic cosign the AEF-1 third-party evaluation standard while Dario Amodei proposes embedded evaluators for safety verification.

The AI Evaluator Forum published AEF-1, a baseline standard for independent third-party AI evaluations covering access, conflicts of interest, funding relationships, recusal, and transparency, cosigned by xAI, OpenAI, and Anthropic. Dario Amodei wrote a rare personal blogpost proposing embedded evaluators such as METR with desks, badges, company laptops, and internal-risk-team-level access to verify safety commitments, plus democratic and global coordination frameworks. The roundup also covers the pacing debate: Bilal Chughtai left Google DeepMind arguing progress may outrun alignment, while critics including Aidan Gomez and Cohere push back against slowdowns and lab gatekeeping. Additional items include Cline Desktop's launch with open-weight model support.

Latent Space·Sep 15, 04:50 UTC · 1d agoAI safety & security

Erlang security advisory (AV26-870)

Canada's Cyber Centre warns that multiple Erlang/OTP versions are affected by vulnerabilities and urges administrators to apply updates.

The Canadian Centre for Cyber Security issued advisory AV26-870 on September 1, 2026, noting vulnerabilities affecting Erlang OTP across multiple versions. The bulletin contains no CVE identifiers or exploitation details and directs users and administrators to Erlang's own security advisories to apply necessary updates.

Canadian Centre for Cyber Security·Sep 1, 18:50 UTC · 14d agoAdvisory

When the prompt becomes the payload: A practical pen-testing guide for GenAI, LLM and RAG applications

CSO Online publishes a practical penetration-testing guide for GenAI, LLM, and RAG applications, covering prompt injection, retrieval poisoning, and tenant isolation testing.

The guide frames LLM applications as attack graphs spanning prompts, retrieval layers, vector stores, tools, identities, and downstream APIs, arguing that conventional web testing misses instruction-vs-data channel risks. It builds on OWASP prompt injection guidance (direct vs. indirect injection) and NIST's 2025 adversarial machine-learning taxonomy, noting that RAG and fine-tuning do not remove injection risk. Recommended practices include documenting trust transitions across components, using canaries and synthetic records to avoid test side effects, running multi-turn and obfuscated injection campaigns, and verifying chains from poisoned documents to observable state changes. It also details testing RAG pipelines via controlled document poisoning across metadata, OCR layers, and code comments, plus cross-tenant isolation checks on retrieved document IDs.

CSO Online·Sep 9, 10:00 UTC · 7d agoAI safety & security1

CTEM Is Not About the Stages. It’s About the Outcome.

Horizon3 argues CTEM programs should measure continuously reduced exposure rather than mapping technologies to Gartner's five stages.

Horizon3 contends that Continuous Threat Exposure Management should be judged by one outcome: continuously reducing attacker-reachable exposure, not by mapping a technology to each of Gartner's five stages. The post argues validation and verification, not visibility or closed tickets, provide evidence that attack paths are actually broken. It describes a Discover, Validate, Prioritize, Remediate, Verify, Repeat motion as its operationalization of CTEM.

Horizon3.ai·Sep 2, 13:11 UTC · 14d agoIndustry

Webinar: Learn How to Answer “Are We Exposed?” Faster After a New CVE

Tines will host a September 2026 webinar showing security teams how to combine SBOM, endpoint, cloud, and vulnerability data into one exposure assessment workflow.

The Hacker News published a contributed webinar announcement from Tines titled "Outpacing AI-Era Attacks Starts With Faster Time to Answer." Tines Co-founder Thomas Kinsella and Senior Security Operations Engineer Andrew Katz will demonstrate connecting SBOM data, endpoint application data, cloud inventory, and vulnerability feeds into a single interactive exposure view. The session also covers pairing AI-assisted analysis with deterministic, reviewed automation to reduce time from CVE disclosure to exposure determination.

The Hacker News·Sep 9, 11:57 UTC · 7d agoIndustry

Enterprise Applications Carry 4.31x More Critical and High Vulnerabilities

Sonatype reports enterprise applications contain 4.31x more critical and high-severity vulnerabilities as accelerated software creation drives rising vulnerability levels.

Sonatype's analysis found enterprise applications carry 4.31 times more critical and high-severity vulnerabilities. The report links rising vulnerability levels to accelerated enterprise software creation. The findings are part of Sonatype's software supply chain research coverage reported by Infosecurity Magazine.

Infosecurity Magazine·Aug 18, 15:00 UTC · 29d agoIndustry

GNU security advisory (AV26-923)

Canadian Cyber Centre advisory AV26-923 flags a stack overflow in GNU libextractor before v1.15 via OLE2 files.

The Canadian Centre for Cyber Security issued advisory AV26-923 on September 15, 2026, covering CVE-2026-91752, a stack overflow vulnerability in GNU libextractor versions prior to 1.15 triggered via OLE2 file parsing. The Cyber Centre encourages users and administrators to review the provided links and apply necessary updates as they become available.

Canadian Centre for Cyber Security·Sep 15, 15:10 UTC · 1d agoAdvisoryCVE-2026-91752

EU's Cyber Resilience Act starts the 24-hour vulnerability clock

EU Cyber Resilience Act reporting rules take effect, requiring manufacturers to disclose actively exploited vulnerabilities to ENISA within 24 hours, with fines reaching €15 million.

The Cyber Resilience Act's Article 14 mandatory reporting duties became applicable, requiring makers of products with digital elements sold in the EU — regardless of where they are based — to file an early warning within 24 hours of becoming aware of an actively exploited vulnerability, a detailed notification within 72 hours, and a final report within 14 days of releasing a fix. Reports must be submitted through ENISA's Single Reporting Platform to the designated CSIRT, and non-compliance with these core duties can trigger fines up to €15 million or 2.5 percent of annual turnover. Manufacturers must also inform affected users of available fixes without undue delay, and most remaining CRA provisions, including mandatory SBOMs and security-by-design requirements, become applicable on December 11, 2027.

The Register · Security·Sep 11, 11:34 UTC · 5d agoPolicy & legal

Who Should Grade My Work? Student Perspectives on Transparent AI-Assisted Writing Assessment in Higher Education

A Saudi university study finds students value ChatGPT writing feedback but treat human instructors as the final grading authority.

Thirteen male undergraduate computing students at a Saudi public university completed handwritten writing tasks that were scored by ChatGPT using a rubric-based prompt, then reflected after being told the score and feedback were AI-generated. Inductive thematic analysis identified four themes: perceived feedback usefulness, awareness of AI's contextual and pedagogical limitations, conditional trust, and reflection on the instructor's institutional role. Participants accepted GenAI feedback for surface-level revision but consistently positioned human instructors as the authority over grading decisions, distinguishing feedback utility from evaluative authority.

arXiv cs.AI / cs.LG / cs.CL·Sep 4, 16:49 UTC · 11d agoAI research

The Next Model Won’t Fix This: Three AppSec Imperatives From Black Hat USA 2026

Checkmarx-funded study discussed around Black Hat USA 2026 found frontier models produce working code 83-95% of the time but only 24-36% of solutions meet the study's requirements.

A study initiated and funded by Checkmarx, highlighted in the vendor's Black Hat USA 2026 takeaways, evaluated frontier models on real-world software repository tasks. The models produced working code 83-95% of the time, but only 24-36% of their solutions passed the study's criteria, underscoring a gap between functional and acceptable output. Checkmarx uses the findings to argue that AppSec teams need process-level controls now rather than waiting for improved models.

Checkmarx·Aug 17, 13:55 UTC · Aug 17, 2026AI safety & security

CISA Warns of Chromium Type Confusion 0-Day Vulnerability Actively Exploited in Attacks

CISA added the actively exploited Chromium V8 type confusion zero-day CVE-2026-85046 to its KEV catalog, urging patching of Chrome, Edge, and Opera.

CISA added CVE-2026-85046, a V8 type confusion flaw (CWE-843) in Chromium-based browsers, to its Known Exploited Vulnerabilities catalog. A remote attacker can trigger arbitrary code execution inside the browser sandbox via a specially crafted HTML page. Google Chrome is directly affected, and Microsoft Edge, Opera, and other Chromium-based browsers may also be impacted depending on their V8 version. Google has released a Stable channel Chrome update, and CISA directs mitigations under Binding Operational Directive 26-04.

Cyber Security News·Sep 8, 16:25 UTC · 7d agoExploit / PoC in the wildCVE-2026-85046

GuardBreaker: Derailing AI-assisted malware analysis with a code comment

ESET names 'GuardBreaker': UAC-0099 embeds a nuclear-weapon question in VBScript comments to trip LLM scanner guardrails during analysis of its MATCHBOIL loader.

ESET researchers observed the Russia-aligned group UAC-0099 inserting a decoy prompt injection into a VBScript used to install its MATCHBOIL loader in an attack against a Ukrainian target, aiming to make LLM-based code scanners refuse and stop inspecting the file. The comment triggers safety guardrails with a request about building a nuclear weapons but has no runtime effect. Similar LLM-thwarting tricks have appeared in malicious PyPI and npm packages reported by Socket and StepSecurity. ESET recommends multi-model cross-validation of AI-assisted analysis and treating missing LLM output as requiring further checks.

ESET WeLiveSecurity·updated Sep 11, 14:32 UTC · 5d ago·first Sep 10, 09:00 UTC · 6d agoAI safety & security 3 sources1

Expert-Space Exploration in MoE Reinforcement Learning

ESRL explores MoE expert-routing space during RL, lifting Qwen3-30B-A3B Pass@1 by 3.2 points over GRPO at no extra cost.

ESRL (Expert-Space Exploration Reinforcement Learning) is an architecture-aware framework that treats expert routing in Mixture-of-Experts models as an additional source of rollout diversity. It preserves high-confidence experts as anchors, restricts stochastic routing to a plausible candidate pool, adapts perturbation strength to router entropy, and replays recorded expert paths during policy optimization. ESRL achieves the best performance across top-K, top-1, and shared-expert routing backbones on mathematics, science, and code tasks; on Qwen3-30B-A3B it improves average Pass@1 and Pass@8 over GRPO by 3.2 and 4.5 percentage points respectively, without additional sampling or compute.

arXiv cs.AI / cs.LG / cs.CL·Sep 11, 16:58 UTC · 4d agoAI research 2 sources

NCP-ArchPreview Technical Report: Moving towards Latent Space Language Models through Next Concept Prediction

An 8.9B-parameter latent-space language model using next-concept prediction matches OLMo-3-7B pretraining loss with only 51.3% of the training tokens.

NCP-ArchPreview augments next-token prediction with Next Concept Prediction over a product-quantized concept vocabulary built from hidden states, trained jointly end-to-end. The 8.9B model was trained on 5.73T tokens from the Dolma-3 dataset, the largest latent-space language model demonstration to date. It consumes 51.3% of the tokens to reach OLMo-3-7B's final pretraining loss and outperforms it by 2.45 points on the downstream macro-average, including a 5.99-point GSM8K gain. The learned latent space also enables lightweight domain adaptation via a 17M-parameter VQ module and improves speculative drafting accepted length by 4.17%.

Hugging Face daily papers·Sep 8, 20:00 UTC · 7d agoAI research1

HazardAuditor: From Executable Threats to Safer Computer-Use Agents

HazardAuditor trains execution-grounded guard models for computer-use agents, improving safety verdict accuracy by up to 16.5 points.

HazardAuditor runs heterogeneous agents (Claude Code, Codex, Hermes, OpenClaw) in controlled environments and normalizes their interactions into a canonical event representation for cross-framework supervision. It introduces Guard Policy Optimization (GuardPO), which converts deterministic safety outcomes into sequence-level advantages and normalizes rationale and verdict regions so the safety decision becomes the effective optimization unit. Across multiple benchmarks and heterogeneous computer-use systems, HazardAuditor improves accuracy by up to 16.5 percentage points over the strongest prior guard model. Code, models, and evaluation artifacts are being released.

Hugging Face daily papers·Sep 13, 20:00 UTC · 2d agoAI safety & security

Keys to the Kingdom: Erlang/OTP SSH Vulnerability Analysis and Exploits Observed in the Wild

Attackers actively exploit CVE-2025-32433, a CVSS 10.0 unauthenticated RCE in Erlang/OTP SSH, heavily targeting OT and critical infrastructure networks.

CVE-2025-32433 enables unauthenticated RCE in Erlang/OTP's SSH daemon via SSH connection protocol messages (codes >= 80) processed before authentication, affecting versions before OTP-27.3.3, OTP-26.2.5.11 and OTP-25.3.2.20. Unit 42 recorded a spike in exploitation between May 1-9, 2025, with 70% of detections on firewalls protecting OT networks, disproportionately affecting healthcare, agriculture, media and high technology. Observed payloads bind TCP-connected shells or launch Bash reverse shells to hosts like 146.103.40.203:6667, with randomized DNS lookups under dns.outbound.watchtowr.com indicating OAST-driven blind RCE validation.

Palo Alto Unit 42·Aug 17, 13:03 UTC · Aug 17, 2026Exploit / PoC in the wildCVE-2025-32433

Online Exam Tool Suffers Data

An online exam tool reportedly suffered a data breach, potentially exposing student or user information, according to Infosecurity Magazine.

Infosecurity Magazine published a report indicating that an online examination platform suffered a data breach. The available metadata does not include the vendor name, number of affected users, or the types of data exposed. Scope and impact cannot be fully assessed without the full article text.

Infosecurity Magazine·Aug 17, 00:00 UTC · Aug 17, 2026Data breach

Disruptive cyber activity highlights risk from internet-exposed systems and edge devices

NCSC links disruptive cyber activity to internet-exposed systems and edge devices, urging OT owners to fix avoidable vulnerabilities and improve resilience.

The UK's NCSC issued guidance following disruptive cyber activity that highlights the risk to internet-exposed systems and edge devices. It encourages owners of operational technology to remediate avoidable vulnerabilities and invest in long-term cyber resilience. The notice underscores that exposed edge devices remain a common entry point for attackers against OT environments.

NCSC UK·Aug 27, 12:00 UTC · 20d agoAdvisory in the wild

An Empirical Security Analysis of Open-Source Software Used in Onboard Satellite Systems

Study of 126 onboard satellite OSS repositories finds 2,827 security findings, 72% medium severity or higher, dominated by memory safety and code quality weaknesses.

Researchers performed an empirical security analysis of 126 public repositories of open-source software used in onboard satellite systems using SBOM generation, software composition analysis, static application security testing, infrastructure-as-code analysis, and secret scanning. After cleaning and deduplication the pipeline produced 2,827 findings, with medium-severity findings accounting for 49% and 72% classified medium or higher. A CWE-based taxonomy mapped all findings to eight weakness families, with Memory Safety and Code Quality dominating, followed by Input Validation and Injection. Project-developed code accounted for 81.4% of findings, though external dependency code remained relevant; findings do not establish mission-specific exploitability.

arXiv cs.CR·Sep 14, 11:54 UTC · 2d agoResearch1