Search: “d&o”

When AI quietly breaks things, who pays?

Reed Smith partner David Halbreich explains how AI companies can avoid D&O/E&O coverage gaps around mergers, governance warranties, and claims timing.

In an interview, insurance recovery partner David Halbreich of Reed Smith outlines insurance pitfalls for AI companies under claims-made D&O and E&O policies. He highlights 'straddle' claims after mergers that fall between tail coverage and go-forward policies, potentially leaving policyholders with no coverage. He also warns that governance artifacts submitted in insurance applications, such as bias testing records and model cards, can become warranties carriers use to deny claims, and discusses who should answer AI-use questions and how business interruption coverage applies to cloud and compute vendor outages.

Help Net Security·Sep 3, 00:00 UTC · 14d agoAI industry

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·Sep 4, 12:00 UTC · 12d agoThreat actor in the wild1

Hierarchical NeRF with JAX3D for Volumetric Rendering, Novel-View Synthesis, and 3D Reconstruction

MarkTechPost tutorial implements a hierarchical NeRF in JAX using jax3d volume-rendering primitives for novel-view synthesis and 3D reconstruction.

The tutorial builds an end-to-end hierarchical Neural Radiance Field using JAX, Flax, Optax, and jax3d's volume-rendering functions (sample_along_rays, volume_rendering, sample_piecewise_constant_pdf). It implements positional encoding, skip connections, separate coarse and fine networks, and view-direction conditioning with hierarchical importance sampling. Training uses JAX JIT compilation, Adam optimization, exponential learning-rate decay, and gradient clipping. Evaluation covers PSNR, depth and opacity visualization, 360-degree rendering, and marching-cubes geometry extraction.

MarkTechPost·Sep 13, 19:46 UTC · 3d agoAI research

Quoting Rick Brewster

Paint.NET added a clean-room Direct2D rewrite for WINE, largely written by Anthropic's Claude and described as unreviewed 'vibe coded' code.

Rick Brewster says Paint.NET now ships a from-scratch, reverse-engineered Direct2D implementation (PaintDotNet.Windows.Direct2D1.Managed.dll) used under WINE via a /wine flag, since Direct2D was never completed well enough there. He credits the Claude coding assistant with writing most of the code, calling it largely 'vibe coded' and not thoroughly reviewed. Simon Willison shared the quote as an example of shipping AI-assisted systems code in production software.

Simon Willison·Sep 2, 05:50 UTC · 14d agoAI tools & infra1

50% of CISOs see Mythos as a sign to exit the profession

Survey of 1,001 US and UK CISOs finds 50% consider leaving the profession amid AI-driven pressure, personal liability concerns and burnout.

A survey of 1,001 CISOs in the US and UK found 50% say Anthropic's Mythos and similar cyber-capable AI models have made them consider exiting the profession, while 60% say board pressure to adopt AI is outpacing their governance capability. Average CISO tenure is cited at 18 months, and 78% worry about personal liability for security incidents, up from 56% a year earlier. Executives from BlackBerry, Databricks and IDC discuss D&O insurance, agentic security operations and phased low-risk AI adoption as partial responses.

CSO Online·Sep 9, 08:25 UTC · 7d agoIndustry

Knowledge Retention & Sharing in DF/IR

DFIR veteran reflects on knowledge retention and sharing gaps across the industry, from EnCase training to PCI forensics workflows.

A personal essay recounts decades in digital forensics and incident response, arguing the industry rarely moves beyond individual or tribal knowledge to operationalize lessons learned. Examples include building condition files and custom EnScripts for PCI investigations at IBM ISS X-Force, and the lack of shared investigative processes in early-career environments.

Lobsters · security·Sep 10, 09:06 UTC · 6d agoIndustry

Online Learning with LLM Experts from Limited Feedback

Paper proposes bandit algorithms for adaptively routing prompts to LLM experts, minimizing regret under limited feedback budgets.

The paper formulates adaptive prompt routing to K LLM experts as a contextual bandit problem with d prompt features over T rounds. Proposed algorithms strategically select actions and observe rewards, achieving O(dT/m) regret in the full-information setting and O(dTK/m) in the bandit setting, where m is the feedback budget. Experiments demonstrate efficient learning of high-quality routing strategies across diverse LLMs from limited feedback.

Hugging Face daily papers·Sep 4, 20:00 UTC · 12d agoAI research

Suno replaces its AI models with a new one trained on licensed music as copyright suits pile up

Suno launched its v6 model family trained on licensed music from Warner, BMG and Believe as copyright lawsuits from Sony and Universal continue.

Suno unveiled a new model family — Suno v6, experimental v6 wild, and faster v6 mini — trained on licensed data from Warner Music Group, BMG and Believe, and plans to retire older models. New capabilities include prompt-based song editing, use of text/images/video as references, and instrument separation, plus a planned opt-in artist remix program. Suno settled with Warner last year and BMG last month, but still faces suits from Sony, Universal Music Group and artists like Jason Isbell, and has raised over $819 million to date.

TechCrunch · AI·Sep 9, 12:05 UTC · 7d agoModel release

When scanners miss the attack: how Cloudflare Client-Side Security protects storefronts

Cloudflare's Page Shield ML uncovered four malicious JavaScript campaigns on storefronts, including affiliate fraud and a remote-backdoor script, that VirusTotal and URLScan missed.

Cloudflare's Page Shield ML detected four client-side JavaScript operations (eight payloads) in live traffic on online storefronts, enabling affiliate commission hijacking, clickless affiliate theft via hidden iframes, user tracking with a remote-code backdoor, and cloaking of paid mobile visitors. Seven of the eight payloads were absent from VirusTotal and URLScan returned no malicious verdict for any, including a Lnkr-family payload indexed unclassified for roughly 2.5 years. Detection relies on a graph neural network over JavaScript syntax trees, an LLM second opinion on Workers AI, and a frontier-model ensemble voting across benign, magecart, other malware, and cryptomining labels.

Cloudflare Blog·Sep 16, 20:06 UTC · 9h agoMalware in the wild

Governing Bring Your Own AI: A Parameterized Maturity Model

Researchers propose a parameterized governance model and maturity ladder for Bring Your Own AI, finding data exposure and compliance dominate BYOAI risks.

The paper studies Bring Your Own AI (BYOAI), where employees use personal generative AI accounts such as ChatGPT, Gemini, and Claude outside enterprise identity and security controls. Drawing on a curated corpus of 30 records (24 studies and 6 framework documents), the authors build a risk taxonomy, a five-level governance maturity ladder, and a parameterized model linking control-layer coverage to residual risk. Findings highlight data exposure and compliance as the most prominent risks, inconsistent framework engagement, and evidence that layered technical controls reduce modeled exfiltration risk more than prohibition-based approaches.

arXiv cs.CR·Sep 4, 15:03 UTC · 12d agoResearch

Upatre Continued to Evolve with new Anti

Unit 42 analyzes an undocumented Upatre downloader variant with VM detection via process hashing, packed code, disabled Windows defenses and Namecoin .bit C2 domains.

Unit 42 analyzed an Upatre downloader variant compiled in December 2016 that went largely undetected by automated systems, featuring heavy code flow obscuration, on-demand decryption of network communications, and novel virtual machine detection. The sample enumerates running processes, computes CRC32 hashes XORed with a hard-coded key, and sleeps if analysis-related processes such as vmtoolsd.exe or python.exe are found. It masquerades with Google Chrome icons, disables Windows Defender, Firewall and other security services, injects code into msiexec.exe, and resolves .bit Namecoin domains like bookreader[.]bit via hardcoded OpenNIC DNS servers over TCP.

Palo Alto Unit 42·Aug 17, 13:23 UTC · Aug 17, 2026Malware1

Involving before Evolving: A Vision for Trustworthy Enterprise Digital Twin Engineering

Vision paper proposes 'involving before evolving' staged approach for trustworthy enterprise digital twins, validated via an ongoing Michelin prototype.

The paper presents a three-stage vision for enterprise digital twin (EDT) engineering that prioritizes early organizational buy-in before evolving toward federation and full interoperability. The approach combines foundation models for rapid prototyping, an ontological backbone for federated interoperability, and observability tooling to build stakeholder trust. The vision is grounded in an ongoing collaboration with Michelin, where an initial working prototype helped secure stakeholder buy-in.

arXiv cs.AI / cs.LG / cs.CL·Sep 11, 17:06 UTC · 5d agoAI research

2026 Cyber Insurance Trends Report: What's Changed and What You Need to Know

Huntress survey: CIRCIA reporting mandates now live, BEC claims exceed ransomware, exfiltration-heavy attacks cost twice as much, premiums rising.

Huntress's 2026 cyber insurance trends report, based on its own survey, finds 79% of respondents carry cyber insurance while 58% report shrinking coverage over five years. New CIRCIA federal reporting mandates and EU NIS2 requirements are reshaping policies, business email compromise now drives more claims than ransomware, and data exfiltration has replaced encryption as the dominant ransomware tactic at roughly twice the cost. After three years of declining premiums, rates are climbing again, and most businesses now refuse to pay ransoms.

Huntress·Sep 1, 17:00 UTC · 15d agoIndustry1

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·Sep 7, 17:47 UTC · 9d agoAI research

Inside NVIDIA’s cuDNN Graph API: Fusion, Autotuning, and Plan Reuse with cuDNN Frontend

MarkTechPost tutorial walks through NVIDIA's cuDNN Frontend graph API, covering kernel fusion, autotuning, plan reuse, and CUDA graph capture on Colab GPUs.

The tutorial explains how to express GPU computations as operation graphs via the cuDNN Frontend graph API, running the five-step build pipeline of validate, build operation graph, create execution plans, check support, and build plans. It progresses from a single fused convolution with bias and ReLU to autotuning across engine configs, FP8-style epilogues, attention, plan serialization, dynamic shapes, and CUDA graph capture. Each kernel is benchmarked against a PyTorch reference on a single Colab GPU to verify correctness and measure cost. The piece also covers practical setup issues like making libcudnn.so visible to the frontend's dynamic loader.

MarkTechPost·Sep 15, 21:37 UTC · 1d agoAI tools & infra2

Suno releases its first AI music model made with record industry help

Suno released its v6 music model family (v6, v6-wild, v6-mini), the first trained with licensed data from Warner Music Group, BMG, and Believe.

Suno's v6 comes in three variants: v6, the more unpredictable v6-wild, and resource-light v6-mini offered free to all users. The model was trained from the ground up on a new dataset including licensed content from Warner Music Group, BMG, and Believe, plus user data, though it is unclear if all dubiously obtained content was excluded. v6 shows dramatically improved genre fidelity, adds plain-language chat editing of individual song elements, multi-element mashups, and prompts based on images, video, or audio. The Verge notes it still cannot produce intentional imperfections like off-key vocals, and v6 starts rolling out now with older models eventually retired.

The Verge · AI·Sep 9, 21:42 UTC · 7d agoModel release

Optimal Rates for Agentic Networked Information Aggregation

Researchers close the Kearns–Roth–Ryu gap for agentic networked information aggregation, proving excess error is constant up to depth M^2 then Θ(M^2/D).

The paper studies a networked learning model where agents in a DAG each see only a subset of features and pass only their predictions forward. It sharpens the earlier lower bound to Ω(√(M/D)) for depth below M^2 and constructs M-covered paths of depth D ≥ M^2 achieving Ω(M^2/D) excess error, establishing the correct rate for both regression and logistic classification. It also shows excess error contracts geometrically along the path for any fixed distribution, ruling out a single instance that witnesses polynomial lower bounds at every depth.

arXiv cs.AI / cs.LG / cs.CL·Sep 4, 16:12 UTC · 12d 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·Sep 14, 16:41 UTC · 2d agoAI research

Proximity Gaps for Gabidulin Codes and Applications

Researchers prove proximity-gap bounds for rank-metric and Gabidulin codes, enabling the first polynomial commitment scheme framework based on rank-metric error-correcting codes.

The paper proves every linear rank-metric code admits a proximity gap for deltas up to (d-1)/(3n) with error at most q^(e+1)/q^m, and improves the gap to (d-1)/(2n) for Gabidulin codes with error at most 10q^(n-1)/q^m, matching bounds for Reed-Solomon codes. A constructed infinite family of constant-rate Gabidulin codes shows the (d-1)/(2n) bound is tight, and a counterexample establishes a lower bound on the error at the d/(3n) gap. Applications include an IOPP for interleaved Gabidulin codes adapted from the Ligero IOPP and a q-linearized polynomial commitment scheme adapted from Ligero-based PCS, reportedly the first PCS framework based on rank-metric codes.

arXiv cs.CR·Sep 9, 07:45 UTC · 7d agoResearch

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

Clop-Linked Windchill Web Shell Decrypts Credentials and Maps Engineering Data

ReliaQuest details a bespoke JSP web shell that Clop deploys on hacked PTC Windchill and FlexPLM servers after exploiting CVE-2026-12569.

ReliaQuest analyzed a custom Java web shell planted on vulnerable PTC Windchill and FlexPLM servers following exploitation of CVE-2026-12569 (CVSS 9.3). The implant decrypts Windchill keystore credentials including the LDAP manager password, enumerates the file vault for engineering data, and loads attacker-supplied Java classes in memory for post-exploitation. Commands let operators read and delete files, exfiltrate results, and deliver follow-on payloads such as ransomware. Ransom-ISAC, eCrime.ch and Defused previously attributed the campaign to the Clop data-theft extortion group.

The Hacker News·Aug 19, 15:27 UTC · 28d agoThreat actor in the wildCVE-2026-12569

Suno launches v6 music models built with Warner, BMG, and Believe

Suno launches v6, v6-wild, and free v6-mini music models co-developed with Warner Music Group, BMG, and Believe, retiring all older models.

Suno's flagship v6 serves Pro and Premier subscribers, v6-wild targets experimentation, and v6-mini is free; all three understand vocals, instrumentation, structure, mood, and multimodal inputs, with text-based editing of individual song sections. The models were built with Warner Music Group, BMG, and Believe following Warner's November 2025 licensing settlement, while Universal and Sony continue litigating and a Munich court found v3.5 and v4 infringed six works. Suno reports more than 100 million users, over two million paying subscribers, and $300 million ARR after raising $400 million at a $5.4 billion valuation in June.

The Decoder·Sep 9, 14:06 UTC · 7d agoModel release

Testing race conditions with memory access tracing and stack-based delay injection

Google Project Zero released MAccConc, Linux kernel tooling that traces memory accesses to explore and test race condition interleavings.

A Google Project Zero researcher published MAccConc (Memory Access Concurrency), tooling for exploring possible interleavings of multithreaded test cases in the Linux kernel, available on GitHub. The tools use KCOV with ASAN outline-mode instrumentation to record per-access memory traces, enabling automatic testing of all A-B-A interleavings plus terminal and GUI explorers for manual analysis. The work targets confirming race condition candidates, building reliable regression tests, and enabling concurrency fuzzing, drawing on ideas from SKI and Ned Williamson's sockfuzzer.

Google Project Zero·Sep 8, 07:00 UTC · 8d agoResearch2

This Key Will Self-Destruct: An Open Standard for Revocable API Keys

SecurityWeek opinion piece proposes ORKS, an open standard adding issuer prefixes, discovery files, and unauthenticated revocation endpoints to make leaked API keys quickly revocable.

The article argues that plain API keys leak frequently yet lack any standardized revocation mechanism, unlike OAuth tokens which gained RFC 7009 revocation in 2013, and that GitHub's Secret Scanning Partner Program solves this only in a proprietary, invite-only way. The author proposes ORKS (Open Revocable Key Standard), with a draft spec on GitHub, built on four parts: keys embedding their issuer domain in a fixed prefix format, a discoverable /.well-known/api-key-config JSON file, unauthenticated revocation by possession of the full key, and declared constraints such as IP allowlists, expiry, scopes, and mTLS. An optional quarantine mode inspired by Toyota's andon cord restricts a reported key to read-only and throttled operation for a default 24-hour window before automatic revocation. The piece frames AI agents as making this urgent, since agents hold many credentials, can exfiltrate them via prompt injection, and can leak secrets into logs at machine speed.

SecurityWeek·Sep 9, 10:00 UTC · 7d agoTools1

Claude Fable 5.1 Solves the Cyphral Distich, a 370-year-old cipher

Claude Fable 5.1 solved Sir Thomas Urquhart's 370-year-old Cyphral Distich cipher, recovering a hidden royalist prayer for Charles II.

Vals AI reports that Claude Fable 5.1 solved the Cyphral Distich, a 64-number cryptogram from Sir Thomas Urquhart's Logopandecteision unsolved since 1653, in 44 minutes using 176k tokens with no human hints. The key insight was that the cipher's key was the book itself: each number indexes a word in the corresponding Proquiritation, taking the first letter, yielding 'O GOD UPHOLD KING CHARLS THE SECOND AND MAKE HIM THE SUPREME RULER OF THIS LAND'. The model also deciphered the larger Cyphral Octastich (285 numbers) from The Jewel (1652) using page-based word indexing, recovering all but nine letters of a royalist prayer. The puzzle had been listed among Klaus Schmeh's Top 50 unsolved encrypted messages.

Hacker News · AI·Sep 13, 21:06 UTC · 3d agoAI researchHN 63↑ · 6 comments1· 1 read

Necessary or Sufficient? Evaluating LLM Explanations With Behavioural Evidence

New framework tests whether LLM-cited explanation factors are necessary or sufficient, finding weak correlation across Claude, GPT, and Gemini models.

An arXiv paper introduces black-box intervention tests measuring whether factors LLMs cite in their explanations are necessary or sufficient for their outputs in agent oversight workflows. Across eight models from the Claude, GPT, and Gemini families, Spearman correlations between cited rankings and measured influence ranged from 0.349-0.354 (advisor recommendation) to 0.431-0.580 (prompt monitoring). Uncited factors scored above the lowest cited factor in up to 57.6% of advisor responses, showing cited top-three factors do not reliably identify the most influential inputs.

arXiv cs.AI / cs.LG / cs.CL·Sep 4, 17:37 UTC · 12d agoAI safety & security1

The VMs Powering Mobile Agents (Instinct, Claude Code)

A teardown reveals Claude Code runs in Firecracker microVMs with a Rust PID 1 and MITM'd egress, while Instinct rents E2B sandboxes with git-based memory.

The author inspects the virtual machines hosting cloud agents: Claude Code runs in a Firecracker microVM with a custom Rust init (process_api) as PID 1, a 324 MB Bun harness on a read-only disk, and 443-only MITM'd SSE egress to api.anthropic.com with host-rotated OAuth tokens and no inbound access. Instinct rents E2B sandbox-as-a-service Firecracker microVMs (Ubuntu 22.04, 2 vCPU, 1.9 GB RAM) where agent memory is a git repo of Markdown committed by the agent and pushed to S3 as a single bundle, using short-lived STS credentials. Both platforms rely on Firecracker, differing mainly in fleet operator and guest boot configuration.

Hacker News · AI·Sep 8, 04:36 UTC · 9d agoAI tools & infraHN 58↑ · 19 comments1

New AI Attack Hides Malicious Instructions in Normal-Looking Text to Evade Safety Filters

Check Point researchers show crafted prose hides policy-violating instructions that bypass all tested LLM gatekeepers, including GPT-4o mini and Llama Guard 3.

A new prompt-crafting technique embeds malicious payloads inside grammatical, natural-looking text without Base64, invisible Unicode, or obvious encodings, defeating lightweight pre-screening gatekeepers. In testing, all four evaluated gatekeeper models—gpt-4o-mini-2024-07-18, gpt-oss-safeguard:20b, claude-3-haiku-20240307, and llama-guard3:8b—classified the crafted wrappers as safe at a 100% bypass rate across 23 obfuscated prompts. GPT-5 Thinking in high-reasoning mode recovered and acted on the hidden instruction in 17 of 18 tests (~94.4%), often spending over a minute and multiple Python executions. Researchers recommend paraphrasing untrusted input, hardening gatekeeper policies, and applying defense-in-depth controls for agentic deployments.

GBHackers·Sep 11, 05:53 UTC · 5d agoAI safety & security 2 sources

I've factored the RSA keys of a Certificate Authority from the 90s

Security researcher factored two 512-bit RSA root CA keys from defunct 1990s certificate authority E-Certify using CADO-NFS on a desktop in roughly 30 hours each.

A researcher extracted legacy root certificates from archived Netscape and Internet Explorer installers, identifying two 512-bit RSA roots shipped with Netscape 4.51 in 1999 by the defunct Canadian CA E-Certify. Using CADO-NFS on a Ryzen 9 5950X desktop, the keys were factored in 32 and 29 hours respectively, allowing private key reconstruction. The work comes shortly after RSA-260 (862-bit) was factored, the largest known factorization to date. The researcher also built a legacy TLS server and published keys and tools on GitHub.

Hacker News · security·Sep 8, 01:16 UTC · 9d agoResearchHN 411↑ · 86 comments

5 useful things you'll learn in my new post-training textbook (shipping now!)

Nathan Lambert's new RLHF and post-training LLM textbook covers PPO, GRPO, GSPO, CISPO and related techniques, freely available online.

Nathan Lambert's book 'Reinforcement Learning from Human Feedback: Aligning and Post-training LLMs' is now shipping from Manning. It covers policy-gradient algorithms including PPO, GRPO, GSPO, CISPO, and RLOO, plus loss aggregation, truncated importance sampling, asynchronous RL systems, and post-training topics like rejection sampling, outcome reward models, and on-policy distillation. The book is freely available online with a 12-hour course, codebase, and exercises.

Interconnects·Aug 10, 13:02 UTC · Aug 10, 2026AI research

Roland is getting into generative AI music with Melody Flip

Roland launched Melody Flip, a DAW plugin that generates genre-themed MIDI loops rather than complete songs like Suno or Udio.

Roland's Melody Flip is a DAW plug-in offering around 250 genre-based 'Palettes' for generating melodies, chord progressions, basslines, and drum patterns, either from scratch or derived from a reference track. Users can control genre, note density, BPM, and key but cannot use text prompts, and outputs are simple loops with General MIDI-style tones intended for MIDI export into a DAW. The launch follows well-received hardware releases like the SH-4d, Gaia 2, and TR-1000, though music-community sentiment toward generative AI may limit goodwill.

The Verge · AI·Sep 4, 17:51 UTC · 12d agoAI industry

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

numbat - AI agent observability, (Fri, Sep 4th)

SANS reviews Perplexity's open source numbat, a Go-based tool giving security teams observability, detection rules, and enforcement for AI agents like Claude and Gemini.

Numbat, Perplexity AI's open source observability tool, monitors desktop, CLI, IDE, and gateway AI agents through local hooks, OTLP/HTTP logs, and on-disk session artifacts. It ships detection rules mapped to MITRE ATT&CK (e.g., recon.network_sweep / T1046), supports enforcement mode, and packages investigations with SHA256-verified manifests and timelines. The SANS review positions it as a response to unmanaged AI agent and MCP server sprawl highlighted by the OpenAI/Hugging Face incident.

SANS Internet Storm Center·Sep 5, 03:39 UTC · 12d agoAI tools & infra

Beneath the Surface of Chains-of-Thought: A Mechanistic Interpretation of Reasoning Operations in LLMs

Study shows LLM reasoning operations like planning and deduction are geometrically separable in hidden states, with separability peaking in middle layers.

Researchers investigate whether functional reasoning operations — problem formulation, goal decomposition, deduction — have corresponding geometric structure in LLM hidden representations. They find operations are separable in held-out representations with separability peaking in middle layers, ruling out lexical and positional confounds; token-wise operation alignment becomes more distributed across layers, and identical surface tokens are represented differently depending on their surrounding chunk. Attention-masking interventions show chunk-onset operation-aligned representations depend on preceding reasoning context; code is released on GitHub (naver-ai/beneath-cot).

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

Capitol Hill wants to know if executive branch, foreign allies coordinated enough to combat scams

CyberScoop·Aug 6, 20:27 UTC · Aug 6, 2026Phishing & fraud in the wild

Safety for Whom? Boundary-Aware Self-Distillation for Controlled LLM Safety Refusal

A self-distillation safety framework tunes narrow-boundary refusals in Qwen3-8B, raising target-domain refusal to 84.75% while cutting over-refusal from 15.20% to 5.20%.

The paper formulates narrow-boundary safety, where deployments need refusals within specific topics rather than whole subjects, and proposes an offline self-generated framework with controlled topic generation, escalating retries, and harmful-benign boundary pairs. On political persuasion with Qwen3-8B, the method raised target-domain refusal from 9.47% to 84.75% and cut the mean unsafe-response rate across three broader benchmarks from 26.26% to 0.14%. Verified target-model responses reduced over-refusal from 15.20% to 5.20%, and boundary-pair data cut comply-side over-refusal on held-out pairs from 32.94% to 4.16%. Results show data composition controls the safety-usability trade-off and alignment should be evaluated on both sides of the refusal boundary.

Hugging Face daily papers·Sep 2, 20:00 UTC · 14d agoAI safety & security1

Growing Up The Hard Way

The Hacker News·Aug 7, 11:55 UTC · Aug 7, 2026Vulnerability1

Grok exfiltrates user data when malicious instructions are encrypted

Researchers show Grok can be made to exfiltrate user data via Cryptographic Context Injection, a newly documented technique that bypasses LLM safety guardrails.

According to Ars Technica, Grok exfiltrates user data when malicious instructions are encrypted, a technique called Cryptographic Context Injection. The method is described as the latest documented way to break LLM safety guardrails, showing that encrypted content can carry hidden instructions past safeguards. The finding underscores gaps in how large language models validate and execute context from external sources.

Ars Technica · Security·Aug 20, 13:00 UTC · 27d agoAI safety & security1

Operation RapidRust: APT36 Deploys RUSTYSHADE, RUSTYMOVE, PSNATCH, and BASHNATCH

Zscaler details Operation RapidRust: APT36 deploys four new tools including RUSTYSHADE, a Rust backdoor using private GitHub repos for encrypted C2.

Zscaler ThreatLabz documents Operation RapidRust, a campaign by Pakistan-aligned APT36 deploying four new tools: RUSTYSHADE, a 64-bit Rust Windows backdoor that uses attacker-controlled private GitHub repositories with a hardcoded PAT and AES-256-GCM-encrypted messages for C2; RUSTYMOVE; PSNATCH, a PowerShell file stealer that scans Office documents, archives, media, and databases modified in the last 120 days and exfiltrates up to 5 GB per run to per-machine GitHub repositories; and BASHNATCH. The backdoor was dropped via PowerShell from attacker-controlled Backblaze B2 storage and supports screenshots, webcam capture, file listing, downloads, and shell command execution.

Zscaler ThreatLabz·Sep 16, 15:13 UTC · 14h agoThreat actor in the wild

Four in Five AI Tools Run with No IT Oversight, New Research Finds

Reco's research finds four in five AI tools run without IT oversight, linking expanding shadow AI usage to a surge in vulnerability disclosures.

Reco's new report states that roughly 80% of AI tools in organizations operate with no IT or security oversight. The research connects growing shadow AI adoption to an increasing number of vulnerability disclosures. The findings highlight governance gaps created by employees deploying unsanctioned AI services.

Infosecurity Magazine·Aug 26, 13:00 UTC · 21d agoAI safety & security