Search: “eagle-3”

Speculative Decoding in vLLM on AMD GPUs

vLLM benchmarks speculative decoding on AMD Instinct MI300X and MI355X GPUs across five drafting methods including EAGLE-3 and native MTP.

The vLLM project documents draft-and-verify speculative decoding support for AMD GPUs via ROCm, comparing native MTP, Gemma 4 MTP, EAGLE-3, DFlash, and DSpark drafting approaches. Output-token throughput effects varied with drafting method, proposal length, model family, draft checkpoint, workload, and acceptance behavior. The post also covers how to enable each method plus practical tuning and observability considerations.

Hacker News · AI·Sep 7, 09:26 UTC · 9d agoAI tools & infraHN 141↑ · 52 comments1

Finland appeals court revives case against Eagle S Officers over cable breaks

Finnish appeals court ruled Finland can prosecute Eagle S officers for 2024 Baltic Sea cable breaks, reviving the case and EUR 105M damages claims.

The Helsinki Court of Appeal ruled Finland has jurisdiction to prosecute three senior officers of the Eagle S, the Russia-linked tanker that severed multiple subsea cables on December 25, 2024, overturning a district court dismissal. The court found the crew's conduct after Finnish authorities made contact was not a 'maritime accident' under the UN Convention on the Law of the Sea, noting the ship dragged its anchor roughly 90 kilometers and cut four more cables. Owners of the Estlink 2 power cable, Fingrid and Elering, are seeking about EUR 105 million ($122 million), and the ruling will guide the related Fitburg anchor-dragging case. The decision can be appealed to Finland's Supreme Court until October 26, 2026.

The Record·Aug 27, 15:32 UTC · 20d agoPolicy & legal

[AINews] OpenAI shuts off Cursor

OpenAI cut off API access to coding tool Cursor after its SpaceX acquisition, citing contract violations by Elon Musk's companies.

OpenAI disabled Cursor's access following the closing of Cursor's acquisition by SpaceX, citing its experience with Elon Musk's companies violating contracts; Cursor responded that OpenAI accounts for only 5% of its traffic. The weekly digest also covers major open-weight releases: Z.ai's GLM-5.3 (744B total/40B active, 1M context) and Tencent's Hy4-preview (770B/49B, ~#5 on Code Arena WebDev), plus Alibaba's Qwen3.8-Flash (125B/6B). vLLM published benchmarks showing no universal winner among speculative decoding methods across model families.

Latent Space·Aug 29, 05:11 UTC · 18d agoAI industry

What Fal.Con 2026 Reinforced: AI Makes Proving Exposure More Important Than Ever

Horizon3's Fal.Con 2026 recap argues AI-accelerated vulnerability discovery makes continuous attacker-based exposure validation essential for defenders.

In a Fal.Con 2026 recap, Horizon3 argues that AI is compressing the time between vulnerability discovery and exploitation, making attacker-derived evidence about real exploitability the key prioritization signal. Horizon3 announced it joined CrowdStrike's Project QuiltWorks, with NodeZero exploitability intelligence flowing into Falcon Next-Gen SIEM and Falcon Fusion SOAR workflows able to trigger NodeZero 1-Click Verify for remediation testing. The company reported running over 1,200 NodeZero demos during the show, and CrowdStrike CEO George Kurtz's keynote framed AI red teaming and offense-informing-defense as central themes.

Horizon3.ai·Sep 4, 17:46 UTC · 11d agoIndustry

Edge0/Edge0-35B-A3B-preview — new model trending #30 on Hugging Face

Edge0 released a 35B sparse MoE model running in under 3 GiB of memory at 15 tok/s via SSD expert offload and int4 quantization.

Edge0-35b-a3b-preview is a 35B-parameter MoE (256 experts, 4 active per token) built on Qwen3.5-MoE 35B-A3B, shipped as a 4-bit checkpoint with LoRA and prerouter adapters under Apache 2.0. The edge0 framework streams expert weights from SSD on demand, bounding peak active memory at 2.9 GiB and achieving 14.9-17.7 tok/s decode on a Mac mini M4 Pro (MLX backend). Recover-LoRA distillation keeps the int4 model within 3.9 points of its fp16 base (79.2 vs 83.2 average on OpenCompass benchmarks including AIME 2026, HumanEval, GPQA-Diamond, MMLU-Pro, and IFBench).

Hugging Face trending models·Sep 8, 13:56 UTC · 8d agoModel release

Mercator ↔ Equal Earth

Simon Willison used GPT-6 Astra (medium) in ChatGPT Work to build an animated D3 transition between Mercator and Equal Earth map projections.

Willison built an animated transition between the Mercator and Equal Earth map projections using D3. The tool was generated by GPT-6 Astra (medium) in ChatGPT Work. Equal Earth is a projection recently voted on at the UN. The post is a vibe-coding demonstration rather than a security or major model event.

Simon Willison·Sep 7, 16:24 UTC · 9d agoAI tools & infra1

Project CAV3RN continues: Google Apps Script as C2 relay and DNS-based C2 channel selection

Project CAV3RN continues targeting Israel, using Google Apps Script C2 relays and DNS-based channel routing in a .NET NativeAOT framework.

Kaspersky Securelist documents the continuation of Project CAV3RN operations against Israel. The modular .NET NativeAOT framework uses Google Apps Script as a C2 relay and DNS-based C2 channel selection, blending command traffic with legitimate Google services to evade detection.

Kaspersky Securelist·Aug 11, 10:00 UTC · Aug 11, 2026Threat actor in the wild

I tested 10 model/harness combinations on the same Three.js task

A developer benchmarked 10 model/harness combinations on a Three.js task; Qwen 3.8 27B on OpenCode scored 95.64% fastest at 8m48s.

The author ran an identical Three.js sci-fi hangar build prompt across 10 model/harness combinations and recorded score, tokens, durations, and tool errors. Qwen 3.8 27B x-high on OpenCode achieved 95.64% in 8m48s, the best fast result, while GLM 5.3 Flash Max on OpenCode scored highest at 96.89% in 20m28s. Other runs included GLM 5.3 Flash, Luna 5.6, SOL 5.6, and Astra 6.0 across Codex Open, OMP Open, OpenCode, DSH, and PTC harnesses, with scores ranging from 78.54% to 96.89%.

Hacker News · AI·Sep 8, 03:42 UTC · 8d agoAI researchHN 104↑ · 61 comments

Latest open artifacts (#24): Motif-3, GLM-5.3, Hy4-preview and open model licenses

Interconnects surveys new open models—Motif-3, GLM-5.3, Hy4-preview—while analyzing a licensing split: Western labs opening up, Chinese frontier labs getting restrictive.

The roundup covers Motif-3 (MIT license, strong scores for its size), GLM-5.3 (switched from MIT to a custom license with a $10 billion revenue threshold and undefined 'affiliates' clause requiring Z.AI security review), and Tencent's Hy4-preview (competent but prone to overthinking). It also notes dots3-note-prev from RedNote/Xiaohongshu (won IMO 2026 with a perfect score), Qwen3.8-Flash-Next (125B-A6B with GDN and Qwen Sparse Attention), NVIDIA Nemotron-3.5-Lightning-30B-A3B-BF16, and Ling-3.0-flash. The core theme: Google and Meta adopted Apache 2.0 while Chinese frontier labs (Zhipu, Kimi K3, MiniMax M3) adopted restrictive commercial licenses.

Interconnects·Sep 8, 14:15 UTC · 8d agoAI research

The Model Proposes, the Code Disposes: A Pre-Registered Ablation of a Verifier-and-Acceptance Stage in an LLM-Orchestrated Offensive-Security Agent

Pre-registered ablation finds a model verifier stage in an LLM offensive-security agent suppresses findings; removing it eliminated suppression with precision tradeoff.

The paper evaluates a verifier-and-acceptance stage in an LLM-orchestrated offensive-security agent via a pre-registered 20-run confirmatory ablation and a 2x2 factorial study with 40 runs on vulnerable lab targets. Removing the stage eliminated pre-report suppression (median 2 vs 0 findings, p = 0.00003) but reduced model-blinded shipped precision (0.471 vs 0.353, p = 0.0087). Suppression was attributed to the model verifier rather than deterministic acceptance rules, and an instrumented canary recorded zero external contacts in all 60 runs. The full design retained 93.8% of model-adjudicated true candidates but failed its pre-registered non-inferiority floor of 0.90.

arXiv cs.CR·Sep 14, 17:13 UTC · 2d agoResearch

Threat Brief: 3CXDesktopApp Supply Chain Attack (Updated)

Trojanized 3CXDesktopApp installers for Windows and macOS loaded RC4-encrypted shellcode delivering a backdoor to hundreds of thousands of 3CX users.

Threat actors compromised the 3CXDesktopApp build process, adding malicious libraries (ffmpeg.dll, d3dcompiler_47.dll) to installers downloaded from the developer's website. The Windows MSI loader decrypts embedded shellcode with RC4, sleeps for a random 1-4 weeks, then beacons to C2 hidden in icon files on GitHub. Unit 42 fingerprinted 247,277 IPs across 199 countries using 3CX applications and blocked shellcode execution at 127 Cortex XDR customers between March 9-30, 2023.

Palo Alto Unit 42·Aug 17, 12:18 UTC · Aug 17, 2026Threat actor in the wild1

Persistent Attempts at Cyberespionage Against Southeast Asian Government Target Have Links to Alloy Taurus

Alloy Taurus (GALLIUM) compromised Southeast Asian government networks from 2022 to 2023 using Exchange web shells and undocumented .NET backdoors Reshell and Zapoa.

Unit 42 tracked persistent multiwave intrusions at a Southeast Asian government starting in early 2022 and continuing through 2023, attributing the activity with moderate confidence to Alloy Taurus (aka GALLIUM), a Chinese state-aligned espionage group. Attackers exploited Exchange Server vulnerabilities to deploy web shells including China Chopper, then ran reconnaissance with Fscan and WebScan, created administrative accounts, and installed undocumented .NET backdoors named Reshell and Zapoa. They established resilience by installing SoftEther VPN, brute-forced Active Directory credentials with Kerbrute, and dumped credential stores with GoDumpLsass and LsassUnhooker. The campaign reflects long-term espionage tradecraft to maintain a foothold.

Palo Alto Unit 42·Aug 17, 10:54 UTC · Aug 17, 2026Threat actor in the wild1

Mars Security Debuts Automated Threat Engine Processing Live Cyber Intelligence Into Validated Rules Within Minutes

Mars Security launches Real-Time Intel-Based Detection, converting threat intelligence advisories into validated, ATT&CK-mapped detection rules within minutes for SOCs.

Mars Security, an autonomous threat hunting and detection engineering platform founded by former offensive security operators, announced Real-Time Intel-Based Detection. The capability ingests advisories from sources like CISA, Mandiant, Unit 42, and Microsoft Threat Intelligence, maps indicators to MITRE ATT&CK, and authors native query logic across connected infrastructure including CrowdStrike Falcon, Wiz, Splunk, Sysmon, identity providers, Snowflake, and Databricks. Every rule is backtested against 30 days of historical telemetry to quantify false positives before analyst approval and one-click deployment. The feature is free for existing customers and available via AWS Marketplace.

CSO Online·Sep 8, 15:05 UTC · 8d agoTools2

Google releases Gemini 3.8 Flash, its third Flash model in six weeks

Google releases Gemini 3.8 Flash, topping the DeepSWE coding leaderboard six weeks after 3.7 Flash, alongside the cybersecurity-focused 3.8 Flash Cyber.

Google shipped Gemini 3.8 Flash, its third Flash model in six weeks, placing it at the top of the DeepSWE software engineering leaderboard. The companion Gemini 3.8 Flash Cyber showed a reported 2.6x patch accuracy increase for the Chrome security team and found a critical vulnerability in two hours, but is limited to trusted testers and governments. Gemini 3.8 Flash improved over 3.7 Flash on the OSWorld-2.0 computer-use benchmark yet remains far behind Claude Opus.

Ars Technica · AI·Sep 2, 18:13 UTC · 13d agoModel release1

Security Data Isn’t the Problem. Security Context Is.

Horizon3 blog argues security context, not data volume, is the SOC bottleneck, promoting its NodeZero integration with CrowdStrike Falcon Next-Gen SIEM.

Horizon3.ai published a vendor blog explaining how its NodeZero Proactive Security Platform integration with CrowdStrike Falcon Next-Gen SIEM brings validated exposure findings into existing security operations workflows. The post argues SOCs are now limited by confidence rather than visibility, needing context to decide which issues matter. It cites a global chemical manufacturer that validated exploitable exposures with NodeZero before completing a $2 billion merger.

Horizon3.ai·Sep 15, 13:12 UTC · 1d agoTools

How Fragile Is Safety Alignment at Frontier Scale? A Single-Direction Attack on a 320B MoE

Researchers show directional ablation breaks refusal in GLM-5.3-Flash, a 320B-parameter MoE, cutting refusal by 41–89 points across seven benchmarks.

The study extends directional ablation, a white-box attack that removes an aligned LLM's refusal behavior, from dense models up to ~70B parameters to GLM-5.3-Flash, a 320B-parameter mixture-of-experts model with 288 routed experts, four-wide hyper-connection residual, and block-FP8 quantization. Editing attention, dense, and routed-expert writers jointly removes 0.776 of refusal, with 74% of the effect existing only under the joint intervention; the conventional module-name-based recipe reaches only 0.066 and fails silently on MoE architectures. The attack yields 41–89 percentage-point reductions in refusal across seven harmful benchmarks with no detected capability change, and a category-concentrated refusal residue survives all edits at ranks 1 to 12.

arXiv cs.CR·Sep 9, 06:48 UTC · 7d agoAI safety & security

The AI Malware Maturity Gap

Recorded Future introduces AIM3, a five-level maturity model for AI malware, showing current attacker AI use is mostly AI-assisted rather than autonomous.

Recorded Future proposes AIM3, a five-level model defining AI malware from LLM-translated to LLM-embedded, spanning experimentation to fully autonomous agentic campaigns. Public examples remain early-stage: PROMPTFLUX uses Google Gemini to rewrite its VBScript dropper (Level 1), while Lamehug/PROMPTSTEAL, attributed to APT28, invokes the HuggingFace API to generate reconnaissance commands (Level 3). The authors argue most current AI malware augments existing tradecraft rather than enabling one-click autonomous attacks.

Recorded Future·Aug 26, 00:00 UTC · 21d agoResearch

The Pelican comparison grid for Astra is pretty interesting

Simon Willison's pelican SVG comparison shows GPT-6 Astra producing markedly better images than GPT-5.6 Sol, Terra, and Luna across reasoning levels.

Willison generated pelicans-riding-bicycles SVGs with newly accessed GPT-6 Astra at low through max reasoning levels and rendered them in a comparison grid against GPT-5.6 Sol, Terra, and Luna. Astra's outputs were markedly more coherent, while even the best GPT-5.6-Sol images remained largely abstract shapes. Astra does not support a reasoning=none setting, so all comparisons involved reasoning-enabled runs.

Simon Willison·Sep 4, 23:59 UTC · 11d agoAI research

[AINews] Muse Spark 1.3 matches GPT-5.6-Sol, confirming Meta Superintelligence as the newest Frontier Lab, >90% discount for training

Meta's Muse Spark 1.3 reportedly ranks as the world's #3 model, matching frontier models from OpenAI and Anthropic with planned open weights.

The Latent Space AI News roundup leads with Muse Spark 1.3, promised in Zuckerberg's letter, which ranks #3 worldwide per AAII, is slated for open weights, and uses a pricing model over 90% cheaper when users opt in to training. The issue also covers the rumored Gemini 3.8 Flash launch and analysis arguing OpenAI's rumored looped-transformer 'Astra' architecture is a modest tweak rather than a breakthrough. Additional coverage includes ByteDance Seed's HarnessDev harness-evaluation benchmark, a retrieval-invoked actual-use evaluation method, Stanford's revamped agent engineering curricula, and Photon 2.1 adding TTS models and NVIDIA B200 support.

Latent Space·Sep 3, 04:38 UTC · 13d agoModel release1

[AINews] Fal’s H3 Max Live breaks the infinite videogen barrier

Fal post-trained MiniMax H3 into a 'Max' variant with 35x-faster inference, enabling faster-than-realtime AI video generation and infinite streams.

Fal post-trained MiniMax's H3 model into a 'Max' variant and optimized it for its in-house inference engine, achieving roughly 35x the speed of the official endpoint. The optimization enables faster-than-realtime video generation, demonstrated by an infinite interactive AI-generated stream productized by levels.io. The roundup also notes Meta Muse Code's general availability with an SDK, open DeepSeek-V4-Flash-Vision-Exp weights, GLM-5.3-Flash's strong agentic cost/performance rankings, and Tencent's 770B-parameter Hy4 Preview MoE with 49B active parameters.

Latent Space·Sep 1, 04:36 UTC · 15d agoAI industry

Mars Security Launches Real-Time Intel-to-Detection Engine That Turns Live Threat Intelligence Into Backtested Detections in Minutes

Mars Security launched Real-Time Intel-Based Detection, converting advisories into MITRE ATT&CK-mapped, backtested detection rules for CrowdStrike, Wiz, and Splunk within minutes.

The capability turns newly published threat intelligence from CISA, Mandiant, Unit 42, and Microsoft Threat Intelligence into validated detection rules within minutes, each backtested against 30 days of the customer's own telemetry before deployment. Rules are written in native query languages across CrowdStrike Falcon, Wiz, Splunk, firewalls, Linux Sysmon, identity providers, AWS telemetry, and data lakes such as Snowflake and Databricks, with no data ingestion or stack changes. The feature is available at no additional cost to existing customers and on AWS Marketplace. Mars also flags detection coverage gaps and extends monitoring to credentials leaked by AI coding agents.

Cyber Security News·Sep 8, 13:20 UTC · 8d agoTools1

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

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

NERVE Attacks: Breaking AI-Powered Brain-Computer Interfaces

Researchers characterize NERVE, five attack dimensions against AI-powered brain-computer interfaces, and release the EEGle framework uncovering 17 attack instances.

NERVE is a systematic attack class spanning the BCI stack across five orthogonal dimensions: Neuro-mimetic Forgery, Evasion via Desynchronization, Replay-based Hijacking, Vein Tapping, and Embedded Backdoors. The accompanying EEGle framework enables AI-assisted, extensible BCI security analysis and helped uncover 17 novel neuro-specific attack instances, revealing a stealth-effectiveness spectrum unique to BCI backdoor design. The authors show generative AI lowers the barrier to entry for non-expert attackers and release EEGle to the community.

arXiv cs.CR·Sep 8, 16:20 UTC · 8d agoResearch

Sevii APS Module preempts attacks with autonomous cyber defens

Help Net Security·Aug 4, 00:00 UTC · Aug 4, 2026Exploit / PoC

Google’s Gemini 3.8 Flash takes on bigger AI models at a lower cost

Google released Gemini 3.8 Flash with a security-focused Cyber variant that produces 2.6x more correct patches and found a critical vulnerability in under two hours.

Google launched Gemini 3.8 Flash for developers and a gated Gemini 3.8 Flash Cyber model reserved for vetted security teams through the new Fairwind program. The company says the model beats most larger frontier models on the DeepSWE v1.1 engineering benchmark at lower cost, and Chrome Security reports the Cyber variant produced 2.6 times more correct patches than the best commercial models while Google's Cloud Vulnerability Research team found a critical foundational vulnerability in under two hours. The models show significant prompt-injection robustness gains measured by Gray Swan and carry CBRN misuse safeguards, with cyber-offense restrictions on the standard version. Pricing matches Gemini 3.7 Flash at $0.75 per million input tokens and $3.75 per million output tokens.

Help Net Security·Sep 3, 00:00 UTC · 13d agoModel release

Mars Security brings threat intelligence to detection in real time

Mars Security launched Real-Time Intel-Based Detection, converting advisories from CISA and Mandiant into backtested MITRE ATT&CK-mapped detection rules for CrowdStrike, Wiz, and Splunk.

Mars Security announced a capability that automatically turns newly published threat intelligence from sources like CISA, Mandiant, Unit 42, and Microsoft into MITRE ATT&CK-mapped detection rules. Each rule is written in the native query language of the customer's telemetry (CrowdStrike Falcon, Wiz, Splunk, firewalls, identity providers, AWS, Snowflake, Databricks) and backtested against 30 days of the customer's data before deployment, with indicator scoring to drop noisy or stale indicators. The platform also maps existing detection coverage, flags gaps such as AWS CloudTrail tampering and pass-the-hash movement, and delivers some recommendations as open pull requests for detection-as-code workflows.

Help Net Security·Sep 8, 13:43 UTC · 8d agoTools

Horizon3 Announces Integration with CrowdStrike Falcon® Next-Gen SIEM

Horizon3 announces NodeZero integration pushing validated exposure findings into CrowdStrike Falcon Next-Gen SIEM for correlated investigations.

Horizon3 announced an integration enabling validated NodeZero findings to flow into CrowdStrike Falcon Next-Gen SIEM, available now in the CrowdStrike Marketplace. Security teams can ingest and correlate exposure data with endpoint, identity, cloud, and other telemetry during investigations. CrowdStrike claims Falcon Next-Gen SIEM delivers up to 150x faster search than legacy SIEMs at up to 80% lower total cost of ownership.

Horizon3.ai·Sep 15, 13:10 UTC · 1d agoTools

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

Attack Chains, Not Just Attack Surfaces: Why Testing Individual Techniques Misses the Point

Filigran introduces Attack Chaining in OpenAEV to continuously simulate multi-stage attack paths, exposing gaps that isolated MITRE ATT&CK technique testing misses.

Filigran announced Attack Chaining, a new scenario type in its OpenAEV platform that links individual techniques into automated, continuously-run multi-stage attack paths, using each step's real output (credentials, tokens, open ports) to branch dynamically toward a final objective. The article cites Filigran's State of Threat Management report, in which 93% of security leaders reported a business-impacting cyberattack in the past 12 months, 88% said AI accelerates attackers, and 84% blamed siloed tools and disconnected testing. The 2025 DGFiP breach is cited as an example where individually survivable weaknesses chained into a major intrusion. The feature includes conditional chaining logic, live attack path mapping, structured findings for identifying chokepoints, and predefined scope and safety guardrails.

The Hacker News·Sep 15, 11:26 UTC · 1d agoTools

Operationalize CTEM with NodeZero®

Horizon3.ai publishes a factsheet on operationalizing Continuous Threat Exposure Management with NodeZero and its CTEM Operating Loop.

Horizon3.ai released a factsheet describing how its CTEM Operating Loop and NodeZero platform turn Continuous Threat Exposure Management into a repeatable process. The workflow covers discovering, validating, prioritizing, remediating, and verifying exploitable exposures. The item is vendor marketing material rather than new vulnerability disclosure or threat intelligence.

Horizon3.ai·Aug 24, 18:19 UTC · 22d agoTools

Decoy Direction Optimization: A Post-Hoc Defense Against LLM Abliteration

Researchers introduce Decoy Direction Optimization, a cheap weight-editing defense that blinds refusal-direction ablation attacks against open-weight LLM safety guardrails.

Refusal Feature Ablation bypasses safety guardrails in open-weight LLMs by projecting out a linear refusal direction, often with high attack success rates. Decoy Direction Optimization injects a high-magnitude nonlinear decoy into MLP neurons so attackers' contrastive estimators ablate a harmless orthogonal feature instead. Evaluated across six model families, DDO keeps ASR below 10% under standard RFA and on Llama-3-8B-Instruct reduces Heretic weight-level attack ASR from 88.7% to 18%. It costs 30 to 450 times less per configuration than trained defense baselines.

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