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Hacker News - Newest: "LLM"

GitHub - lechmazur/position_bias: A benchmark for testing whether LLM judges keep the same preference when two lightly edited versions of the same story are shown in opposite orders. Flex routing (EU and EFTA) Dark Factories: Retooling for LLM Velocity Ask HN: What would be the impact of a LLM output injection attack? GitHub - AronDaron/dataset-generator: No-code desktop app for generating high-quality synthetic datasets to fine-tune LLMs — plan-then-execute pipeline, LLM-as-judge, HuggingFace upload. GitHub - Oaklight/llm-rosetta: Production-ready LLM API translation layer for Python — bidirectional conversion between OpenAI, Anthropic & Google formats via hub-and-spoke IR. Optional API gateway. Streaming & non-streaming. Zero core deps. Contributions welcome! GitHub - browser-use/browser-harness: Self-healing browser harness that enables LLMs to complete any task. GitHub - moeen-mahmud/remen: Remen turns thoughts into something you can return to Analyzing 156 LLM Launch Posts on Hacker News ChatGPT vs Gemini vs Claude: The Best LLM Subscription You Should Buy GitHub - salaamalykum/quran-semantic-search: High-density RAG Semantic Search Engine & Quran Corpus (GEO/SEO Architecture) GitHub - NVIDIA/TensorRT-LLM: TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT LLM also contains components to create Python and C++ runtimes that orchestrate the inference execution in a performant way. The State of LLM Bug Bounties in 2026 Operational Readiness Criteria for Tool-Using LLM Agents Meshcore: Architecture for a Decentralized P2P LLM Inference Network How an LLM becomes more coherent as we train it GitHub - seetrex-ai/laimark GitHub - Jossifresben/BibCrit: AI-assited biblical textual criticism GitHub - wastedcode/memex: File system based wiki, maintained by Claude 99helpers.com GitHub - cliver-project/AITrigram GitHub - unbody-io/adapt: A self-evolving memory layer for AI agents. GitHub - hb20007/awesome-gen-ai-fails: A list of incidents where reliance on generative AI and LLMs resulted in harm to companies, individuals, or society GitHub - nevenkordic/localmind: Run any local LLM with persistent memory and context. CLI agent over Ollama with SQLite-backed hybrid recall. No cloud. Ask HN: What are the machine requirements for a LLM like Llama-3.1-8B? 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Open the Black Box with the Arthur Engine Milla Jovovich's New Open Source LLM Memory App and the Dark Code Problem Your intuition of LLM token usage might be wrong Show HN: Bloomberg Terminal for LLM ops – free and open source GitHub - 0xchamin/mcptube: Transform YouTube videos into a compounding knowledge base with transcripts, vision analysis, and agentic search. Works as an MCP server for Claude, Copilot & more. Show HN: Open KB: Open LLM Knowledge Base Your LLM is a compiler, not a runtime GitHub - sapountzis/Unslop: A Web Feed That Deserves You crates.io: Rust Package Registry Beyond Karpathy's LLM-Wiki: The Necessity of Cognitive Governance GitHub - amitshekhariitbhu/llm-internals: Learn LLM internals step by step - from tokenization to attention to inference optimization. GitHub - parallem-ai/parallem: An expressive library for running agents with the Batch API. 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GitHub - anitiue/Hindsight: An experience-driven self-improvement framework for LLM agents — 基于经验的 LLM Agent 自我改进框架 GitHub - stef41/lmscan: 🔍 Detect AI-generated text and fingerprint which LLM wrote it. Open-source GPTZero alternative. Zero dependencies, works offline. GitHub - alainnothere/AmdPerformanceTesting: Amd Performance Testing Ask HN: Is a purely Markdown-based CRM a terrible idea? Optimized for LLM agents Context Engineering - LLM Memory and Retrieval for AI Agents | Weaviate little_helper_tui/letter.md at main · sleepyeldrazi/little_helper_tui GitHub - EvanZhouDev/umr: The Unified Model Registry for all your local AI apps. GitHub - JordanCT/VigIA-Orchestrator Your Agent Is Mine: Measuring Malicious Intermediary Attacks on the LLM Supply Chain A Taxonomy of RL Environments for LLM Agents Llama LLM Network Feture GitHub - genedeng-ca/ai-mac-migration: AI-powered Mac-to-Mac migration tool - replace Apple Migration Assistant with intelligent, selective transfer using local LLMs GitHub - lunargate-ai/gateway: High-performance self-hosted AI gateway (OpenAI-compatible) with routing, retries, and streaming GitHub - AuthBits/webmcp: A lightweight, prompt-driven MCP web research server for high-quality LLM powered information extraction. Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering Springdrift: An Auditable Persistent Runtime for LLM Agents with Case-Based Memory, Normative Safety, and Ambient Self-Perception High-Stakes Personalization: Rethinking LLM Customization for Individual Investor Decision-Making From Static Templates to Dynamic Runtime Graphs: A Survey of Workflow Optimization for LLM Agents HUOZIIME: An On-Device LLM-enhanced Input Method for Deep Personalization TIDE: Token-Informed Depth Execution for Per-Token Early Exit in LLM Inference Characterizing WebGPU Dispatch Overhead for LLM Inference Across Four GPU Vendors, Three Backends, and Three Browsers LLM Targeted Underperformance Disproportionately Impacts Vulnerable Users
LLM-driven security reports disrupt coordinated disclosure
jwilk · 2026-05-07 · via Hacker News - Newest: "LLM"

[LWN subscriber-only content]

Predictions that LLM tools would cause a surge in reports of security vulnerabilities have, unquestionably, borne out. As expected, maintainers are having to wade through more security reports than ever before; in addition, LLM tools are disrupting traditional-coordinated disclosure practices as well. The method of Copy Fail's disclosure, in particular, left vendors, projects, and users scrambling. In addition, maintainers are seeing parallel discovery of the same security flaws within the embargo window. Both of these developments mean that coordinated security disclosures may become a thing of the past.

"Mining security gold"

Jeremy Stanley, a member of the vulnerability management team for the OpenStack cloud-computing project, brought this topic to the OSS Security mailing list on April 28. He said that projects he worked on "are under a seemingly unending deluge of reports from researchers using LLMs to mine for security gold in our software". That had led to him thinking about the risks that public LLM services might pose to traditional vulnerability-handling workflows, embargoes, and coordinated disclosure of security flaws. He wondered if it would be helpful to keep embargoes short to mitigate the risks of parallel discovery or disclosure to other LLM users.

I'm sorely tempted, both due to the increased volume and the risk of premature disclosure, to just assume that any vulnerability reported as a result of research using an LLM is trivially discoverable by others, and give up trying to pretend there's any point to working it under embargo. Similarly, it makes sense to me that patch development and descriptive prose shouldn't be produced with LLM assistance for any vulnerability that is being worked under an embargo.

He said that he could not be the only one thinking about this topic, and asked what others thought. Jacob Bachmeyer replied that parallel discovery was a big risk: "If an LLM can find a bug for a whitehat, it can do the same for a blackhat. [...] LLM-discovered vulnerabilities should be considered already publicly known".

Effect on embargoes

If the vulnerabilities are (arguably) known to multiple people, the question arises of whether standard practices around security embargoes still make sense. Lucas Holt said that he saw "the logic and temptation" of shortening embargoes, but dropping a zero-day exploit on a small project would not help anyone. He suggested that large projects may have multiple people looking for and discovering the same flaws, but smaller projects were unlikely to have multiple people probing them for vulnerabilities at the same time.

Stanley clarified that he was approaching the problem from the perspective of "an upstream maintainer and vulnerability coordinator of large/popular projects receiving these reports". He was seeing a flood of reports, and that trying to manage all of them in private was leading to "accidents breaking our embargoes before things are ready or distros/deployers have been given sufficient advance warning". If security reports were public immediately, he thought projects could crowdsource help from a larger portion of their community "rather than relying solely on overwhelmed vulnerability coordinators and security-focused maintainers".

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Holt had suggested that people who used LLMs to find security bugs could also use their tools to create patches. Brian May warned people to be careful of that approach. "Simple patches that look good can in fact be hiding serious security issues. Thinking of the September 2006 Debian openssl issue here."

Greg Dahlman also thought that LLMs were unreliable when it comes to creating security fixes. He described the ability of current LLMs to produce correct and secure code as being within "the coin flip range"; in other words, he thought there was only a 50-50 chance that an LLM's suggested solution to fix a flaw would be adequate. Therefore, any embargo timeline needed to take into account the asymmetry between the time it takes to discover a flaw and the time needed to actually fix it.

Already happening

It turns out that Stanley's hypothesis about parallel discovery had already been proven in the wild. Clemens Lang, who works on the Red Hat Enterprise Linux (RHEL) crypto team, provided a data point to support the theory: "We're seeing duplicate reports of the same issue found by multiple independent groups that use LLMs, within the embargo period." Greg Kroah-Hartman also reported that kernel developers were seeing "seeing duplicate reports of the same issue from different groups within the time period it takes to get a fix merged".

Willy Tarreau said that he had predicted the death of security embargoes months ago:

Embargoes now play against security, for all the time we don't act, users stay exposed to anyone having the luck to find the same problem. It's not a matter of the LLM's strength but a matter of determination by the researcher who could simply run a small model several times helping it dig further. Bigger models just find faster, but that only counts for those seeking protection, not for those trying to attack.

Copy Fail disclosure fail

The Copy Fail privilege-escalation vulnerability (CVE-2026-31431) was announced on April 29 by Xint. It is a "straight-line logic flaw", meaning that it does not require race conditions or other special circumstances, that allowed local users to trivially get root access on most Linux distributions unless they had the most up-to-date kernels.

Along with the announcement, there was a proof-of-concept (POC) Python script that allowed users to see if their systems were vulnerable. The fix had already been included with the 7.0, 6.19.12, and 6.18.22 kernels, but was not available as a backport to older stable kernels until April 30. Most Linux distributions were caught with their proverbial pants down. On April 30, with a POC showing how to exploit the vulnerability widely available, major distributions such as Debian, Red Hat Enterprise Linux, SUSE, and Ubuntu had no fix ready for their users.

It was described as "one of the worst make-me-root vulnerabilities in the kernel in recent times" by Eddie Chapman on the OSS Security list. He wondered what went wrong:

Has the embargo been broken early today? Not looking to point any fingers, those who make things happen in our communities work dam hard and deserve respect and support, especially with the extra burden of AI slop now.

Gentoo contributor Sam James said that it's up to security reporters to notify Linux distributions of kernel vulnerabilities: "unless the reporter chooses to bring it to the linux-distros [mailing list], there is no heads-up to distributions. It did not happen here."

The discussion turned to something of an ad-hoc postmortem, fingerpointing, and problem-solving session. Alexander Peslyak, who goes by "Solar Designer", said that distributions had little way of knowing about the importance of this vulnerability, as it did not stand out among all the others.

The vulnerability was reported to the kernel team on March 23, according to the timeline in Xint's announcement. A patch was committed to the mainline kernel on April 1. CVE-2026-31431 was added to the kernel's security repository on April 25, with a Common Vulnerability Scoring System (CVSS) score of 7.8 (out of a possible ten), four days before the Copy Fail announcement. Peslyak pointed out that there were 168 CVEs in the batch from that day, with scores between 7.1 and 9.8. "By the score alone, this one really does not stand out. To me, this is usual noise, with little signal in there." It did not hint at the severity or imminent threat of a POC being released. In fact, there are 21 CVEs added on April 25 that have a "9.8 CRITICAL" CVSS score.

Greg Kroah-Hartman replied that the kernel team's "constant message", for decades, has been that users must upgrade to the latest release to ensure that they have all of the fixes for currently known issues. He added that the kernel team had no knowledge of the Copy Fail announcement ahead of time "as no one is obligated to tell us that they are about to let loose a trivial exploit", and that the team was not allowed to notify others ahead of time, lest they have to tell everyone about everything. "That's the only policy by which all the legal/governmental agencies have agreed to allow us to operate in, so we are stuck with it."

On May 3, James shared a link to a comment from Brian Pak of Xint that said the company had provided a fully working exploit to the kernel security team when the vulnerability was reported. "We've since learned that such details don't automatically get forwarded downstream and that Linux kernel commit messages are typically kept minimal. That's simply how the process works." James said that the kernel team "were very much aware of the impact from the offset", and inquired if the kernel team was "honestly proud of how this went".

The CVE garbage patch

Kroah-Hartman asked exactly what James would suggest that the kernel team do better, and how it should do it. He added that the team receives bug reports of local-user privilege-escalation bugs all the time; it was not obvious that this one was special until after the fact because the submitter used it to show off their software. "That is something that normally does not happen and is outside of the control of all of us involved here." Emily Shepherd wanted to know if the POC or a description of the flaw's severity had been provided; Kroah-Hartman replied that he honestly did not remember because "that was months and hundreds, if not thousands, of reports ago". He also reminded the list how the kernel security team operates:

The job of the kernel security team is to triage a bug report, drag in the relevant maintainer/developer, get the issue fixed and merged into Linus's tree as soon as possible. Once it lands in Linus's tree, our role is over.

We do not do "announcements" of anything to anyone, so even if this was a "look how bad you can abuse the system" type of thing, we would not be telling anyone anything.

He added that he's documented this in detail, given many talks about it, and has been blogging about it as well.

On social media, Josh Bressers suggested that the blame lies with the company: "every AI vulnerability company wants to find something juicy, and have no idea how to coordinate the findings". Kroah-Hartman dismissed the idea that coordination of vulnerabilities was even possible now. Bressers agreed: "I do think you're right that the traditional disclosure model is gone forever". He did think it was "pretty obvious" that Copy Fail would be a big one; but he had no idea what to do to prevent important vulnerabilities from drowning in the "great CVE garbage patch".

Copy Fail is just one vulnerability out of thousands. At the rate that LLM tools seem to be speeding up discovery, it does seem that Kroah-Hartman has a point. Traditional disclosure notification is becoming increasingly difficult, if not outright impossible. The volume of reports, coupled with the fact that many AI-assisted reporters will be unfamiliar with how security disclosure usually works, means that relying on embargoes and coordinated fixes is going to be increasingly risky. We live in interesting times for open-source security, whether we want to or not.