Search: “slog”

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Re: AI slops from Eve

oss-security moderator Solar Designer says he may reject repetitive AI-generated postings after debate over AI slop submissions.

oss-security list moderator Solar Designer responded to criticism triggered by AI-generated 'slop' postings from an account known as Eve, saying that in his moderator role he may start rejecting repetitive AI-generated submissions. The brief thread reflects open-source security community concern about automated content quality on the mailing list.

oss-securityupdated Sep 13, 15:08 UTC · 3d agofirst Sep 11, 14:50 UTC · 5d agoIndustry 11 sources1

China-Linked Hackers Exploit Chrome-Windows Zero-Day Chain to Deploy GRIMWEDGE

Volexity attributes spear-phishing campaign exploiting Chrome-Windows zero-day chain to Chinese actors UTA0560 and APT31 deploying GRIMWEDGE and LONGTALE.

Volexity attributes a September 1, 2026 spear-phishing campaign targeting NGOs to China-linked UTA0560, which abused a reflected XSS flaw on a US university website to trigger a three-part exploit chain (CVE-2026-85046, CVE-2026-87491, CVE-2026-85880) escaping the Chrome V8 and browser sandboxes to deploy the GRIMWEDGE JavaScript backdoor with reconnaissance, file management, and command execution capabilities. The same chain was used near-simultaneously by JungleBamboo (APT31) to deploy SUPERSTOMP, installing the LONGTALE/GemStone credential-stealing Chrome extension masquerading as Google Gemini. The Chrome flaws were patched in Chromium but not yet in stable Chrome, creating an unusual patch-gap zero-day window attackers raced to exploit.

The Hacker Newsupdated Sep 15, 10:17 UTC · 1d agofirst Sep 15, 05:31 UTC · 2d agoThreat actor in the wild 9 sources CVE-2026-85046 CVE-2026-87491 CVE-2026-858801· 1 read

The Price of Sparsity: Sufficient Conditions for Sparse Recovery using Sparse and Sparsified Measurements

Researchers derive sufficient sample-size conditions for recovering sparse binary signals from sparse Gaussian measurements, quantifying an information-theoretic threshold of order slog(p/s)/log(ds/p).

The paper studies support recovery of sparse binary signals from noisy linear measurements. For sparse Gaussian designs, the authors identify sufficient minimal sample sizes for maximum-likelihood recovery in the high-SNR regime d*s/p -> infinity, yielding an information-theoretic threshold of order slog(p/s)/log(ds/p) that makes the price of measurement sparsity explicit. They also show a regime where the sample-complexity loss from sparsity is only logarithmic while computational gains are nearly linear, and prove that for independently sparsified dense Gaussian designs a sample size of order p/ψ² suffices for support recovery at any fixed error level.

Hugging Face daily papersSep 7, 20:00 UTC · 9d agoAI research

Type Diversity Enables Transformers to Generalise Compositionally

Researchers show lexical-versus-structural compositional generalization gaps in Transformers stem from type diversity imbalance in datasets, not architectural limits.

The paper argues that Transformers' difficulty with structural compositional generalization is an artifact of low structural type diversity in prior benchmark datasets rather than an architectural limitation. Using Grammatical Framework, the authors create linguistically diverse variants of COGS and SLOG. They find type diversity correlates with compositional generalization equally in lexical and structural test cases, contradicting previous claims that compound divergence explains task difficulty.

arXiv cs.AI / cs.LG / cs.CLSep 11, 17:59 UTC · 5d agoAI research

Product showcase: Is this image real? Slop or Not investigates

Slop or Not is an offline iPhone/Mac app using on-device Apple Neural Engine models to detect AI-generated images, text and SynthID watermarks.

Slop or Not is an AI text and image detector for iPhone and Mac that runs entirely offline via the Apple Neural Engine, with no account required. It returns AI-probability scores and checks for Google's invisible SynthID watermark to verify AI-origin images on-device. The hands-on review found strong detection of obvious AI images, a borderline 50.4% AI call on a realistic one, and correct identification of real photos, citing survey data that 85% of people struggle to distinguish AI-generated content.

Help Net SecurityAug 13, 00:00 UTC · Aug 13, 2026AI tools & infra

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 · SecurityAug 20, 13:00 UTC · 27d agoAI safety & security1

Insights into Suspected DPRK Workers

Huntress details incidents involving suspected DPRK remote workers (Famous Chollima) in partner environments and shares detection indicators.

Huntress analyzed several incidents involving suspected North Korean remote workers, associated with the activity cluster known as Famous Chollima. The report describes indicators defenders can use to detect and prevent DPRK worker infiltration in customer environments. The scheme centers on operatives obtaining remote jobs at Western companies under assumed identities.

HuntressAug 26, 04:00 UTC · 22d agoThreat actor in the wild

VDiff-Bench: A Challenging Benchmark for Fine-Grained Image Difference Identification

VDiff-Bench, a 1,756-question benchmark, shows multimodal LLMs struggle with fine-grained image-difference identification, scoring as low as 8.7% on low-level changes.

VDiff-Bench is a multiple-choice benchmark of 1,756 four-way questions over image pairs covering 10 change categories including position, motion, color, texture, OCR/text and illumination, with curated hard negatives. Evaluation of 11 state-of-the-art open- and closed-source MLLMs shows fine-grained visual comparison remains brittle: 7-8B-scale open-source models score 52.5-70.6% on semantic changes but only 8.7-33.3% on low-level changes like noise and texture. Notably, Grok 4.3 shows a sharp performance drop on noise and texture differences, falling behind large open-source models like Kimi K2.5 and K3.

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

New Ted Backdoor Hides Inside Victims' Own HAProxy Builds to Intercept Web Traffic

Rapid7 found a new backdoor, ted, compiled into trojanized HAProxy at two South Korean organizations, with medium-confidence attribution to North Korean actors.

Rapid7 documented a previously undocumented Linux toolkit named ted compiled into the HAProxy load balancer binaries of two South Korean organizations in the automotive and media sectors. The implant intercepts web traffic, serves altered pages only to filtered visitors, and hides C2 exchanges from backend logs and HAProxy statistics; a companion RAT, curlRAT, beacons on a default 12-hour schedule. The toolkit also trojanizes crond, sshd, agetty, atd, and polkitd binaries and sanitizes logs and bash history. Rapid7 attributes the activity with medium confidence to North Korean state-sponsored actors, with domain infrastructure overlapping APT37 listings in maltrail and delivery resembling the Operation SyncHole campaign.

The Hacker NewsSep 4, 14:51 UTC · 12d agoThreat actor in the wild

Hackers Disable Endpoint Protection and Deploy Sliver Across Compromised Windows Domain

The Hunter's Ledger tracked campaign UTA-2026-024 using Sliver C2, Domain Admin account creation, and Ethereum-based C2 rotation to compromise a US organization's Windows domain.

The Hunter's Ledger tracked an intrusion at one unnamed US organization as UTA-2026-024, staged from exposed server 193.233.202.17 with a Sliver beacon. Operators created a non-expiring Domain Admin account, enabled RDP with NLA disabled, dumped SAM, SYSTEM and SECURITY hives plus LSASS memory, and disabled eight endpoint protection services. A Node.js implant resolved its C2 server from an Ethereum smart contract that rotated domains five times in five months, while SYSTEM scheduled tasks with backdated dates and DNS allowlist manipulation provided persistence. The infrastructure ties to a confirmed ransomware incident, but no encryptor deployment was proven in this intrusion.

Cyber Security NewsSep 8, 12:10 UTC · 8d agoThreat actor in the wild

Version Control DFIR: a Cheatsheet to GitHub, GitLab, Bitbucket, and Azure DevOps

Wiz published a DFIR cheatsheet covering log visibility, incident readiness, and threat hunting across GitHub, GitLab, Bitbucket, and Azure DevOps.

Wiz researchers released a practitioner's guide to version control system forensics, incident response, and threat hunting. The cheatsheet maps log sources, audit capabilities, and hunting workflows across GitHub, GitLab, Bitbucket, and Azure DevOps. It aims to improve incident readiness for source code and CI/CD compromise scenarios.

Wiz BlogAug 27, 12:00 UTC · 20d agoResearch1

What Good Identity Hardening Looks Like

Huntress guidance defines mature identity hardening beyond baseline MFA, covering exception cleanup and detecting identity configuration drift before attackers do.

Huntress argues MFA is only a starting point and outlines what mature identity hardening actually looks like in practice. The guidance covers closing MFA exceptions and coverage gaps that create unauthenticated attack paths. It also stresses catching identity configuration drift before attackers can exploit it.

HuntressAug 25, 13:00 UTC · 22d agoResearch

AI slops from Eve

oss-security moderator Solar Designer approved three AI-generated vulnerability reports from automated security researcher Eve, sparking debate over AI slop on the list.

oss-security moderator Solar Designer approved three posts submitted by Eve, described as an 'automated security researcher', noting they lacked Date headers and arrived on the list server on September 9. He expressed uncertainty about their value but suggested they may have historical significance as early examples of AI-generated security reports at the dawn of AI security research. The post is meta-commentary on AI-generated content reaching a vulnerability disclosure mailing list rather than a specific vulnerability disclosure itself.

oss-securitySep 10, 01:37 UTC · 7d agoIndustry

New Chaos Variant Targets Misconfigured Cloud Deployments, Adds SOCKS Proxy

Darktrace says the Chaos botnet now targets misconfigured cloud deployments like Hadoop and added a SOCKS proxy for traffic relaying.

Darktrace identified a new 64-bit ELF variant of the Chaos botnet targeting misconfigured cloud deployments, expanding beyond the malware's traditional focus on routers and edge devices. Captured in a deliberately misconfigured Hadoop honeypot instance, the intrusion began with an HTTP request creating an application that ran embedded shell commands to fetch the Chaos agent binary from pan.tenire[.]com, set chmod 777 permissions, execute it, and delete the artifact to reduce forensic traces. The restructured variant adds a SOCKS proxy feature letting compromised systems ferry attacker traffic, while removing SSH-based spread and router-exploit functions, suggesting monetization beyond crypto mining and DDoS-for-hire. Possible Chinese origin is suggested by language artifacts and infrastructure; the delivery domain was previously used in Silver Fox's Operation Silk Lure phishing campaign delivering ValleyRAT.

The Hacker NewsAug 18, 12:13 UTC · 29d agoMalware1

Retrospective by 'gpg.fail' authors

Authors of the gpg.fail GnuPG vulnerability set published a retrospective with talk recording, slides, and a repo PoC.

Sam James shares that the researchers behind the 'gpg.fail' set of GnuPG vulnerabilities have published a retrospective, including a talk recording and slides. The slides appear to mention an additional vulnerability not yet widely reviewed, and a proof-of-concept is available in their repository. This follows earlier discussion of the gpg.fail findings on oss-security.

oss-securityupdated 03:19 UTC · 5h agofirst Sep 13, 01:12 UTC · 4d agoResearch 9 sources1

SAFIRE: Safety-Critical Benchmark for Fine-grained Fire and Smoke Understanding in Multimodal LLMs

SAFIRE, an 83K-image fire and smoke benchmark, shows open-source multimodal LLMs average only 61.9% accuracy on safety-critical fire reasoning.

SAFIRE is a large-scale benchmark for fire-smoke understanding in multimodal LLMs with 83K captioned images across 20 scenarios and 193K multiple-choice VQA questions spanning 10 evaluation dimensions from perception to higher-order reasoning. Annotations were built via a GPT-5.4-assisted multi-stage pipeline with MLLM majority voting. Ten open-source MLLMs (8B-38B) average 61.9% accuracy, exposing major gaps in safety-critical reasoning. Adapting vision encoders on 7% of the domain data raises fire-scene classification from 20.1% to 64.5%.

arXiv cs.AI / cs.LG / cs.CLSep 7, 17:59 UTC · 9d agoAI research

SAS: Simple Attention Sparsification via End-to-End Optimization of Context Ranking

SAS trains attention sparsification end-to-end with the language modeling loss, beating sparse attention baselines especially under tight context budgets.

Simple Attention Sparsification (SAS) injects the selector's continuous scores into attention logits in log form inside the softmax, letting gradients from the language modeling loss directly update the ranking of context units. The method uses normalized softmax gates calibrated against the current block and a memory-efficient Triton kernel integrated into FlashAttention-style computation. Across reasoning, long-context, and agentic tasks, SAS consistently outperforms trainable sparse attention baselines across budgets, with the largest gains under tight attention budgets.

Hugging Face daily papersupdated Sep 11, 17:58 UTC · 5d agofirst Sep 10, 20:00 UTC · 6d agoAI research 2 sources1

Plug 'n' Pray: Agentic LLM-based Detection of Potential Log File Exposures in Third-Party Content Management System Plugins

Agentic LLM analysis validates 79 log file exposures across 62 of the 300 most-installed WordPress plugins, covering 250M+ active installations.

Researchers built an agentic LLM-based framework combining static and dynamic analysis to automatically detect insecure log files created by WordPress plugins. Scanning the 300 most-installed plugins, which account for roughly 75% of all active installations in the official ecosystem, it produced 81 findings with 79 manually reproduced across 62 plugins. Insufficiently secured log files can disclose credentials and personal data and have led to website compromises. The authors derive a taxonomy of log path and protection patterns and best practices, finding multi-layered protection often absent.

arXiv cs.CRSep 15, 13:29 UTC · 1d agoResearch

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.

GBHackersSep 11, 05:53 UTC · 6d agoAI safety & security 2 sources

Creepy crawlies

git.kernel.org spends more CPU rendering commit pages for abusive AI-era scrapers than on all legitimate access including git clones.

Konstantin Ryabitsev reports that abusive crawler 'background radiation' at git.kernel.org consumes more CPU cycles rendering commit HTML than all legitimate access, with 14 cores across five geo-distributed nodes dedicated to scraper traffic. Simon Willison highlights the implications for crawlable web services like Datasette.

Simon WillisonSep 7, 23:08 UTC · 9d agoAI industry1

Next-Gen Phishing Tactics Users Aren’t Ready For | Huntress

Huntress details modern phishing tactics including ClickFix, browser-in-the-browser, and OAuth consent phishing beyond basic credential harvesting.

Huntress describes a shift in phishing attacks beyond basic credential harvesting toward advanced tactics. Covered techniques include ClickFix social engineering, browser-in-the-browser (BitB) attacks, and OAuth consent phishing. The post recommends training users on these patterns through Huntress SAT simulations.

HuntressAug 28, 16:00 UTC · 19d agoPhishing & fraud in the wild1

Google Doc Sidebar Sends Mac and Windows Users Down Different Paths to Malware

Huntress analysts trace one X direct message into separate Mac and Windows malware chains delivering AMOS infostealer and NetSupport Manager RAT.

Huntress SOC analysts dissected a malware campaign distributed via an X direct message styled as a Google Docs sidebar. macOS users were routed to the AMOS infostealer, while Windows users received NetSupport Manager remote access malware. The write-up details how a single message branched into two distinct delivery paths per operating system.

HuntressSep 11, 16:36 UTC · 5d agoMalware in the wild

DeepSeek-v4.1 Flash: Pushing the Limits of KV Cache Compression

DeepSeek-V4.1 Flash is a 552B-parameter multimodal MoE model with 1M-token context achieving 4x KV cache compression for long-horizon agent workloads.

A detailed analysis of the DeepSeek-V4.1 Flash technical report describes a 552B-parameter multimodal mixture-of-experts model supporting contexts up to 1 million tokens. Its Causal Encoder-Decoder (CED) architecture activates 8B parameters during prefill and 16B during decode, and reportedly delivers about 420 tokens/s. Joint optimization of architecture (CSA2 cross-layer compression), FP4 KV cache precision, and deployment strategy cuts runtime KV cache to roughly 1/4 and persistent KV cache to about 1/8 of DeepSeek-V4-Flash at the same sequence length, targeting storage and bandwidth bottlenecks in long-horizon agent serving. The author notes all DeepSeek-V4 Pro models were taken offline following the release.

Hacker News · AI01:39 UTC · 6h agoModel release HN 41↑ · 3 comments

Zero-Click Grok Chat History Theft: Adversa AI Demonstrates Cryptographic Context Injection

Adversa AI's Cryptographic Context Injection bypasses AI guardrails using AES-encrypted payloads, enabling zero-click theft of Grok users' full chat histories.

Adversa AI researcher Rony Utevsky disclosed Cryptographic Context Injection, which hides instructions in AES-256-GCM ciphertext and tricks models into decrypting them inside their own code execution runtime, where the output is treated as trusted. Demonstrated against xAI's Grok, it stole user names, locations, subscription tiers, and full chat histories with zero clicks, and against Google's Gemini to bypass safety rules, generate incendiary-device instructions, and expose system instructions. Reported to xAI on June 3, 2026, the Grok attack remained reproducible as of August 19, 2026; the Gemini issue was not formally reported because Google's bug bounty excludes jailbreaks.

Security AffairsAug 23, 07:20 UTC · 25d agoAI safety & security

Adversarial Testing of Automated Program Repair Agents for Security Vulnerabilities

SWEADV benchmark shows adversarial issue descriptions make LLM program-repair agents write insecure fixes in 51.7% of cases, evading most detection tools.

Researchers built SWEADV, a benchmark of 750 adversarial issue descriptions derived from 150 SWE-bench Verified repair tasks, covering command execution, deserialization, path traversal, denial of service, and weak hashing attack types. Tested on mini_swe agents backed by GPT-5-Mini, MiniMax-M2.5, and DeepSeek-R, adversarial descriptions induced malicious behavior with successful repair in 51.7% of cases. Detection was weak: LLM-as-judge pre-repair screening reached only 62.3% accuracy, and post-repair detection via static analysis and LLM-as-judge achieved just 39.4% and 55.4%.

arXiv cs.CRSep 14, 17:53 UTC · 2d agoAI safety & security2

Hackers Use Fake Claude and ChatGPT Installers to Infect Mac Users With Password-Stealing Malware

Attackers distribute MacSync macOS infostealer via fake Claude and ChatGPT installers and sponsored search ads, stealing passwords, cookies, keys, and wallets.

SEQRITE reports a malware-as-a-service campaign pushing MacSync, a macOS password stealer, through sponsored search results and fake Claude and ChatGPT download pages. ClickFix-style prompts trick users into pasting a Terminal command that launches a stager, which loads an in-memory AppleScript to harvest credentials. The malware collects browser vaults, Keychain data, SSH keys, session cookies, messaging sessions, and cryptocurrency wallets, then persists via renamed LaunchAgents and can request screen-recording permissions.

Cyber Security NewsSep 10, 09:53 UTC · 6d agoMalware in the wild

Foul Language: WordlistLoader Disguises Malware as Ordinary Text

ClickFix-style campaigns deploy WordlistLoader, which disguises malware as ordinary text, to deliver the increasingly prevalent Amatera infostealer.

Researchers describe WordlistLoader, a new loader that disguises malicious payloads as ordinary text or wordlist files to evade detection. It is being used in ClickFix-style social engineering campaigns to deliver Amatera, an increasingly prevalent infostealer. The obfuscation technique helps the campaign slip past file-type-based inspections.

Dark ReadingAug 24, 20:51 UTC · 23d agoMalware in the wild