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Emacs arbitrary code execution: incomplete fix for CVE-2024-53920

Incomplete fix for Emacs CVE-2024-53920 allows arbitrary code execution when viewing or editing untrusted files in non-Lisp modes like Perl flymake.

Bas Alberts of GitHub Security Lab discovered that the patch for CVE-2024-53920, an arbitrary code execution flaw in Emacs, was incomplete. Code execution remains possible when viewing or editing untrusted text files in modes other than Emacs Lisp mode, for example Perl files with flymake mode enabled. All Emacs versions affected by the original CVE remain affected by the incomplete fix.

oss-securitySep 14, 14:36 UTC · 2d agoVulnerability CVE-2024-53920

CVE-2026-91752: GNU libextractor < 1.15 Stack Overflow via OLE2

GNU libextractor before 1.15 has a stack-based buffer overflow (CVE-2026-91752) in its OLE2 parser, triggerable via crafted files.

A stack-based buffer overflow was identified in GNU libextractor's OLE2 plugin in versions prior to 1.15, assigned CVE-2026-91752. The flaw resides in the process_star_office function, which sizes a variable-length stack array using attacker-controlled OLE2 stream data. Attackers can craft malicious OLE2/StarOffice files to trigger the overflow. The issue was disclosed on the oss-security mailing list by researcher Haitam Lazaar on September 16, 2026.

oss-securitySep 16, 23:13 UTC · 1h agoVulnerability 2 sources CVE-2026-91752

A Three-Layer Caching Architecture for Low-Latency LLM Web Search on Commodity CPU Hardware

OreoLook's three-layer Redis caching architecture cuts redundant LLM calls and embedding work for CPU-hosted web-search answer generation.

The paper describes a three-layer caching architecture for OreoLook (formerly lixSearch), an open-source LLM answer engine: a Redis session context window with Huffman-compressed disk overflow, a semantic query cache matching rephrasings via embedding cosine similarity, and a URL embedding cache deduplicating embedding computations. Deployed on a single 8-vCPU Intel Cascade Lake server with 30 Hypercorn workers across three containerized replicas, it achieved an 89.3% aggregate Redis keyspace hit rate, 0.1 ms read latency, and 1.38 MB memory overhead. An LRU eviction daemon migrates idle sessions to disk and rehydrates them for resumption hours or days later.

Hugging Face daily papersAug 11, 20:00 UTC · Aug 11, 2026AI tools & infra1

C*: Unifying Programming and Verification in C

Research paper C* (arXiv:2504.02246) proposes unifying programming and formal verification in C, discussed on Hacker News.

The arXiv paper 2504.02246, titled C*: Unifying Programming and Verification in C, presents an approach that combines C programming with built-in formal verification. The item surfaced via Hacker News, where it reached 28 points and 18 comments. Detailed abstract content was not included in the source text.

Hacker News · securitySep 8, 15:56 UTC · 8d agoResearch HN 28↑ · 18 comments

Multi-Vector (Late Interaction) Embedding Models with Sentence Transformers

Hugging Face details building and using multi-vector late-interaction embedding models with Sentence Transformers for retrieval workloads.

Hugging Face published a guide on multi-vector, late-interaction embedding models (ColBERT-style) supported through Sentence Transformers. The post covers how practitioners can build and use these models for retrieval and RAG pipelines. It is a developer tooling and technique write-up, not a security advisory.

Hugging Face BlogAug 18, 00:00 UTC · Aug 18, 2026AI tools & infra1

Access Control as Verified Parse Constraints

Researchers verify a class of EverParse validators that correctly enforce access-control policies, deploying a machine-checked enforcement gate on seL4.

The paper targets enforcement-code bugs in commercial security gateways by proving that forward-only, backtrack-free EverParse validators are verified recognizers for a bounded finite-state class that includes access-control decision functions with fixed-offset fields and bounded disjunction. Encoding a bounded policy language into a fixed-size byte buffer allows an SMT solver to verify the enforcement code once, covering all byte values, policies, requests, and sessions. Editing rule content over a fixed endpoint set requires no new proof, while adding endpoints reruns the toolchain. A deployment on the seL4 microkernel ensures every request passes through the gate and unverified components cannot corrupt the enforcement chain.

arXiv cs.CRSep 11, 06:33 UTC · 5d agoResearch1

Rosetta at AlexandriaX-2026: LoRA-Adapted NileChat for Context-Aware Dialectal Arabic Dialogue Translation

Rosetta ranks 4th and 5th in AlexandriaX-2026 dialectal Arabic dialogue translation using a LoRA adapter on NileChat-3B, finding limited pretraining benefit.

The Rosetta system for the AlexandriaX-2026 shared task fine-tunes a LoRA adapter on NileChat-3B for context-aware English-to-dialectal Arabic dialogue translation. The adapter was additionally pretrained on MADAR and PADIC dialect corpora for the unconstrained track. It achieved spBLEU 26.10 (4th, constrained) and 25.09 (5th, unconstrained). External dialect pretraining improved only two of thirteen dialects while slightly degrading overall performance, indicating negative transfer.

arXiv cs.AI / cs.LG / cs.CLSep 9, 16:15 UTC · 7d agoAI research1

TasmScan: Continuation-Aware Taint Analysis for TVM Bytecode with Savelist Abstraction

TasmScan introduces source-free taint analysis for TON smart-contract bytecode, detecting 95.3% of defects with 96.8% precision and 17x speedup.

TasmScan is the first bytecode-level static analysis framework for the TON Virtual Machine, enabling cross-continuation data flow reasoning without source code by modeling savelist semantics through forward register analysis with formal over-approximation guarantees. It lifts bytecode into a typed intermediate representation (TASIR) and performs path-sensitive taint analysis. On a 208-contract benchmark with human-confirmed ground truth it detects 95.3% of defects across five classes at 96.8% precision, and resolves 294,546 dynamic continuation targets with 100% precision across 2,921 registry contracts. It achieves a 17x median speedup over symbolic-execution baselines.

arXiv cs.CRSep 15, 11:01 UTC · 1d 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 OnlineSep 9, 10:00 UTC · 7d agoAI safety & security1

WireGuard-Linux Stack-Based Buffer Overflow in lsiio (Linux IIO Userspace Tool) Due to Unbounded fscanf

The Linux IIO userspace tool lsiio has a stack buffer overflow in find_type_by_name() caused by unbounded fscanf reads of oversized filesystem-backed attribute values.

A stack-based buffer overflow exists in the Linux Industrial I/O (IIO) userspace utility lsiio. In the find_type_by_name() function, the program reads an unbounded string from a filesystem-backed attribute into a fixed-size stack buffer using fscanf("%s", ...). A crafted or oversized attribute value causes a write beyond the bounds of the destination buffer. Despite the title's reference to WireGuard-Linux, the flaw described is in the IIO lsiio utility.

Full DisclosureSep 4, 00:13 UTC · 13d agoVulnerability

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.CRSep 14, 11:54 UTC · 2d agoResearch1

LexFlip: A Dissociation Diagnostic for Legal Meaning Preservation Metrics

LexFlip releases 373 minimal perturbations of Quebec statutory French that reverse legal force while preserving tokens, exposing weaknesses in embedding-based meaning preservation metrics.

LexFlip provides 373 minimal perturbations of Quebec statutory French that reverse legal force while preserving 0.93 of tokens, creating dissociation items that break monotone token-overlap metric validation. The seven embedding and BERTScore metrics tested register only 0.022-0.039 of their identical-to-unrelated range on these edits, versus 0.670 for bidirectional NLI. Against FrJudge, with a measured human ceiling of r=0.597, a bare length feature outscores every semantic metric tested.

arXiv cs.AI / cs.LG / cs.CLSep 4, 15:49 UTC · 12d agoAI research

Why Johnny Can't Encrypt: A Usability Evaluation of PGP 5.0 (1999)

Seminal 1999 USENIX study finds most novice users cannot correctly sign and encrypt email with PGP 5.0 in 90 minutes.

Whitten and Tygar's USENIX Security Symposium paper evaluates whether cryptography novices can use PGP 5.0 effectively, using cognitive walkthrough analysis and a laboratory user test. The majority of test participants failed to successfully sign and encrypt a message within 90 minutes, despite PGP 5.0 having a well-regarded graphical interface. The authors argue that security requires usability standards beyond those of general consumer software and propose domain-specific UI design principles for security. The paper is a foundational reference in usable security research.

Lobsters · securitySep 9, 06:47 UTC · 7d agoResearch

Studying Without a Syllabus: Task-Agnostic Environment Preprocessing

Paper formalizes task-agnostic environment preprocessing, where agents study unfamiliar environments under a budget to build reusable artifacts for a frozen solver.

The paper formalizes task-agnostic environment preprocessing, where a studying system explores an environment under a budget and produces artifacts like indices, scripts, or procedural guidance for a frozen solver, without task examples or evaluation feedback. The authors compare unaided and archive-equipped meta-agents against fixed synthetic-practice and corpus-processing methods across six heterogeneous benchmarks. A meta-agent variant achieves the highest Avg@3 reward on five benchmarks, while fixed corpus processing remains best on the largest corpus benchmark. Studied artifacts reduce the test-time sampling needed to reach a given score, shifting computation from repeated test-time attempts to a pre-task study phase.

Hugging Face daily papersSep 8, 20:00 UTC · 8d agoAI research

27.5KB language-agnostic WebGPU syntax highlighter

A developer released gpu-lexer, a 27.5KB language-agnostic syntax highlighter that uses a tiny WebGPU model to label code tokens in the browser.

gpu-lexer splits source into words, whitespace, and symbols, then a small WebGPU model uses local and whole-file context to assign nine token classes, working on languages never seen in training. On held-out files, 12.57% of token labels differ from Shiki, though this measures agreement with Shiki rather than objective correctness. In benchmarks against Shiki 4.4.3, Prism.js, Highlight.js, Sugar High, and Starry Night, it highlighted 10 concatenated copies of three.min.js (5.56M characters) about 10x faster on an Apple M4 Pro in Chrome 152. The author frames it as an experiment, not a grammar-equivalent highlighter.

Hacker News · securitySep 9, 01:14 UTC · 7d agoAI tools & infra HN 21↑ · 5 comments1

Notes on gotchas while migrating 35kb preprompts from Opus to self-hosted Ollama

Opinion piece urges migrating 35KB preprompts from Anthropic/OpenAI to self-hosted Ollama, citing session privacy risks and safety filters blocking security research.

The author documents gotchas migrating 35KB preprompts from Claude Opus to self-hosted Ollama, motivated by fears that frontier providers train on user sessions, citing the OpenAI Navier-Stokes controversy. The piece argues inference providers cannot audit their own retention or training pipelines and that only self-hosted hardware offers verifiable privacy. It also criticizes frontier safety filters for refusing vulnerability research tasks and calls for models that support exploitability testing in CI/CD pipelines.

Hacker News · AISep 14, 13:59 UTC · 2d agoAI industry HN 41↑ · 13 comments1

Linux Detection Engineering - Local Privilege Escalation

Elastic details a layered detection framework for Linux local privilege escalation, covering 2026's copy-on-write bug wave and LLM-assisted discovery.

Elastic Security Labs describes how most Linux local privilege escalations share a common host flow — an unprivileged process launched from a writable path becoming root — and proposes layered detections combining general outcome-based rules with per-technique rules in Elastic Defend and Auditd. It tracks 13 recent LPE disclosures, seven of which share a copy-on-write/zero-copy bug class, including Copy Fail, DirtyFrag, Fragnesia, DirtyDecrypt, DirtyClone, pedit COW, and RefluXFS. Qualys attributes RefluXFS to an LLM-assisted research effort with Anthropic using Claude Mythos Preview, and another bug is credited to an LLM-assisted workflow. Detection and endpoint rules are published in Elastic's detection-rules and protections-artifacts repositories.

Elastic Security LabsSep 11, 00:00 UTC · 6d agoResearch

SEMA-GUARD: Semantic and Graph-Based Vulnerability Detection in Assembly Code

SEMA-GUARD uses semantic analysis and graph neural networks to detect vulnerabilities in assembly code, achieving 85.1% accuracy on a Juliet-derived benchmark.

SEMA-GUARD is a framework that detects vulnerabilities in compiled programs when source code is unavailable, targeting malware, firmware, and embedded systems analysis. It enriches control flow graphs with low-level execution semantics including stack manipulations, memory accesses, and data flow. Evaluated on a Juliet Test Suite set compiled to assembly and split into function-level chunks, it achieves 85.1% accuracy and an F1 score of 0.801, outperforming purely statistical or structural approaches.

arXiv cs.CRSep 15, 14:35 UTC · 1d agoResearch1

Harnessing LLMs for Automating BOLA Detection

Unit 42's BOLABuster methodology uses LLMs to automate detection of broken object-level authorization vulnerabilities, uncovering flaws in Grafana, Harbor, and Easy!Appointments.

Palo Alto Unit 42 details BOLABuster, a methodology combining large language models with heuristics to automate detection of broken object-level authorization (BOLA) flaws, which traditional fuzzing and static analysis struggle to find. The approach uses LLM reasoning to understand application logic, map endpoint dependency relationships, and generate and interpret test cases. It found CVE-2024-1313 in Grafana, CVE-2024-22278 in Harbor, and 15 CVEs in Easy!Appointments. The team is continuing to hunt for BOLAs in open-source and internal projects.

Palo Alto Unit 42Aug 17, 12:34 UTC · Aug 17, 2026Research CVE-2024-1313 CVE-2024-22278 CVE-2023-3285+14 CVEs

CVE-2026-85484: HTML::FormHandler versions before 0.410002 for Perl render option group labels and radio button labels into HTML without escaping

HTML::FormHandler before 0.410002 for Perl renders option group and radio button labels unescaped into HTML, enabling XSS (CVE-2026-85484).

Robert Rothenberg disclosed CVE-2026-85484 on the oss-security mailing list, affecting HTML::FormHandler versions before 0.410002 for Perl. The module renders option group labels and radio button labels into HTML without escaping, which can enable cross-site scripting in applications using the rendered markup. The issue is addressed in version 0.410002.

oss-securitySep 8, 20:16 UTC · 8d agoVulnerability 2 sources CVE-2026-85484

The GNU C Library security advisories update for 2026-09-14

glibc advisory GLIBC-SA-2026-0017 discloses a buffer overflow in strfmon/strfmon_l affecting versions 2.38 through 2.44.

The GNU C Library published security advisories including GLIBC-SA-2026-0017, a buffer overflow in strfmon and strfmon_l. Calling these functions with right-justified width padding conversions can write past the end of the caller-supplied output buffer in glibc 2.38 to 2.44. Exploitation requires an application code path that calls strfmon with attacker-influenced parameters.

oss-securitySep 14, 19:54 UTC · 2d agoVulnerability 2 sources1

[0day-rubbish] QuantaStor 6.8.3.018 Command injection in the alert-mail command via the smtpPassword field (8.8)

QuantaStor 6.8.3.018 has a CVSS 8.8 command injection in its alert-mail command, exploitable via the smtpPassword field.

0day Rubbish Research Team disclosed a command injection (CWE-78) in QuantaStor 6.8.3.018's alert-mail command, reachable through the smtpPassword field. The flaw scores CVSS 8.8 (AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H). No CVE identifier or evidence of active exploitation is mentioned in the disclosure.

Full DisclosureSep 8, 17:31 UTC · 8d agoVulnerability 2 sources

Augustinian BabyLM: What Ostensive Definition Can and Cannot Teach a Small Language Model

Study shows visually grounded token embeddings in a small masked LM persist through training and improve object-property knowledge, but escape standard BabyLM benchmarks.

The paper implements ostensive definition for a small DeBERTa masked language model trained on 10M words, seeding visually grounded tokens with embeddings derived from labeled image regions before training. Visual initialization leaves a persistent, seed-replicated advantage on object-property knowledge (COMPS) and a corpus-tailored Visual-Property Swap benchmark covering color, material, size, and shape, but has no effect on most BabyLM grammar benchmarks. Synthetic grounding of previously unseeded words causally transfers the advantage to exactly those words.

arXiv cs.AI / cs.LG / cs.CLSep 10, 17:43 UTC · 6d agoAI research

ZDI-26-587: Ashlar-Vellum Cobalt VS File Parsing Heap-based Buffer Overflow Remote Code Execution Vulnerability

ZDI advisory ZDI-26-587 details a heap-based buffer overflow RCE (CVE-2026-19781, CVSS 7.8) in Ashlar-Vellum Cobalt VS file parsing, requiring user interaction.

The Zero Day Initiative released advisory ZDI-26-587 covering a heap-based buffer overflow in Ashlar-Vellum Cobalt's VS file parsing. A remote attacker can execute arbitrary code when the target opens a malicious file or visits a crafted page. ZDI rated the vulnerability CVSS 7.8 and assigned CVE-2026-19781.

ZDI Published AdvisoriesAug 24, 05:00 UTC · 23d agoAdvisory CVE-2026-19781

Meet Redis LangCache: A Managed Semantic Cache That Cuts LLM API Costs by Up to 90% and Returns Cache Hits Up to 15x Faster

Redis launches LangCache, a managed semantic cache matching LLM prompts by meaning, cutting API costs up to 90% and returning hits up to 15x faster.

Redis LangCache is a fully managed semantic caching service in public preview on Redis Cloud, accessed via a REST API with Python and JavaScript SDKs. It embeds incoming prompts, vector-searches stored entries, and returns a cached response when similarity clears a configured threshold, skipping the LLM call entirely. Redis claims up to 90% cost savings and up to 15x faster cache hits; a demo run showed 0.37 seconds versus 2.232 seconds direct inference (about 6x) with zero LLM tokens. Customer Mangoes.ai reports a 70% hit rate, 70% lower LLM spend, and 4x faster responses on a patient-care voice app.

MarkTechPostSep 10, 22:34 UTC · 6d agoAI tools & infra1

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 ZeroSep 8, 07:00 UTC · 8d agoResearch1

AutoTrans: AI-Assisted Automatic Translation of Security Assertions for RISC-V Processors

AutoTrans uses LLMs with regex extraction and formal verification to automatically translate security assertions across RISC-V processors, achieving 78% unattended acceptance.

AutoTrans is an automated framework for translating verified security assertions between RISC-V processor targets, where manual translation takes hours per assertion. It combines a regex-based SystemVerilog signal extractor to prevent LLM signal hallucination, a pinned prompt template yielding byte-identical prompts resilient to model updates, and JasperGold FPV formal verification of generated assertions. Applied with DeepSeek V4 to translate assertions between RISC-V targets such as IBEX and NS31A, it achieves a 78% automatic translation acceptance rate without human intervention and 100% after human refinement.

arXiv cs.CRSep 9, 11:31 UTC · 7d agoResearch

Update modules/auxiliary/scanner/http/elasticsearch_tika_xfa_xxe.rb

Rapid7 updated a Metasploit auxiliary scanner module that detects XML external entity injection in Elasticsearch via Apache Tika.

A commit in the Metasploit Framework updated modules/auxiliary/scanner/http/elasticsearch_tika_xfa_xxe.rb, an auxiliary scanner module. The module targets XML external entity (XXE) injection in Elasticsearch through Apache Tika, and was co-authored by jheysel-r7. The terse commit message contains no additional details, CVE references, or exploitation notes.

Metasploit Framework commitsSep 8, 19:22 UTC · 8d agoTools

[0day-rubbish] core-admin 1.0.164 (build 16468) Systemic shell command injection via ineffective quote escaping (8.8)

0day Rubbish discloses a CVSS 8.8 shell command injection in core-admin 1.0.164 via ineffective quote escaping, enabling authenticated remote code execution.

0day Rubbish Research Team publicly disclosed a systemic shell command injection (CWE-78) in core-admin 1.0.164 (build 16468). The flaw stems from ineffective quote escaping and scores 8.8 (AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H). The disclosure does not mention a CVE identifier or observed exploitation in the wild.

Full DisclosureSep 8, 17:31 UTC · 8d agoVulnerability1