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graphql-go/graphql <= 0.8.1: quadratic CPU-exhaustion DoS via OverlappingFieldsCanBeMergedRule

Unauthenticated quadratic CPU-exhaustion DoS disclosed in graphql-go/graphql up to v0.8.1 via OverlappingFieldsCanBeMergedRule; no fixed version exists.

Evgenios Gkritsis publicly disclosed an algorithmic-complexity denial-of-service flaw in github.com/graphql-go/graphql affecting all released versions up to and including v0.8.1. The defect is triggered via the OverlappingFieldsCanBeMergedRule validation, is unauthenticated and network-reachable, and causes quadratic CPU exhaustion. No fixed version exists; the disclosure was public because the project has no private security-reporting channel or SECURITY.md.

oss-security · 2d agoVulnerability

GitLab Patches Critical Flaws Enabling Arbitrary File Read, Credential Theft and Remote Code Execution

GitLab patched a CVSS 10.0 path traversal (CVE-2026-85706) plus deserialization and buffer-overflow flaws, urging self-managed users to update immediately.

GitLab released versions 19.3.2, 19.2.6, and 19.1.8 on September 10, 2026, fixing CVE-2026-85706 (CVSS 10.0), an unauthenticated path traversal in the repository commits API enabling arbitrary file reads on both Community and Enterprise Editions. CVE-2026-87719 (CVSS 9.9) is insecure deserialization in the EE GraphQL subscription serializer that can expose Advanced Search configurations and credentials, while CVE-2026-88765 (CVSS 8.5) allows authenticated RCE via crafted project exports. The update includes database migrations, so single-node deployments will experience downtime; GitLab.com is already patched.

Cyber Security Newsupdated · 1d agofirst · 5d agoVulnerability 18 sourcesCVE-2026-85706CVE-2026-87719CVE-2026-887651

Critical GitLab GraphQL Flaw Could Let Unauthenticated Attackers Delete Public Projects

GitLab urgently patched CVE-2026-19478 (CVSS 9.4), a critical unauthenticated GraphQL flaw allowing modification or deletion of public projects on self-managed instances.

GitLab released an out-of-band critical patch on August 17, 2026 fixing CVE-2026-19478 (CVSS 9.4), a flaw that under certain conditions lets unauthenticated attackers remotely modify or delete public projects and user data via a GraphQL directive in Community and Enterprise Editions. Fixes are available in GitLab 19.2.4, 19.1.6, 19.0.8, and 18.11.11; GitLab.com and GitLab Dedicated are already patched, so only self-managed installations need to act. The release also fixes CVE-2026-19650 (CVSS 7.1), a cross-site request forgery flaw in GraphQL multiplex query handling requiring user interaction. No exploitation or public exploit code has been observed as of August 18, 2026.

The Hacker News · Aug 17, 2026VulnerabilityCVE-2026-19478CVE-2026-196501

Towards Scalable and Cost-Efficient Vulnerability Detection: A Study on Automatic Query Generation

A study finds LLM-synthesized CodeQL queries improve average F1-score by 82% over baseline queries, offering scalable vulnerability detection versus direct LLM scanning.

Researchers conducted an empirical study evaluating whether LLMs can synthesize executable CodeQL queries from National Vulnerability Database vulnerability data. LLM-generated queries significantly enhanced baseline CodeQL suites, yielding an 82% improvement in average F1-score across a diverse set of real-world vulnerabilities. A cost-benefit analysis shows direct LLM-based scanning of entire repositories is often computationally and financially prohibitive, while LLM query synthesis offers a scalable and cost-effective alternative for large-scale vulnerability detection.

arXiv cs.CR · 7d agoResearch1

GitLab Warns of Active Exploitation of Critical GraphQL Flaw

GitLab emergency-patches actively exploited flaw CVE-2026-19478 (CVSS 9.4), letting unauthenticated attackers modify or delete public projects on self-managed servers.

GitLab emergency-patched CVE-2026-19478 (CVSS 9.4) on August 17 after WatchTowr researchers warned of active exploitation. The flaw lets unauthenticated attackers remotely modify or delete public projects and user data through a GraphQL directive, affecting only self-managed installations. Fixes ship in versions 19.2.4, 19.1.6, 19.0.8, and 18.11.11; the 18.2-18.10 branches receive no patch and must upgrade. Until patching, defenders should restrict unauthenticated access to /api/graphql, disable public repositories, and hunt for @gl_introduced in logs.

Security Affairs · 25d agoExploit / PoC in the wildCVE-2026-194781

Procedural Graphs: Self-Evolving Execution Structures for LLM Agents

Researchers introduce Procedural Graphs, self-evolving (procedure, relation, procedure) structures guiding LLM agent tool use and planning.

Procedural Graphs organize procedural knowledge into (procedure, relation, procedure) triplets to guide LLM agent actions, addressing drift such as lost objectives, out-of-order tool calls, and repeated unproductive steps. At each decision step the framework localizes the active node and a guidance model translates the surrounding subgraph into step-level situational guidance. An LLM refiner edits graph topology by contrasting failed with successful trajectories, and across datasets, task types and LLMs the approach outperforms memory-based baselines and matches or surpasses hand-designed graphs.

arXiv cs.AI / cs.LG / cs.CL · 8d agoAI research1

The Gopher in the Room: Analysis of GoLang Malware in the Wild

Unit 42 analysis of 10,700 Go-compiled malware samples shows steady growth in the wild, with 92% targeting Windows and top families including Veil, GoBot2, and HERCULES.

Unit 42 collected roughly 10,700 unique Go-compiled malware samples and found that Go usage by malware developers has steadily risen in recent months. About 92% of samples targeted Windows and 75% were attributed to known families, led by Veil, GoBot2, and HERCULES. The most prevalent groupings were penetration testing tools, remote access Trojans, and backdoors. Statically linked Go binaries average 4.65MB, which can complicate phishing delivery but sometimes causes antivirus products to skip or fail scanning.

Palo Alto Unit 42 · Aug 17, 2026Research1

A First-Principles Evaluation of Graph-Based Network Intrusion Detection Systems

GIDS-Eval framework reveals evaluation gaps in graph-based network intrusion detection; two crafted edges fully evade three detector-dataset pairs.

Researchers introduce GIDS-Eval, a framework decomposing graph-based network intrusion detection systems into six interchangeable stages to enable controlled comparisons. Surveying nine GIDS and reimplementing five, they find two crafted edges achieve full evasion against three of eight detector-dataset pairs, snapshot windows alone cause a mean 38.3% relative swing in average precision, and none of 18 replayed detector-dataset pairs can alert as events arrive. Their encoder-free GIDS-Lite control ranks first by AP on two of four datasets at up to 575x lower runtime.

arXiv cs.CR · 6d agoResearch1

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 · AI · 2d agoAI industryHN 41↑ · 13 comments1

Critical GitLab Flaws Let Attackers Read Arbitrary Files, Steal Credentials and Execute Code

GitLab issues emergency patches for critical path-traversal flaw CVE-2026-85706 (CVSS 10.0), GraphQL credential exposure CVE-2026-87719, and potential RCE flaw CVE-2026-88765.

GitLab released versions 19.3.2, 19.2.6, and 19.1.8 on September 10, 2026, fixing 18 vulnerabilities across Community and Enterprise Editions. CVE-2026-85706 allows unauthenticated arbitrary file reads via the repository commits API; CVE-2026-87719 exposes Advanced Search credentials through GraphQL subscription deserialization; CVE-2026-88765 may enable authenticated RCE via crafted project export imports. No exploitation was reported, but self-managed administrators are urged to upgrade immediately and review logs for suspicious API and GraphQL activity.

GBHackers · 5d agoVulnerabilityCVE-2026-85706CVE-2026-87719CVE-2026-88765+15 CVEs1

Now everyone can put data to work

OpenAI launched a Data agent in ChatGPT Work that connects to enterprise warehouses and builds shareable analysis dashboards without SQL.

OpenAI introduced a Data agent in ChatGPT Work that connects to approved sources including Snowflake, BigQuery, Databricks, Redshift, ClickHouse, MongoDB, and Datadog, plus files from Google Drive and SharePoint. It investigates metric changes, builds interactive dashboards, and integrates with BI tools such as Power BI, Tableau, Omni, Sigma, and ThoughtSpot using semantic layers from dbt, Databricks Genie Ontology, and Snowflake Horizon. Queries enforce the connected account's existing table, row, and column permissions, with administrators controlling access via Workspace settings. OpenAI says nearly all of its product team and over two-thirds of its GTM organization use it internally, and NTT Data, Thermo Fisher, and ServicePiston are Alpha customers.

OpenAI News · 6d agoAI industry

[webapps] Langflow 1.8.4 - Path Traversal to Remote Code Execution

A path traversal to remote code execution exploit for Langflow 1.8.4, a popular LLM application builder, was published on Exploit-DB.

Exploit-DB lists a proof-of-concept exploit chaining path traversal to remote code execution in Langflow 1.8.4, an open-source tool used to build LLM applications and agents. The chain allows an attacker to write arbitrary files outside the intended directory and achieve code execution on the host. The provided text does not include a CVE identifier or reports of exploitation in the wild, but RCE in a widely deployed AI tooling product is notable for defenders.

Exploit-DB · 16d agoExploit / PoC1

Procedural Graphs: Self-Evolving Execution Structures for LLM Agents

Procedural Graph framework stores procedural knowledge as triplets and self-evolves via LLM refinement, beating memory-based baselines across datasets, tasks, and LLMs.

The Procedural Graph organizes procedural knowledge into (procedure, relation, procedure) triplets; at each decision step the framework localizes the agent's active node and a guidance model translates the surrounding subgraph into step-level guidance that biases the solver's next action. An LLM refiner contrasts failed with successful trajectories and edits the graph's topology and attributes, retaining rejected edits to discourage repetition. Starting from a minimal skeleton, the loop builds graphs that match or surpass hand-designed ones and can repair flawed expert priors, delivering consistent gains over memory-based baselines across multiple datasets, task types, and LLMs.

Hugging Face daily papers · 9d agoAI research1

GraphProfiler: Source-Linked Sensitive Attribute Inference via Personal Knowledge Graphs

GraphProfiler links LLM attribute inferences to source posts via personal knowledge graphs, enabling targeted redaction of privacy-leaking content.

GraphProfiler represents a user's post history as a source-linked personal knowledge graph where nodes and edges trace back to originating posts, making LLM-based attribute inference auditable. It reaches 86.7% attack success rate on the eight-attribute SynthPAI benchmark and 84.6% on PANDORA, within two points of strong text-only baselines, while citing supporting evidence for over 98% of predictions. Ablation experiments show removing cited posts reduces attack success substantially more than removing random posts, supporting targeted privacy mitigation.

arXiv cs.CR · 5d agoResearch1

GitLab Patches Critical Unauthenticated GraphQL Vulnerability

GitLab issued an emergency patch for a critical unauthenticated GraphQL flaw (CVE-2026-19478, CVSS 9.4) enabling remote modification or deletion of public projects.

GitLab patched CVE-2026-19478 (CVSS 9.4), an unauthenticated GraphQL directive flaw allowing remote modification or deletion of public projects and user data on self-managed servers. The emergency patch released August 17 covers versions 19.2.4, 19.1.6, 19.0.8, and 18.11.11, but no fixes exist for the 18.2-18.10 branches. A second issue, a CSRF weakness in GraphQL multiplex queries (CVE-2026-19650, CVSS 7.1), shipped in the same release. No exploitation or public PoC has been observed; the flaw was reported by hiimguardian through HackerOne.

Security Affairs · 29d agoVulnerabilityCVE-2026-19478CVE-2026-196501

τ^τ-Bench: An Environment for End-To-End, Realistic Agent Construction

New τ^τ-bench tasks coding agents with building deployable customer-service agents; best config, Claude Opus 5, passes only 23.9% of simulations.

Researchers introduce τ^τ-bench, an end-to-end benchmark where a developer agent must build a complete customer-service agent from real business records, a client with requirements, a production API, an inherited codebase, and cost/model limits, then is scored by deploying it against held-out simulated users. Across 53 tasks in four domains, the strongest configuration, Claude Opus 5 under Claude Code, passes just 23.9% of evaluation simulations versus an 82.2% expert-authored reference ceiling. Failure modes mirror those of human developers: shallow queries instead of deep record comprehension, almost no client communication, and shipping the first architecture that runs rather than experimenting.

Hugging Face daily papers · 13d agoAI research

An Empirical Analysis of CodeQL False Positives and Query Refinements for Java Vulnerabilities

Study of 167 Java CVE instances finds CodeQL false positives follow recurring patterns; query refinements remove 81.8% of reviewed ones.

Researchers ran CodeQL's Java security query suite on 167 CVE instances from 110 projects, manually reviewing 500 sampled false-positive paths and building a five-category taxonomy led by Missed Path Constraint or Sanitization (36.6%), Benign Execution Context (29.4%), and Missing Trust Boundary Modeling (27.6%). Guided by the taxonomy, query-level refinements removed 81.8% of reviewed false positives and 15.8% of reported paths across the selected queries while retaining 7 of 8 true positives. To address generalization, agentic coding tools given the refinement patterns as templates adapted them to new projects successfully in 56% and 62% of tasks, versus 28% without guidance.

arXiv cs.CR · 13d agoResearch1

Analyzing a Go-Based IoT Self-Propagating DDoS Botnet

Akamai researchers published an analysis of a Go-based, self-propagating IoT botnet used for DDoS attacks.

Akamai's security research team published an analysis of a self-propagating DDoS botnet written in Go that targets IoT devices. Detailed technical findings were not available in the provided source text, which included only the title.

Akamai Blog · 13d agoMalware in the wild

Atlas: Efficient Verifiable Semantic Search

Atlas delivers zero-knowledge proofs for HNSW semantic search, verifying RAG retrieval in under a second on SIFT1M and 2.0 seconds at 100M vectors.

Atlas lets a search provider prove that a query was answered correctly against a committed HNSW index without revealing the index, addressing provider deviations like truncation or bias. It combines offline preprocessing, a fixed-size-state restructuring of HNSW with a correctness proof, and timestep-tagged batching of per-step arguments. The system proves queries in under a second on SIFT1M and 2.0 seconds at 100 million vectors while preserving plaintext HNSW recall, and proven retrieval maintains end-to-end RAG answer quality at lower cost than prior verifiable retrieval systems.

arXiv cs.CR · 6d agoResearch1

Private Information Retrieval With Arbitrary Privacy Requirements: Introduction and Capacity Results

Researchers formulate private information retrieval under arbitrary graph-based privacy requirements, deriving capacity bounds and introducing pyramid storage graphs.

The paper generalizes classical private information retrieval (PIR) to arbitrary privacy requirements over graph-based storage systems, where each message is retrieved privately from a pre-specified server subset. The authors derive lower and upper capacity bounds for general graphs and exact capacity results for path and cyclic storage graphs. They also introduce a new pyramid storage graph structure that models symmetric message storage and replication patterns.

arXiv cs.CR · 2d agoResearch

Feyospace-v1: How the Cyber Mercury Seven Trained Frontier Cyber Models

A seven-person independent team trained open-weight agentic cyber models via a data-centric post-training framework, ranking 10th on CyberGym and first at comparable scale.

The paper presents Feyospace-v1, a data-centric post-training framework combining five systems: Choulea (hidden reasoning analysis), SkyReal (teacher-sampling cost reduction), Hongzwang (bypassing teacher API restrictions), PSBreakup (restoring capabilities weakened by model merging), and Kreator (converting expert interventions into trainable reasoning). The data engine builds resettable coding, vulnerability, CTF, kernel-history, full-exploit, firmware, and device-backed environments, retaining only execution-verified and evidence-audited trajectories, yielding 164,269 trajectories for long-context supervised fine-tuning. Three checkpoints improve over their starting models by an average of 23.76% on the full CyberGym suite and 10.49% across pooled CTF suites. As of September 1, 2026, Feyospace-s1 achieves a 63.24% verified success rate, ranks 10th on the official CyberGym leaderboard, and all three checkpoints rank 1st among models at comparable parameter scales.

Hugging Face daily papers · 9d agoAI research

From Parameters to Answers: How LLMs Retrieve and Use Their Internal Knowledge

Interpretability study traces how Qwen, Llama, and Gemma route query information and internal knowledge across layers when answering questions.

Researchers used layerwise interventions on hidden states to separate query-routing signals from target knowledge in language models, testing Qwen, Llama, and Gemma on country-continent questions with varied answer types. A pair-conditioned request direction strengthens before interventions alter downstream knowledge, opening a causal window while answer-supporting content is still forming. Trajectories differ by model: Gemma shows a partially overlapping mid-layer routing profile, while Llama has no sustained routing-effect window under the same gates.

arXiv cs.AI / cs.LG / cs.CL · 6d agoAI research1

DataFlex-RL: An Evaluation Platform for RLVR Data Policies

DataFlex-RL benchmark of 13 RLVR data policies on Qwen2.5-7B finds none reproducibly beats uniform sampling under matched GRPO training.

DataFlex-RL is an evaluation platform comparing rollout-selection, reweighting, and mixture data policies for RLVR under a common GRPO recipe. Across 13 configurations and 12 matched seeds with Qwen2.5-7B-Base on 12 math, logic, and science benchmarks, uniform GRPO improved domain-balanced accuracy by 7.76 points, but no alternative policy achieved a statistically significant improvement. A corrected 12-seed Llama-3.1-8B-Base extension found no consistent winner, and math-heavy evaluation summaries were negatively correlated (-0.33) with domain-balanced summaries.

Hugging Face daily papers · 12d agoAI research

Miles v0.1: Production-Level Post-Training

Radix Ark open-sources Miles v0.1, a full-stack RL post-training framework demonstrated with asynchronous agentic RL on GLM-5.2 744B-A40B across 64 GB300 GPUs.

Miles v0.1 is a full-stack, open-source system for frontier-scale reinforcement-learning post-training, built on slime with rollout engines on SGLang and trainers supporting NVIDIA Megatron-LM and PyTorch FSDP backends plus three weight-synchronization transports. It supports full-parameter RL, LoRA RL, on-policy distillation, supervised fine-tuning, true-on-policy rollout-training alignment, and extends to diffusion models. The end-to-end case study ran fully asynchronous agentic RL on GLM-5.2 744B-A40B for terminal-use coding tasks on 64 NVIDIA GB300 GPUs with a median step time of 263 seconds over the first 30 measured steps. The code is open-sourced on GitHub.

Hugging Face daily papers · 9d agoAI tools & infra

Dark Caracal Deploys New Go Malware With Ethereum-Based C2 Fallback

Dark Caracal targeted a Venezuelan communications organization with new Go-based GoCaracal malware and an updated Bandook backdoor using Ethereum smart-contract C2 fallback.

Arctic Wolf Labs linked a June 2026 intrusion against a communications organization in Venezuela to Dark Caracal, an espionage group associated with Lebanon's General Directorate of General Security (GDGS). The group deployed a previously undocumented Go-based framework called GoCaracal in lightweight and extended builds alongside a Delphi-loaded Bandook backdoor, with delivery via phishing emails carrying weaponized SVG attachments through URL shorteners. The extended build uses a custom Solidity contract, BulletproofC2, on Ethereum to retrieve replacement C2 addresses without redeploying malware, and Arctic Wolf traced 249 related samples from January to July 2026 showing a modular evolution arc.

Security Affairs · 20d agoThreat actor in the wild

Automating Attack Graph Construction for Agentic Pentesting. Towards Neuro-Symbolic Vulnerability Hunting

Semi-automated pipeline converts Trivy, Semgrep, Nmap output into MulVAL attack graphs for agentic pentesting, 53.7% mean vulnerability coverage in CyBench.

The paper presents a semi-automated pipeline that parses Trivy, Semgrep, and Nmap findings into MulVAL predicates and uses an LLM-assisted process to build domain-specific Datalog rules linking scanner evidence to attack techniques. MulVAL/XSB then performs symbolic inference to generate structured, auditable attack paths for agentic pentesting. Evaluated on 54 web CTF tasks from CyBench, every task produced at least one goal-reaching graph with 53.7% mean ground-truth vulnerability coverage, 51.9% full coverage, and an 83.9% noise-path rate. Median end-to-end runtime was 24.9 seconds, making the pipeline runtime-practical for agentic workflows.

arXiv cs.CR · 2d agoResearch

The OpenClaw 2.0 release moves your sessions into SQLite

OpenClaw 2.0 migrates AI agent sessions to SQLite, adds guided credential setup, and flags shared-session controls as not a security boundary.

OpenClaw 2.0, described as the largest update in the project's history, migrates sessions and transcripts into SQLite and adds guided setup that detects existing AI credentials from Codex, ChatGPT, Claude CLI sign-ins, API keys, and local Ollama or LM Studio models. The release expands multiplayer sharing while explicitly stating its permission controls are not tenant isolation or a security boundary, and that revoked access can briefly remain usable. Startup JavaScript requests fell from 140 to 45 and startup time from about 1.6 seconds to 575 milliseconds in simulated tests against a mocked Gateway. Automation wrappers must now inspect reported health because requesting --json does not waive risk acknowledgement.

Help Net Security · 16d agoAI tools & infra1

Rapidly scaling online storage to serve over 1 billion ChatGPT users

OpenAI's Habitat online storage platform now handles over 70 million requests per second and 500 PB of data for 1 billion users.

OpenAI details the evolution of Habitat, its online storage platform backing ChatGPT and other products, which began in mid-2024 as a Python client-side library over Azure Cosmos DB. Habitat now processes more than 70 million requests per second, serves over 500 petabytes of data across nearly 40 geographic regions, and supports over 1 billion users weekly. By mid-2025 the client library approach became brittle, so OpenAI moved Habitat into a standalone service to centralize deployments, observability, and multi-tenancy reliability. This is part one of a two-part series; a future post will cover read optimization and scaling the Azure Cosmos DB partnership.

OpenAI News · 5d agoAI tools & infra1

How to connect AI usage to business value

OpenAI explained how ChatGPT Admin Console analytics link AI usage, spend, and Codex contributions to business outcomes.

OpenAI published guidance describing analytics features in the ChatGPT Admin Console that combine usage, credit, and token data across ChatGPT Work and Codex. The Insights task classifier groups messages into use cases such as software engineering and sales research, while an Outcomes view tracks Codex contributions to merged commits and lines of code. An Admin plugin and Admin API let teams automate reporting and combine AI analytics with business metrics like ticket resolution time or revenue.

OpenAI News · 11h agoAI industry