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IBM security advisory (AV26-922)

Canadian Cyber Centre relays IBM advisory for Langflow, MQ, and Sterling File Gateway flaws including MQ remote code execution (CVE-2026-13293).

Canadian Cyber Centre advisory AV26-922 relays IBM fixes for Langflow OSS (versions through 1.11.5 across release lines), IBM MQ (10.0.0.0 and 9.x LTS/CD through 9.4.5.1), and Sterling File Gateway (through 6.2.2.1). CVE-2026-13293 is a remote code execution flaw in IBM MQ Java messaging caused by an incomplete security scanner blocklist enabling network-based code execution. CVE-2026-19290 is an improper access control vulnerability in IBM Sterling File Gateway. Administrators are urged to review and apply the necessary updates.

Canadian Centre for Cyber Security · 23h agoAdvisoryCVE-2026-13293CVE-2026-19290

August 2026 CVE Landscape

Insikt Group catalogs 73 high-impact August 2026 CVEs (43 Very Critical), including PaperCut, Zimbra, and Metabase flaws actively exploited or weaponized.

Recorded Future's Insikt Group identified 73 high-impact vulnerabilities in August 2026, 43 rated Very Critical, spanning 45 vendors with Microsoft accounting for roughly 11%. 31 vulnerabilities surfaced via CISA's KEV catalog, with others validated via open sources, vendor telemetry, and honeypot data. New Nuclei detection templates were released for CVE-2025-62593 (Ray), CVE-2026-72898 (Metabase), and CVE-2026-9198 (IBM Langflow). The report also highlights two AI-assisted operations: UAT-10147 exploited Zimbra, AjaxPro, Nacos, and Telerik servers before using DeepAudit and PentestGPT post-compromise, while a separate Chinese-speaking actor weaponized Hermes Agent and DeepSeek in a failed attempt.

Recorded Future · 8d agoVulnerability in the wildCVE-2025-62593CVE-2026-72898CVE-2026-9198+4 CVEs

[webapps] Langflow 1.10.0 - RCE

A public proof-of-concept demonstrates remote code execution in Langflow 1.10.0, the open-source AI workflow builder.

Exploit-DB lists a remote code execution proof of concept targeting Langflow version 1.10.0. Langflow is a widely used open-source tool for building AI agent and LLM workflows. The listing does not include a CVE id or evidence of in-the-wild exploitation, but RCE in AI development tooling is relevant to teams running it in production.

Exploit-DB · 14d agoExploit / PoC1

[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

Critical Langflow Vulnerability Exploited as Attacks on AI Platform Rise

Attacks exploiting CVE-2026-0768, a critical vulnerability in the Langflow low-code AI platform, are rising amid growing adversary attention this year.

CVE-2026-0768 is a critical vulnerability in Langflow, a low-code AI development platform, with exploitation attacks now rising. Dark Reading notes the platform has drawn increasing adversary attention in 2026. Organizations running exposed Langflow instances face elevated risk and should patch promptly and review instances for compromise.

Dark Reading · 14d agoExploit / PoC in the wildCVE-2026-07681

Langflow Remote Code Execution Vulnerability Exploited in Attacks (CVE-2026-0768)

Critical CVSS 9.8 RCE CVE-2026-0768 in Langflow is under active exploitation, with attackers probing for credentials and secrets.

CVE-2026-0768, a critical (CVSS 9.8) remote code execution flaw in Langflow's code validator, lets attackers execute Python code with root privileges via the validate endpoint's code parameter. VulnCheck honeypots in the UK detected Russian-origin exploitation performing reconnaissance and credential harvesting, querying environment variables like LANGFLOW_SUPERUSER and AWS keys and reading Langflow's secret key. Versions before 1.4.2 are affected; no vendor advisory or public PoC was available at reporting time.

Qualys ThreatPROTECT · 13d agoExploit / PoC in the wildCVE-2026-0768CVE-2026-33017CVE-2026-5027+1 CVEs1

Attackers Exploit MLflow SSRF Flaw to Steal Cloud Credentials and Secrets

Attackers exploit MLflow SSRF CVE-2026-64849 (CVSS 9.3) to steal cloud credentials; CISA added it to KEV; FUXA flaw CVE-2026-25895 is being scanned.

watchTowr observed exploitation of MLflow CVE-2026-64849, an unauthenticated SSRF (CVSS 9.3) affecting versions below 3.15.0, within hours of CVE assignment on August 17, 2026, with attackers abusing model-registry webhooks to reach cloud metadata endpoints and exfiltrate credentials and secrets. CISA added the flaw to its Known Exploited Vulnerabilities catalog on August 19, 2026, with a September 2 patch deadline for federal civilian agencies. VulnCheck reported scanning of FUXA CVE-2026-25895 (missing authentication plus path traversal, CVSS 9.5, versions through 1.2.9) beginning August 18; about 60 FUXA instances are exposed and no RCE payloads have been dropped yet.

The Hacker News · 27d agoExploit / PoC in the wildCVE-2026-64849CVE-2026-25895CVE-2026-25939+1 CVEs

CVE-2026-0770: Langflow exec_globals RCE Vulnerability

CVE-2026-0770 is a critical unauthenticated remote code execution vulnerability in Langflow's exec_globals, endangering exposed deployments.

CVE-2026-0770 is a critical remote code execution vulnerability in Langflow, a popular open-source framework for building language model applications. It allows remote attackers to execute arbitrary code on affected installations without authentication, making internet-exposed deployments particularly dangerous. The flaw resides in the exec_globals component; the available disclosure does not state active exploitation or provide patch details.

Web discovery (articles for new exploits & KEV entries) · 23d agoVulnerabilityCVE-2026-0770

Hackers Target Langflow in CVE-2026

Threat actors are actively exploiting CVE-2026-0768, an unauthenticated Python RCE in Langflow, hunting OpenAI, AWS, and SSH credentials.

Attackers began exploiting CVE-2026-0768 (CVSS 9.8), an unauthenticated remote code execution flaw in the code validator of the Langflow AI low-code platform, affecting all versions up to 1.4.2. VulnCheck observed 50+ Canary detections on the first day of exploitation, with attackers checking Langflow, OpenAI, and AWS keys in environment variables, reading the secret key, and looking for SSH access and shell history; most traffic originates from Russia and targeted UK-based canaries. The flaw was reported via ZDI by Trend Research in July 2025 and disclosed in January 2026; six other Langflow CVEs were added to VulnCheck's KEV list this year.

Security Affairs · 14d agoExploit / PoC in the wildCVE-2026-07682

Attackers Exploit Critical Langflow and Rails Flaws in Credential

VulnCheck reports active exploitation of critical Langflow CVE-2026-0768 and Rails CVE-2026-66066 for credential harvesting, with detections rising to 360.

VulnCheck observed active exploitation of CVE-2026-0768 (CVSS 9.8) in Langflow and CVE-2026-66066 'KindaRails2Shell' (CVSS 9.5) in Ruby on Rails, with detections rising from 50 on August 30, 2026 to 360 by September 1. The Rails flaw allows unauthenticated arbitrary file reads, leaking secret_key_base, Rails master key, database passwords, cloud credentials and API tokens, ultimately enabling RCE; the patch still leaves the variation-key Marshal deserialization RCE gadget functional. Observed chains include a Python credential harvester with SimpleHelp remote access via CVE-2026-5027, and weaponization of CVE-2025-3248 to enlist hosts into an XMR mining botnet after disabling auditd. More than 7,100 exposed vulnerable Ruby on Rails instances and over 15,000 successful exploitation attempts across three Langflow flaws were recorded.

The Hacker News · 15d agoExploit / PoC in the wildCVE-2026-0768CVE-2026-66066CVE-2026-0769+2 CVEs1

U.S. CISA adds a MLflow flaw to its Known Exploited Vulnerabilities catalog

CISA added actively exploited MLflow SSRF flaw CVE-2026-64849 (CVSS 9.3) to its KEV catalog; attackers are stealing cloud credentials from exposed instances.

CISA added CVE-2026-64849, a critical unauthenticated server-side request forgery in MLflow, to its Known Exploited Vulnerabilities catalog. The flaw affects MLflow versions before 3.15.0 and allows unauthenticated attackers to reach internal services including cloud metadata endpoints, exposing temporary cloud credentials. watchTowr observed in-the-wild exploitation exfiltrating credentials and secrets, plus widespread scanning of exposed MLflow instances within hours of the CVE's assignment on August 17, 2026. MLflow is an open-source platform for managing the machine learning and AI development lifecycle with over 60 million monthly downloads.

Security Affairs · 27d agoExploit / PoC in the wildCVE-2026-64849

Context Engineering Inside the Harness: 4 Mechanisms That Beat Context Overflow and Goal Loss on Long-Horizon Tasks

Survey of four harness mechanisms—context budgeting, compaction, todo-state, and memory—that keep long-horizon LLM agents on task across 200+ tool calls.

The article details how agent harnesses, not larger context windows, solve context overflow and goal loss on long-horizon tasks, citing Chroma's Context Rot report showing 18 LLMs (GPT-4.1, Claude 4, Gemini 2.5, Qwen3) degrade on long inputs. Concrete implementations include LangChain Deep Agents offloading tool responses over 20,000 tokens to the filesystem and truncating old tool calls at 85% window usage, and Claude Code capping auto memory at 25KB while re-reading the 5 most recently modified files after compaction. OpenAI's Responses API now offers server-side compaction via context_management with a standalone /responses/compact endpoint, which Codex uses for long-running coding tasks. Manus reports a roughly 100:1 input-to-output token ratio per ~50-tool-call task, motivating todo.md state recitation to prevent goal drift.

MarkTechPost · 3d agoAI research1

Intezer adds native response automation without separate SOAR

Intezer launched Workflows, native response automation inside its AI SOC, letting teams automate remediation without a separate SOAR platform.

Intezer announced Workflows, a native automation and response builder inside its AI SOC platform that lets security teams run post-investigation actions such as closing alerts, isolating hosts, and updating tickets without a separate SOAR. Workflows are created through natural language via MCP, inherit full investigation context, and are logged for audit, with per-tenant routing and customer communications aimed at MSSPs. The announcement cites Intezer's AI SOC Report 2026 finding that nearly 1% of real incidents trace back to lowest-severity alerts.

Help Net Security · 28d agoTools

IBM security advisory (AV26-862)

Canada's Cyber Centre relayed an IBM advisory disclosing vulnerabilities across SPSS, MQ, Maximo, Instana, Concert and other IBM products.

The Canadian Centre for Cyber Security (AV26-862) published an IBM security advisory dated August 31, 2026, noting vulnerabilities affecting multiple IBM products as of August 28, 2026. Affected products include SPSS Collaboration and Deployment Services, IBM MQ Agent, Maximo Application Suite Monitor Component, Observability with Instana agent, Financial Transaction Manager for Red Hat OpenShift, Engineering Test Management, Control Center, Concert Software and Tivoli System Automation. No CVE identifiers, CVSS scores or exploitation details are provided in the relayed text.

Canadian Centre for Cyber Security · 15d agoAdvisory

E-Commerce Access, Vedicline Data, Langflow RCE, ASUS Claim, and Energy Shell Access

SOCRadar reports underground posts claiming a Bangladeshi e-commerce database, Vedicline data leak, Langflow RCE, ASUS breach, and energy-sector shell access.

SOCRadar's Dark Web Team identified several new underground posts, including an alleged Bangladeshi e-commerce customer database offered for sale. The roundup also covers a claimed Vedicline data leak, Langflow remote code execution, an ASUS breach claim, and energy-sector shell access sales. Details on record counts and victims were not provided in the excerpt.

SOCRadar · 9d agoData breach

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.

MarkTechPost · 5d agoAI tools & infra

FreeFlow: A Bias-free Hierarchical Transformer for Optical Flow Estimation

FreeFlow is a bias-free hierarchical transformer achieving state-of-the-art optical flow results on Sintel, KITTI-2015, and Spring benchmarks.

FreeFlow replaces task-specific inductive biases like correlation volumes and iterative warping with a single feed-forward encoder-decoder combining window, shifted-window, and reduced-resolution global attention. It reaches 0.68/1.48 EPE on Sintel Clean/Final, 3.23 Fl-all on KITTI-2015, and 3.192 1px on Spring. The architecture scales consistently from small to large variants and remains memory efficient at 1080p inference.

Hugging Face daily papers · 6d agoAI research

Discrete Beckmann Transport Models for One-Step Language Modeling and Reasoning

DBTM achieves one-step text generation via a time-independent transport map trained directly from data, removing pretrained teacher distillation.

Discrete Beckmann Transport Models (DBTM) build a time-independent flow whose autonomous transport map provably carries any point in ambient space to a fixed point on simplex vertices in a single step. The fixed-point property is characterized by a conservation equation whose residual can be minimized directly from data, eliminating the need for a teacher flow, distillation, and time conditioning. A partial-context interpolant extension turns additional function evaluations into refinement steps rather than ODE integration steps. On language modeling and reasoning tasks, DBTM's one- and few-step generation improves quality and accuracy over discrete diffusion and continuous flow baselines.

arXiv cs.AI / cs.LG / cs.CL · 1d agoAI research1

IndicTriMix: Developing Language Identification Datasets and Models for Tri-Language Code-Mixing

Researchers release IndicTriMix benchmarks and fine-tuned MuRIL and XLM-RoBERTa models for token-level language identification in tri-language code-mixed text.

The paper formulates token-level language identification in code-mixed text as a sequence labeling task and fine-tunes MuRIL and XLM-RoBERTa transformer models for Indian languages. It evaluates on Hindi, Gujarati, and Bengali configurations with manually annotated test sets and proposes two code-mixed generation approaches using parallel trilingual sentences. A public benchmark, annotated test sets, and fine-tuned models are released for reproducibility.

arXiv cs.AI / cs.LG / cs.CL · 5d agoAI research1

Unifying Conformal Language Tasks with In-Context Ensembles

Researchers propose Conformal Relevance, which builds conformal score functions via in-context example curation and ensembling to improve conciseness across seven NLP tasks.

The paper targets NLP tasks like summarization and extractive QA that reduce to retrieving content under coverage and conciseness constraints. Conformal Relevance replaces hand-engineered LLM scoring prompts with curated in-context examples and ensembles, maintaining coverage guarantees while improving conciseness with minimal manual input. The authors demonstrate the framework on seven NLP tasks and contribute theory, including a complementarity condition for when ensembling improves worst-case sentence scores and a saturation bound on ensemble gains.

Hugging Face daily papers · 14d agoAI research1

Building Multilingual Bridges: Data Mixing as the Pillar of Generalization for In-Language Reasoning

Tiny Aya L2-Thinker, a 3.35B model, achieves over 93 percent in-language reasoning across 60 languages via optimized multilingual data mixing; weights released.

The paper studies L2 reasoning, the ability to reason consistently in the language of the user's prompt, approached through SFT data composition and scheduling. Tiny Aya L2-Thinker (3.35B) achieves an in-language reasoning rate above 93 percent across 60 languages on six benchmarks spanning math, commonsense, instruction following, open-ended generation, and cultural reasoning. Findings show generalization to held-out languages comes from broader language coverage, multilingual non-reasoning data, and a strong English reasoning backbone, suggesting reasoning is language-agnostic and transferable without per-language supervision. Model weights and multilingual reasoning data are publicly released.

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

The Semantic Bottleneck: Leveraging Semantic Representations for Non-Invasive Speech Decoding

Researchers introduced Brain2Semantics2Text, decoding sentence meaning from non-invasive MEG brain recordings via a semantic bottleneck, improving on prior Brain2Text methods.

The paper proposes Brain2Semantics2Text, a non-invasive speech decoding method that maps sentence-level magnetoencephalography (MEG) responses into a semantic embedding space and inverts those embeddings into natural language. Motivated by evidence that high-level semantic representations are distributed across cortex and evolve on slower timescales, the approach targets meaning rather than phonemes or words, avoiding the need for word-level alignment. The authors report improved sentence-level results compared to prior non-invasive Brain2Text methods despite the low signal-to-noise ratio of neural recordings.

Hugging Face daily papers · 7d agoAI research2

ToolLoop: Closed-Loop Tool-Use Data Synthesis via Decomposed Generation and Dynamic Self-Feedback

ToolLoop introduces a closed-loop synthetic data framework whose 11K examples lift a 4B model to 86.40% on BFCL tool-use evaluation.

ToolLoop decomposes tool-use data synthesis into function-name sampling, backward derivation of user queries, and forward derivation of tool calls, with dynamic self-feedback at each stage. This shifts the paradigm from generate-then-filter to generate-verify-refine, reducing inefficient and imbalanced synthetic data. A 4B model trained on 11K synthetic examples reaches 86.40% accuracy on BFCL non-reasoning mode (86.07% in an Isolate variant excluding BFCL-overlapping functions) and 72.1% on ACEBench using only 18.3% of baseline training data.

arXiv cs.AI / cs.LG / cs.CL · 7d agoAI research1

Pre-Whitening and BCJR Posterior Distillation for Bi-LSTM Detection in Faster-than-Nyquist Signaling

Study shows nested-window Bi-LSTM architectures do not improve faster-than-Nyquist detection; pre-whitening plus BCJR distillation cuts bit error rates.

Across roughly 260 controlled trainings, processing nested intersymbol-interference windows in separate recurrent branches never significantly beat a plain Bi-LSTM at matched parameter budgets. The authors attribute the limitation to the observation model rather than architecture, and instead pre-whiten inputs and distill BCJR soft posteriors into the network. With 3.4% more parameters, the method reaches 1.05x the BCJR bit error rate at compression factor 0.8 and 1.89x at 0.7, improving to 1.47x with a wider whitened window.

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

Akamai Valkey Managed Database: Real-Time Memory for Enterprise AI

Akamai launched Valkey Managed Database, a low-latency in-memory data layer aimed at cutting AI inference costs and accelerating RAG.

Akamai introduced Valkey Managed Database, a managed in-memory data service based on the open-source Valkey project. The company positions it as real-time memory for enterprise AI, optimizing inference costs, accelerating retrieval-augmented generation, and powering real-time AI agents.

Akamai Blog · 29d agoAI tools & infra

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 · 5d agoAI research1

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 papers · Aug 11, 2026AI tools & infra1

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 · 6d agoResearch1

Φ-Bench: Can Large Language Models Engineer the Infrastructure That Powers Them?

Researchers release Phi-Bench, a benchmark evaluating frontier LLMs on open-ended, long-horizon engineering and optimization of the LLM infrastructure stack.

Phi-Bench evaluates LLMs on open-ended engineering of the LLM infrastructure stack, derived from optimization problems studied in frontier research and grounded in real-world code repositories. Tasks range from localized kernel-level function completion to long-horizon implementation and end-to-end system optimization. Experiments on frontier LLMs reveal current capabilities and limitations on the path toward autonomous optimization of future AI infrastructure.

Hugging Face daily papers · 7d agoAI research1