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CategoryAll Exploit / PoC 2 Phishing & fraud 2 AI safety & security 1 AI tools & infra 1 Malware 1 Tools 1 Model release 1 Vulnerability 1 AI research 1

SeverityAll critical 0 high 2 medium 4 low 0 info 5

Apache Superset SQL Injection Flaw Gets Public PoC Exploit

A public Python proof-of-concept exploit was released for CVE-2026-23980, an authenticated error-based SQL injection flaw in Apache Superset before 6.0.0.

A public proof-of-concept exploit repository now targets CVE-2026-23980, an error-based SQL injection affecting Apache Superset versions from 0.0.0 up to but not including 6.0.0. An authenticated user with read access can inject SQL through the sqlExpression or where parameters, potentially reaching business, customer, and security data depending on database configuration and privileges. Apache disclosed the flaw in February and urges upgrading to Superset 6.0.0; compensating controls include least-privilege database accounts, network restrictions, and log monitoring.

GBHackers09:23 UTC · 10h agoExploit / PoC 2 sources CVE-2026-23980

Public PoC Released for Apache Superset SQL Injection Vulnerability

A public Python PoC exploit is available for CVE-2026-23980, an authenticated error-based SQL injection in Apache Superset versions before 6.0.0.

CVE-2026-23980 is a SQL injection flaw (CWE-89) in Apache Superset affecting all releases before 6.0.0, exploitable via the sqlExpression and where parameters by authenticated users with read-level access. A public repository containing a Python exploit.py proof-of-concept has been released, reducing attacker effort against exposed instances. Apache disclosed the issue on February 24, 2026 and fixed it in Superset 6.0.0. Defenders should upgrade and monitor logs for malformed queries, database errors, and unusual activity from low-privilege accounts.

Cyber Security Newsupdated 09:23 UTC · 10h agofirst 08:04 UTC · 11h agoExploit / PoC 2 sources CVE-2026-239801

Saving Jet Fuel

Tutorial optimizes flight paths to cut jet fuel costs using open-source Scikit-decide planning framework and OpenAP aircraft performance models.

A technical walkthrough demonstrates wind-aware flight path optimization using Scikit-decide, an open-source framework for reinforcement learning and automated planning, paired with OpenAP fuel-consumption models built by Dr. Junzi Sun at TU Delft and NOAA wind data. A Boeing 787-9 flying EWR to FCO can require roughly $68K in fuel, and adjusted routing could save thousands. The post uses Python 3.12, DuckDB with spatial extensions, and QGIS for map rendering.

Hacker News · AISep 15, 23:17 UTC · 20h agoAI tools & infra HN 45↑ · 19 comments

CVE-2026-86792: Apache Airflow Apache Kafka provider: Connection-editor remote code execution on the Scheduler via Kafka connection callback configuration

Apache Airflow Kafka provider 1.15.0 before 2.0.0 resolves unvalidated dotted-path strings into Python callables, enabling Scheduler RCE.

CVE-2026-86792 (moderate) affects apache-airflow-providers-apache-kafka versions 1.15.0 before 2.0.0. Dotted-path strings in a Kafka connection's extra field are resolved into Python callables via import_string with no allowlist, then invoked by the confluent-kafka client. This allows someone with Kafka connection configuration access to achieve remote code execution on the Airflow Scheduler; upgrading to 2.0.0 resolves it.

oss-securitySep 15, 20:04 UTC · 23h agoVulnerability CVE-2026-867921

GhostCode Phishing Kit Bypasses Microsoft 365 MFA to Hijack Accounts in 78 Seconds

eSentire identified GhostCode, a phishing kit abusing Microsoft 365 OAuth device-code sign-in to steal tokens and take over accounts in seconds.

eSentire analysts identified GhostCode in late August, a phishing kit that uses business contact-form messages and an NDA pretext to deliver a password-protected HTML attachment leading victims to a Microsoft device-code sign-in. Victims authenticate on legitimate Microsoft pages, letting the kit obtain a Primary Refresh Token in 32 seconds and register three devices in 78 seconds, with residential proxies matching the victim's location. The kit hides its redirect with encrypted addresses, junk data, and scanner-filtering challenges, and uses GHOSTnet-linked infrastructure during device enrolment. eSentire recommends blocking device-code authentication via Conditional Access, invalidating tokens, and reviewing newly enrolled devices.

Cyber Security News14:54 UTC · 5h agoPhishing & fraud in the wild 9 sources

GhostCode Abuses Microsoft Entra Device Enrollment to Maintain Access After Token Revocation

eSentire exposes GhostCode, a device-code phishing kit that abuses Microsoft Entra device enrollment to persist even after stolen tokens are revoked.

eSentire's Threat Response Unit observed GhostCode campaigns in late August 2026, using BEC-style social engineering that impersonated procurement staff, including BJ's Wholesale Club, via Salesforce contact forms. Victims received password-protected HTML lures disguised as a FlipBook document portal, with junk-data padding, HTML comment injection, and AES-256-GCM encrypted redirects gated by anti-bot checks. The kit exploits the OAuth 2.0 device authorization grant, prompting victims to approve real Microsoft device-code sign-ins with MFA. Within 78 seconds of approval, attackers registered three Entra devices and obtained a Primary Refresh Token, so rogue device registrations persist even after session token revocation.

GBHackers13:41 UTC · 6h agoPhishing & fraud in the wild

PAPERMILL Malware Campaign Abuses Signed Notepad++ to Deliver VenomRAT to Windows Users

JUMPSEC tracks PAPERMILL, a China-nexus phishing campaign using a signed Notepad++ binary, libcurl.dll sideloading, and Donut loaders to deploy VenomRAT against Indian tax-audit targets.

PAPERMILL delivers ISO disk images via tax-audit phishing emails that passed SPF, DKIM, and DMARC, containing a renamed Authenticode-signed Notepad++ executable and a malicious libcurl.dll that proxies curl functions while executing loader logic in DllMain. The chain uses Mark-of-the-Web bypasses, anti-sandbox sleeps, UAC elevation prompts, Registry persistence, and a Donut shellcode loader to reflectively load .NET VenomRAT v6.0.3 with HVNC and credential-stealing capability, with C2 at 154.36.188.201:4449. JUMPSEC assesses the campaign as China-nexus, financially motivated, and Silver Fox-adjacent rather than definitively Silver Fox-operated.

GBHackersupdated 12:23 UTC · 7h agofirst 09:36 UTC · 10h agoMalware in the wild 2 sources

DeepZero: Open-source hunting for vulnerable Windows drivers

DeepZero, a new open-source engine, automates discovery of exploitable Windows kernel drivers for BYOVD attacks using Ghidra, Semgrep, and an LLM.

DeepZero is a free, open-source Python pipeline orchestrator that automates hunting for exploitable Windows kernel drivers relevant to BYOVD (bring your own vulnerable driver) attacks. Its seven-stage YAML pipeline parses PE headers, filters for kernel-mode drivers with IOCTL surfaces, excludes drivers listed on loldrivers.io, then runs headless Ghidra decompilation, Semgrep scanning, and an LLM-based exploitability assessment. The maintainer reports multiple verified vulnerabilities in the Snappy Driver Installer corpus, some still in the disclosure process, and notes findings involving plug-and-play-created device objects may need physical hardware to confirm.

Help Net Security05:30 UTC · 14h agoTools

Luciferus Uncensored AI Service Lets Cybercriminals Generate RAT Malware

Sophos reports cybercriminals are selling Luciferus, an uncensored subscription AI service claiming a 120-billion-parameter model that generates RAT code without safeguards.

Sophos Counter Threat Unit observed a user named Optimus_Prime advertising the Luciferus uncensored AI service on August 24, claiming a proprietary 120-billion-parameter model offering unrestricted coding assistance, with tiers priced at $35, $55, and $75. The public website shows different pricing ($22 to $47.14), and Sophos speculates with low confidence the service may be based on Alibaba's Qwen rather than a truly proprietary model. Researchers documented the Junior tier generating a basic Python RAT with network communication and command-execution functionality, though the code was not tested. The service follows the commercialization trend of WormGPT and FraudGPT in cybercriminal ecosystems.

GBHackers05:23 UTC · 14h agoAI safety & security1

Nums AI Releases Causilo: A Tabular Foundation Model That Tops TabArena Among Single Models

Nums AI released Causilo, an Apache-2.0 tabular foundation model achieving the highest single-model Elo (1794) on TabArena for classification and regression.

Nums AI released Causilo 1.0.1, a pretrained in-context learning tabular foundation model for classification (up to 10 classes) and regression, with Apache-2.0 code and research-only weights on Hugging Face. It achieved the highest single-model TabArena Elo of 1792.9 overall, beating TabFM (1764.4) and EXAONE Tabular (1758.8), and a maintainer re-run placed it 3rd of 88 including system entries. It also ranked first by CRPS, R² and RMSE on ScoringBench across 101 datasets, and was fastest on fit and predict versus TabICLv2 and TabPFN-3 on an H100 GPU at 8.15 GiB memory. The model was pretrained only on synthetic data, uses cross-attention to keep cost linear in feature count, and version 1.0.1 adds quantile outputs via 999 native quantiles.

MarkTechPost04:59 UTC · 15h agoModel release

Can Skills Learned in Games Transfer to Real-World Work?

Good Start Labs trains models in strategy games like 1830 and Diplomacy, showing terminal-agent training transfers to financial research benchmarks.

Good Start Labs, spun out of Every with $3.6M from General Catalyst and Inovia, trains AI models in verifiable strategy games. A 30B model trained as a multi-turn terminal agent in 1830: The Game of Railroads and Robber Barons improved Finance-Agent benchmark performance, while single-turn QA training did not transfer. The founders also co-authored COS-PLAY, a paper on co-evolving LLM decision and skill-bank agents for long-horizon tasks.

Latent SpaceSep 15, 20:11 UTC · 23h agoAI research