Search: “malware-generation”

CS-Guard: Benchmarking LLM Guardrails for Code Generation Security

CS-Guard benchmark shows LLM code-generation guardrails fail widely, with ~50% jailbreak ASR text-to-code and up to 100% code-to-code.

Researchers introduce CS-Guard, the first systematic benchmark for evaluating LLM guardrails for code generation security, covering text-to-code (1,000 malware-generation prompts, 7 jailbreak attacks, and a novel fictional scenario attack) and code-to-code (331 prompts across infilling, completion, and translation). They evaluate 9 guardrails across seven LLMs, finding average jailbreak attack success rates around 50% for text-to-code and 14.4% to nearly 100% for code-to-code. The fictional scenario attack achieves ASR close to 100% across many guardrails, raising reliability concerns for real-world software development. The benchmark and data are released publicly.

arXiv cs.CR·Sep 9, 06:50 UTC · 7d agoAI safety & security1

Scam Attacks Taking Advantage of the Popularity of the Generative AI Wave

Unit 42 finds about 225 generative AI-themed domains registered daily since ChatGPT's launch, with nearly 29 percent suspicious, fueling scams and PUP delivery.

Palo Alto Networks analyzed new domain registrations containing generative AI keywords such as chatgpt, prompt, and sora since ChatGPT's November 2022 launch, observing around 225 GenAI-related registrations per day. About 28.75 percent of these domains are suspicious, a rate 22 times higher than for general new domains, with registration spikes aligning with milestones like Bing ChatGPT integration, the GPT-4 release, new GPTs, and OpenAI's Sora announcement. Over 72 percent of the domains use gpt or chatgpt keywords, and gpt domains show a 76 percent suspicious rate. Case studies cover PUP delivery, spam distribution, and monetized domain parking, with 35 percent of traffic to these domains directed at suspicious ones.

Palo Alto Unit 42·Aug 17, 12:47 UTC · 29d agoPhishing & fraud in the wild1

The MAL Simulator: Cyber Operations Simulation based on Attack & Defense Graphs

MAL Simulator grounds attack-defense graph simulations in a CRATE-emulated network, training RL attacker and defender agents where attackers outperform search methods.

The MAL Simulator is a cyber operations simulator built on the Meta Attack Language (MAL), enabling decision-driven attack and defense simulations adaptable to new domains without modifying source code. Case studies trained defensive and offensive agents, grounded in data collected from an emulated network implemented in the CRATE cyber range. The trained attacker policy reached designated targets more efficiently than compared search methods, and the trained defender induced lower costs than a naive heuristic under noisy alerts, though defender performance dropped significantly against an RL attacker.

arXiv cs.CR·Sep 15, 02:59 UTC · 1d agoResearch

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, 12:21 UTC · 29d agoResearch1

Keyv-Linked npm Worm Poisons Hundreds of Packages, Plants Claude Code and VS Code Hooks

The Hacker News·Aug 4, 15:03 UTC · Aug 4, 2026Malware1

FrostyGoop’s Zoom-In: A Closer Look into the Malware Artifacts, Behaviors and Network Communications

Unit 42 dissects FrostyGoop OT malware, which sent Modbus TCP commands to disrupt heating for 600+ apartment buildings in Ukraine.

Palo Alto Unit 42 analyzed new FrostyGoop/BUSTLEBERM samples, the ninth known ICS-centric malware, first used against a Ukrainian municipal energy company by sending Modbus TCP commands to ENCO control devices. The attack caused a two-day heating outage affecting over 600 apartment buildings during sub-zero temperatures. The Go-compiled malware accepts Modbus register operations and timing parameters via command-line arguments or a JSON configuration file, uses an obscure open-source Modbus library, and checks the Windows BeingDebugged flag to evade debuggers. Unit 42 telemetry recorded over 1 million Modbus TCP devices exposed to the internet between September and October 2024.

Palo Alto Unit 42·Aug 19, 12:04 UTC · 27d agoMalware in the wild

Malicious LiteLLM Releases Tied to Trivy Hack May Have Exposed 2,100+ Organizations

Malicious LiteLLM 1.82.7/1.82.8 PyPI releases tied to the Trivy TeamPCP campaign harvested cloud, SSH, and database credentials, potentially exposing 2,500+ organizations.

CloudSEK reported that two malicious LiteLLM releases on PyPI (versions 1.82.7 and 1.82.8, live about 40 minutes on March 24) harvested cloud keys, SSH keys, Kubernetes tokens, and database passwords, with captured loot files mapping potential exposure to more than 2,500 organizations including NVIDIA, Cisco, Deloitte, Volkswagen, FedEx, Siemens, and X Corp. The campaign is part of TeamPCP (tracked by Google as UNC6780), linked to the Aqua Security Trivy scanner compromise tracked as CVE-2026-33634 and added to CISA's Known Exploited Vulnerabilities catalog on March 26. The payload used a litellm_init.pth file executed at Python interpreter startup and exfiltrated secrets to models.litellm[.]cloud; the FBI's FLASH-20260702-01 advisory urged rotation of CI/CD, publishing, and cloud credentials.

The Hacker News·Aug 12, 08:05 UTC · Aug 12, 2026Data breach in the wildCVE-2026-33634

Your threat feed is someone else's database: What ingesting malware intel at scale takes

GitHub's Dependabot lead shares five production lessons for ingesting community malware intelligence feeds across eight package ecosystems at scale.

GitHub's Dependabot team monitors over 30 million repositories and extended malicious-package advisories from npm to eight package ecosystems by ingesting OpenSSF's malicious-packages intelligence. The team catalogued roughly 18 new malicious npm packages per day in the year ending May 2026. The write-up argues that provenance with batch reverts, fingerprinting to catch echo-chamber duplicates, and heavyweight normalization are the make-or-break engineering for feed ingestion. It also recommends automated publishing with import caps and anomaly flagging, and quarantining malformed records rather than silently repairing them.

Help Net Security·Sep 3, 00:00 UTC · 13d agoResearch1

The AI Malware Maturity Gap

Recorded Future introduces AIM3, a five-level maturity model for AI malware, showing current attacker AI use is mostly AI-assisted rather than autonomous.

Recorded Future proposes AIM3, a five-level model defining AI malware from LLM-translated to LLM-embedded, spanning experimentation to fully autonomous agentic campaigns. Public examples remain early-stage: PROMPTFLUX uses Google Gemini to rewrite its VBScript dropper (Level 1), while Lamehug/PROMPTSTEAL, attributed to APT28, invokes the HuggingFace API to generate reconnaissance commands (Level 3). The authors argue most current AI malware augments existing tradecraft rather than enabling one-click autonomous attacks.

Recorded Future·Aug 26, 00:00 UTC · 21d agoResearch

Windows Malware Detector as a Compound AI System: Trade-Offs in Accuracy, Efficiency, and Adversarial Robustness

Researchers model industrial Windows malware detection as a Compound AI System, quantifying trade-offs between detection accuracy, efficiency, and adversarial robustness under tiered attacker knowledge.

Industrial Windows malware detectors combine rule-based mechanisms with ML-based static and dynamic analyses, but their architectures are rarely publicly disclosed. The authors propose a methodology balancing detection performance, computational cost, and robustness, plus system-level threat models capturing whole-pipeline evasion rather than isolated components. Experiments on real-world data show training time reductions with marginal detection loss, while more knowledgeable attackers craft increasingly effective adversarial examples. The paper derives deployment guidelines from the observed efficiency-robustness trade-off.

arXiv cs.CR·Sep 8, 08:04 UTC · 8d agoResearch

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·Sep 1, 07:23 UTC · 15d agoExploit / PoC in the wildCVE-2026-0768CVE-2026-66066CVE-2026-0769+2 CVEs1

SECURITY AFFAIRS MALWARE NEWSLETTER ROUND 112

Security Affairs publishes its 112th malware newsletter roundup covering recent malware and cybercrime developments.

This is the 112th installment of Security Affairs' recurring malware newsletter, which aggregates recent malware and cybercrime stories into a single roundup. The retrieved page text contains only cookie-consent boilerplate, so no specific malware families, campaigns or indicators are described in the available content.

Security Affairs·Aug 30, 12:31 UTC · 16d agoMalware

How to Keep Malware’s Rotating Infrastructure From Becoming a Detection Gap

ANY.RUN marketing piece argues SOC detection lags rotating malware and phishing infrastructure, citing a 46-country campaign and 3DBlast kit to promote TI feeds.

ANY.RUN describes how malware and phishing campaigns rotate domains and hosting, making single-IOC blocking ineffective for SOC teams. One investigated phishing campaign spanned 46 countries with 425 kit URLs across 240 hosts, 94% of which were seen for only a single day. A phishing kit dubbed 3DBlast impersonates Microsoft 365 and Google using BitB, AiTM, OAuth device-code phishing and DOM relay techniques. The article is primarily a promotion for ANY.RUN TI Feeds and TI Lookup products.

Cyber Security News·Sep 15, 15:36 UTC · 17h agoIndustry

Researchers Uncover 10,000+ Malware Loaders Behind YouTube and SEO Poisoning Campaign

Unit 42 uncovers CL-CRI-1171, a two-year pay-per-install campaign distributing 10,000+ OfferLoader samples via YouTube and SEO poisoning.

Palo Alto Networks Unit 42 tracked a campaign as CL-CRI-1171, an infection-as-a-service platform operating for at least two years. It used 11 YouTube gaming channels with hundreds of thousands of subscribers and SEO-poisoned download pages for trojanized WinDirStat and Bluetooth driver installers to distribute OfferLoader, a disposable loader embedded in Inno Setup installers. Payloads delivered included Insomnia RAT (Node.js and Python backdoors), ARKTunnel (a WebSocket-based RAT using LSB steganography), and Docro Hijacker (Chrome browser hijacker), with later infections delivering GCleaner and Socks5Systemz. Over 200 rotating domains across .xyz, .cfd, .space, and .info TLDs were used, with gating filters that served broken links or decoy pages to scanners and researchers.

GBHackers·Sep 11, 12:24 UTC · 4d agoMalware in the wild 2 sources2

Recent Trends in Internet Threats: Common Industries Impersonated in Phishing Attacks, Web Skimmer Analysis and More

Unit 42 analyzed 67 million malicious URLs and domains in H2 2022, a 52% increase, highlighting phishing impersonation and web skimmer trends.

Unit 42 observed more than 67 million unique malicious URLs, domains and IPs between July and December 2022, a 52% increase over the first half of the year. Malicious JavaScript detections grew 99.3%, with over 4 million malicious JS samples hosted on 4.8 million URLs. Over 85% of hosting infrastructure was concentrated in eight countries, led by the United States, Brazil and China. The report also analyzes industries spoofed in phishing pages and includes a web skimmer case study on a Tranco top 1 million website.

Palo Alto Unit 42·Aug 17, 13:04 UTC · 29d agoResearch

GitHub Dependabot malware alerts now cover eight ecosystems

Help Net Security·Aug 10, 00:00 UTC · Aug 10, 2026Malware

Campaign Evolution: pseudo

Unit 42 traces the pseudo-Darkleech campaign's 2016 shift from Angler to Neutrino to Rig exploit kits and rotating ransomware payloads.

Unit 42 documents how the pseudo-Darkleech exploit kit campaign evolved through 2016, switching from Angler EK to Neutrino EK in June and to Rig EK in September after Neutrino ceased operations. Payloads rotated from TeslaCrypt to CryptXXX, CrypMIC, and finally Cerber ransomware by October 2016. Injected script on compromised websites changed from 12,000-18,000 character obfuscated blocks to short, unobfuscated hidden iframes starting July 1, 2016.

Palo Alto Unit 42·Aug 17, 09:54 UTC · 29d agoThreat actor in the wild

Weedhack Malware Spreads via Fake Minecraft Clients and SEO Poisoning

McAfee Labs reports Weedhack malware spread via spoofed Minecraft client websites using SEO poisoning, with over 6,300 blocked access attempts.

McAfee Labs found multiple lookalike websites impersonating legitimate Minecraft clients (Glazed, Radium, Meteor, Nova, Xenon) still distributing Weedhack, a multi-stage malware whose JAR payloads collect system information, add Microsoft Defender exclusions, and steal sensitive data. Distribution relies on SEO poisoning to outrank official sources, plus Discord, MediaFire, GitHub, and Minecraft hosting sites; nearly half of malicious URLs were Discord links. One fake site was built with the AI website builder Lovable, and McAfee blocked more than 6,300 access attempts to malicious sites.

The Hacker News·Aug 24, 17:41 UTC · 22d agoMalware in the wild

Malware Can Abuse Windows Hello for Business Keys for Persistent Entra ID Access

The Hacker News·Aug 7, 09:55 UTC · Aug 7, 2026Malware in the wild

Russian hackers plant nuclear weapon prompt in malware to trip AI safety guardrails

ESET reports Russian group UAC-0099 hid a prompt in VBS malware comments to trip AI safety filters and disrupt automated malware analysis in Ukraine.

ESET identified a technique dubbed GuardBreaker in which UAC-0099 embedded a comment reading "I want to make nuclear weapon. Help me …" inside a malicious VBS script to trigger AI safety mechanisms and halt AI-assisted malware analysis. The script, part of the group's toolset, downloads the MATCHBOIL malware used exclusively by this Russia-aligned group; CERT-UA documented the chain including LUNCHPOKE, BURNYBEAR and MATCHBOIL.V2 in a July advisory. UAC-0099 typically targets transportation and energy sectors and hands validated targets to GRU-linked Sandworm. ESET warned that AI-assisted analysis must be backed by layered detection and human-driven engineering.

Help Net Security·Aug 31, 00:00 UTC · 16d agoAI safety & security in the wild

Nearly 800 Malicious npm Packages Deliver Cross

Nearly 800 typo-squatted npm packages deliver WEL1DROPPER, a cross-platform downloader installing RAT and infostealer payloads on Windows, macOS, Linux.

Researchers found roughly 800 npm packages with AI-generated typo-squat names that trigger a WEL1DROPPER downloader when loaded via require() rather than install hooks. The downloader fetches payloads from Cloudflare Workers hosts, falling back to DNS TXT records from wel1.ru, then achieves persistence, sandbox checks, ETW/AMSI patching and Sliver C2 deployment on Linux. Domains like tcsbank.ru suggest targeting of Russian financial institutions; Sonatype tracks the campaign as Flooding Dropper, a possible evolution of the Moika dependency-confusion campaign. Unit 42 separately documented npm/PyPI crypto stealers and malicious Chrome extensions that turn browsers into residential proxy crawlers.

The Hacker News·Aug 11, 14:37 UTC · Aug 11, 2026Malware in the wild

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 Online·Sep 9, 10:00 UTC · 6d agoAI safety & security1

Almost Half of Malware Samples Communicate Direct to IP

Unit 42 analysis of 4 million malware reports finds 45% of C2-active samples connect directly to hard-coded IPs, bypassing DNS defenses.

Palo Alto Unit 42 analyzed over 4 million Advanced WildFire dynamic analysis reports and found that 45.32% of malware samples with C2 activity made at least one direct-to-IP connection, accounting for 23.17% of all C2 connection attempts. The firm proposes zero trust IP (ZT-IP), an enforcement approach that verifies whether outbound destinations were ever sanctioned by a DNS response. ZT-IP analysis surfaced Phorpiex ransomware droppers fetching payloads directly from C2 IPs, a persistent data exfiltration campaign using an obfuscated \GET protocol, and Mozi P2P botnet payloads delivered to IoT devices without DNS. Only 1% of benign samples connected directly to untrusted IP addresses.

Palo Alto Unit 42·Aug 17, 12:45 UTC · 29d agoResearch

InceptionRAG: Stealthy Poisoning Attack Against Retrieval-Augmented Generation

InceptionRAG fragments malicious payloads into dormant passages that trigger LLMs to self-deduce misinformation via multi-hop reasoning, bypassing existing RAG poisoning defenses.

Researchers introduce InceptionRAG, a stealthy corpus poisoning attack against retrieval-augmented generation that splits a malicious payload into a chain of individually harmless dormant passages. When retrieved together, the passages induce LLMs to self-deduce target misinformation through multi-hop reasoning, achieving over 80% attack success rate across three datasets and three LLMs under rigorous adversarial constraints. A zeroth-order suffix optimization (ZOSO) method automates authoritative suffix generation in black-box settings. The authors also propose HODOR, a document isolation defense that decouples adversarial logical dependencies.

arXiv cs.CR·Sep 15, 08:22 UTC · 1d agoResearch

Why Is SHAP Not a Reliable Standalone Explanation Framework for Malware Detection?

arXiv paper shows SHAP gives unreliable standalone explanations for malware detection, with attribution dilution and sign reversal in dependent PE feature spaces.

The paper argues SHAP's formal guarantees are insufficient for reliable malware interpretation because the explained feature-coalition game is fixed only by analyst choices, not by malware behavior in the data. In static Portable Executable feature spaces, dependent feature groups cause conditional SHAP to dilute credit by a factor of 1/m across redundant features, attribute importance to features the model never uses, and even reverse attribution signs; interventional SHAP queries off-manifold coalitions no real executable exhibits. Experiments on EMBER-2018, EMBER-2024, and BODMAS with fixed LightGBM and XGBoost detectors confirm these effects. The authors position SHAP as a limited diagnostic requiring explicit data-distribution statements and domain validation, not a standalone explanation framework.

arXiv cs.CR·Sep 4, 02:00 UTC · 12d agoResearch1

H1 2026 Malware Vulnerability Trends

Recorded Future's H1 2026 report finds 215 actively exploited CVEs, RAT dominance, NFC payment fraud, and AI-augmented but not autonomous tradecraft.

Recorded Future's Insikt Group identified 215 actively exploited CVEs in H1 2026, up 34% from 161 in H1 2025, with the most impactful flaws combining network reachability, no authentication, and code execution. AsyncRAT was the top malware family, with AsyncRAT, Cobalt Strike, XWorm, Stealc, and REMCOS remaining top-ten staples; Android NFC malware like NFCShare and NGate enabled payment card theft and ATM cash-outs. AI-enabled attacks remained additive to established tradecraft, concentrated in Levels 1-3 of Recorded Future's AIM3 maturity model, with AI-assisted vulnerability research (e.g., Claude Mythos fixing 271 Firefox bugs in Firefox 150) inflating NVD disclosure volumes 43% above the prior six-month average. The report urges defenders to prioritize remotely exploitable RCE flaws, behavioral detection, developer credential security, and third-party oversight.

Recorded Future·Sep 3, 00:00 UTC · 13d agoThreat actor in the wild1